business plan sales forecast definition

What is a sales forecast: definition, importance, and how to build one

Posted November 16, 2021

By Serena Miller

Editor, Sales Best Practices at Outreach

Proper forecasting is essential for any sales organization. It’s a process that enables data-driven business decisions, helps revenue leaders identify new opportunities, and provides a clear picture of projected revenue.

Even so, building accurate sales forecasts is complex if you don’t know where to start, or if you’re not leveraging the types of tools that yield precise results.

In an August 2021 commissioned study conducted by Forrester on behalf of Outreach, almost one-third of B2B sales leaders said their forecasts were derived by selecting key deals and adding in qualitative analysis to arrive at their final number. 

However, this static and unscientific approach to forecasting makes it impossible to drive predictable business growth. If you’re not accurately and consistently forecasting your sales, you could be missing out on key insights that impact budget, hiring, scalability, and — ultimately — cash flow.

Here, we’ll take a deep dive into what a sales forecast is, how forecasting can benefit your organization, and how Outreach helps revenue teams bring science to the the traditional approach to sales forecasting. 

What is A Sales Forecast?

A sales forecast predicts  expected revenue over a given period of time. When used correctly, sales forecasts help teams to accurately estimate how much product or service they’ll sell, which helps to keep the expectations of reps, managers, leaders and other stakeholders on the same page.

Sometimes, the concept of a sales forecast is conflated with other related terms, like sales goal setting. But the two are actually quite distinct: sales goal setting is an expression of what you’d like to occur, while a sales forecast predicts what will actually happen — regardless of what you may have wanted to achieve.

Depending on the unique elements of your business (like age, size, existing systems of record, etc.), the level of detail and accuracy with which you forecast will vary. Forecasts are limited by their inputs, so you can only expect a high degree of precision if you have enough clean data to use.

Extremely accurate forecasts also require a range of complicated calculations, which is why many businesses have turned to technology for support. 

Why does sales forecasting matter?

If you already have clearly defined goals, a strong sales process , and a healthy pipeline, you might wonder if creating accurate forecasts is worth the effort. In short: yes, confident sales forecasting is an absolutely critical component of a company’s growth. 

Accurate forecasts support business growth

Consistent forecasting can improve both internal and external operations by helping your business:

• Efficiently plan for demand - In order to make sound decisions regarding hiring, supply chain management, and inventory, you need a clear understanding of what your operation will need to run smoothly. Because forecasts act as precise pictures of expected sales, each department within your business can use them to fully address staffing needs, product development, and budget before these factors ever become an issue.
• Make informed business investments - Whether you’re looking to develop a new product or boost customer service through increasing your staff, you first need the funds to actually cover those costs. Sales forecasting helps you better estimate incoming profit vs. anticipated costs, so you can make wise investments in the growth of your business without the risk of mismanaging your capital.
• Quickly uncover and resolve potential problems - Proper forecasting gives you transparency into your sales pipeline , so you can quickly identify trends that might otherwise cause significant issues.
• Improve your sales process - Your sales process should be modified based on what works and what doesn’t. Identifying areas that take longer than they should, have low conversion rates, or don’t meet customers’ needs is essential for refining your playbooks and closing more deals.

Multiple teams contribute to the forecasting process

Each sales organization is unique, so the person or team responsible for creating the forecasts often varies from one business to the next. In some instances, each sales rep is responsible for committing the deals they believe are likely to close. In others, revenue operations managers or sales leaders build forecasts to more objectively categorize and project their reps’ performance.

Regardless of who builds them, decision makers and stakeholders use sales forecasts to make choices about an organization's growth, how they’ll strategize that growth, and what kind of timeline they’ll need to succeed. Predictions in both short- and long-term performance help businesses uncover potential opportunities that help them scale.

Sales managers who rely on their reps to commit deals that feed into the forecast also find great value in confident forecasts, as they help ensure that reps’ deals are on track to close for the quarter. Managers need an easy way to gauge potential risk in their teams’ pipeline so they can focus on deals that are slipping, and forecasts provide them with the visibility to do just that.

Forecasts impact a variety of other departments, too. Product leaders rely on sales forecasts to evaluate and prepare for product demand, while finance teams use them to make investments. Sales forecasts are highly valuable to HR departments, too, as they’re frequently used to determine staffing needs.

Getting it right is easier said than done

That means getting it right (and doing so consistently) is a critical part of a business’s growth. In fact, sales organizations that utilize a formal, structured forecasting process increase their win rates of forecasted deals by 25% versus those that take a less formal approach.

But accurate sales forecasting is art and science — and many organizations don’t have the necessary skills. Less than 50% of sales leaders and sellers have confidence in their organization’s forecasting accuracy, as poor data quality and quantity threaten the precision of their process. These limitations are a result of some unfortunately common challenges among businesses, including:

• A lack of accurate, up-to-date data in their CRM
• An inability to identify and monitor key deal signals
• A lack of visibility into the numbers/math that drive their forecasts
• Manual, error-prone data entry processes

Sales Forecast Methods

Leveraging the proper tools can certainly help ensure forecasting accuracy, but you must also consider which method is right for your business. Forecasting isn’t a one-size-fits-all process: it’s a balancing act that requires a thorough understanding of context, relevance, and available data.

Thus, it’s important to keep in mind that there are some key factors you should take into account before settling on a particular forecasting method, including:

• The availability of historical data
• What time period the forecast will cover
• The realistic timeline for developing the forecast
• How accurate the forecast needs to be
• The purpose of the forecast

Once you’ve nailed down these considerations, you can more easily determine the forecast method that best suits your needs. There are several popular sales forecast methods from which to choose, each of which offers a distinct advantage:

How to Create a Sales Forecast

The forecasting process should be tailored to your unique business, based on your specific goals, available data, sales process, and tools for support. But to help get you started, we’ve outlined the most critical steps you should follow when building your forecast:

Choose a Sales Forecast Method

In the past, many organizations relied on qualitative methods for forecasting. But the art of selling has become much more of a science, with the emergence of tools and technologies that help form data-driven insights.

Competitive sales organizations should implement a forecasting method that uses reliable, actionable data to better inform business decisions moving forward. Revenue leaders can’t afford to use the inaccurate “guesstimation” methods of the past if they want to deliver predictable growth.

As you consider your options for forecasting methods, keep in mind that a quantitative, scientific, data-driven approach (backed by powerful analytics, user-friendly dashboards, and tools for complete pipeline visibility) is key to unlocking a clear competitive advantage.

Acknowledge Sales Forecast Assumptions

Your team’s performance — and the factors that impact that performance — are likely dynamic. As you build your sales forecasts, don’t forget that they’re based on assumptions instead of facts that are set in stone. They’re not crystal balls that can reveal the future, but they do offer helpful predictions based on an accumulation of information. Thus, you should make sure you have an up-to-date understanding of the following factors:

• Your products/services - You probably modify the cost of your products and services (and the products and services themselves) over time to better serve your customers and improve profitability. Make sure you take these changes into account, including any new product launches, current product updates, price or sales channel adjustments, and cost of production, labor, and materials.
• Market conditions/state of your industry - The industry in which your business operates can impact your growth, so it’s important not to ignore broader conditions and trends. Take a look at overarching changes in the economy, number of viable competitors, and size of your current and potential customer base.
• Regulatory changes - Some companies must operate under certain industry laws or regulations, so make sure you’re always up-to-date with any relevant legislation.
• Marketing inputs - Sales and marketing alignment can be challenging to achieve, but doing so can make forecasting that much easier. Bringing the two together can help you better understand how specific marketing activities (e.g. new marketing campaigns, changing advertising budgets, new marketing channels) impact overall sales performance, so make sure you take them into account.

Create Your Forecast

Armed with the specific elements needed for an accurate prediction, you’re now finally ready to build your sales forecast! It’s important to note that the following forecasting steps are just a starting point, as they reflect a simplified approach to the process. Of course, enterprise-level organizations require a more intricate approach that takes into account other market complexities.

If you’re a beginner, here are some basic steps to get you started with building a forecast:

• List out the goods and services you sell
• Estimate how much of each you expect to sell
• Define the unit price or dollar value of each good or service sold
• Multiply the number sold by the price
• Determine how much it will cost to produce and sell each good or service
• Multiply this cost by the estimated sales volume
• Subtract the total cost from the total sales

Once you have a fully defined sales forecast, you can leverage the results to drive your business goals.

Sales Forecast Examples: How to Commit with Confidence

The traditional approach to sales forecasting is filled with gaps, particularly for teams who use disparate systems and processes to manage the revenue cycle. Without a consolidated view of pipeline health and buyer insights, revenue leaders must guess their forecast, so they are perpetually at risk of surprise outcomes. They have dozens of dashboards, but they’re not sure they can trust the data. Instead, they are forced to rely on the gut intuitions of their whole team to inform their forecasting models.

But with a single, unified platform for support, forecasting can shift from a critical gap to a seamless, highly-valuable component of your business. Outreach Commit delivers real-time pipeline data and buyer engagement signals to bring science to the art of forecasting, enabling revenue leaders to go from guessing the future to changing it with recommended actions.

More Forecasting Resources for Sales and RevOps Teams

Today’s shifting economy means revenue leaders have to do more with fewer resources. So how do you deliver on lofty revenue targets while also reducing costs? It starts with more efficient forecasting processes. Instead of spending anxious hours on manual forecasts, modern revenue leaders are embracing ways to save time and refocus their energy on growing revenue. For Outreach's top resources on forecasting efficiency, download the free content bundle: Your Road to Forecasting Efficiency .

How an Account Executive uses Outreach

Sales productivity: Key metrics and how to boost them

How a sales manager uses Outreach to coach her team

Discover the sales execution platform.

Request a demo

The Last Guide to Sales Forecasting You’ll Ever Need: How-To Guides and Examples

By Kate Eby | January 26, 2020 (updated August 26, 2021)

• Share on Facebook
• Share on LinkedIn

Link copied

Sales forecasts are a critical part of your business planning. In this comprehensive guide, you’ll learn how to do them correctly, including explanations of different forecasting methods, step-by-step tutorials, and advice from experienced finance and sales leaders.

Included on this page, you'll find details on more than 20 sales forecasting techniques , information regarding how to forecast sales for new businesses and products , a step-by-step guide on how to forecast sales , and a free sales forecast template .

What Is Sales Forecasting?

When you produce a sales forecast , you are predicting what your sales or revenue will be in the future. An accurate sales forecast helps your firm make better decisions and is arguably the most important piece of your business plan. 

A sales forecast contrasts with a sales goal . The former is the realistic representation of what you believe will occur, while the latter is what you want to occur. Forecasts are never perfectly accurate, but you should be as objective as possible when creating a sales forecast. Goals, on the other hand, can be based on optimistic or motivational targets.

Because the sales forecast is critical to business planning, many different stakeholders in a company (beyond sales managers and representatives) rely on these estimates, including human resources planners, finance directors, and C-level executives. 

In this article, you’ll learn about different sales forecasting methods with varying levels of sophistication. The most basic method is called naive forecasting , which uses the prior period’s actual sales for the new period’s forecast and does not apply any adjustments for growth or inflation. Naive forecasts are used as comparative figures for more robust methods.

What Is Sales Planning?

A sales plan describes the goals, strategies, target customers, and likely hurdles for your sales effort. The sales plan defines your sales strategy and the method of execution you will use to achieve the numbers in your sales forecast.

Overview of Sales Forecasting Steps

Your sales forecasting model can ultimately become very sophisticated, but to grasp the basics, you should first gain a high-level understanding of what is involved. There are three primary steps to getting started:

• Decide which forecasting method or technique you will use. Also, determine the time period for your forecast. Later in this guide, we will review different methods of forecasting sales, including how to know which is best for your business.  
• Gather the data to plug into your forecast model. The data points will vary by method, but will almost always include your actual past sales and current growth rate.
• Pick a tool to support your forecasting effort. For learning purposes, you can start with pencil and paper, but soon after, you’ll want to take advantage of digital solutions. Common tools include spreadsheets, accounting software, and customer relationship management (CRM) or sales management solutions.

As you get going, remember not to be overly focused on complex formulas. Do regular reality checks to make sure your sales forecasts accord with common sense. Bounce forecasts off sales reps to get realistic feedback, and revise.

You will likely achieve greater accuracy if you build your forecasts based on unit sales wherever possible, because pricing can move independently from unit sales. Use data if you have it.

Benefits and Importance of Sales Forecasting

Sales forecasting helps your business by giving you data to make decisions concerning allocating resources, assigning staff, and managing cash flow and overhead. Using this data reduces your risk and supports your growth. 

Your sales forecast enables you to predict both short and long-term performance and customer demand for your product. In the short term, having a sales forecast makes it easy for you to spot when actual sales are not meeting estimates and gives you an opportunity to make corrections early in the period.

The forecast guides how much you spend on marketing and administration, and the projections generate your sales reps’ objectives. In this way, sales forecasts are an important benchmark for gauging the performance of your sales reps. 

Sales forecasts also lead to better management of inventory levels. With a good idea of how much product you will sell, you can stock enough to meet customer demand without missing any sales and without carrying more than you need. Excess inventory ties up capital and reduces profit margins. 

In the long term, sales forecasts can help you prepare for changes in your business. For example, you might see that within a few years, your company will require more manufacturing capacity to meet growing sales. To expand capacity, you may need to build a new factory, so now you can start planning how you will pay for it. Predictive sales forecasting is a critical part of your presentation if you are seeking equity capital from investors or commercial loans for expansion. 

In short, sales forecasting helps your business avoid surprises, so you aren’t making decisions in a crisis environment. Companies with trustworthy sales forecasts see a 10 percentage point  greater increase in annual revenues compared to counterparts without, according to research from the Aberdeen Group .

What Makes a Good Sales Forecast?

The most important quality for a sales forecast is accuracy. But, the benefits of accuracy must be weighed against the time, effort, and expense of the forecasting technique.

Useful sales forecasts are also easily understood and often include visual elements, such as charts, graphs, and tables, to make important trends visible. 

Ideally, you can quickly build a highly reliable sales forecast with simple, economical methods. The ultimate forecast method would automatically (i.e., without manual intervention) fetch the relevant data and make predictions using an algorithm finely tuned to your business. 

In reality, the forecasting process is more time consuming and subjective. Sales forecasts often depend on reps’ assessments of how likely their prospects are to close, and perceptions vary widely. (A conservative rep’s 60 percent probability may be understated, while another rep’s 60 percent may be overly optimistic.) 

Sales managers, who are usually responsible for forecasting, spend a lot of time factoring in these nuances and other market factors when calculating forecasts. 

Surprisingly, spending more time on forecasting does not always improve accuracy. According to research from CSO Insights, sales managers who spend 15 to 20 percent of their time producing their forecast had win rates for approximately 46.5 percent of deals. But, when they spend more than 20 percent of their time on forecasting, the win rate declined by more than two percentage points. 

An axiom of forecasting is that accuracy is highest during time periods that are close at hand and lowest during those that are far into the future. Short-term forecasts draw upon the following: deals that are already in the sales pipeline, the current economic environment, and actual market trends. So, the data underlying short-term forecasts is more reliable.

Forecasting for distant time periods requires bigger guesses about opportunities, demand, competitor activity, and product trends, so it makes sense that the forecast becomes less accurate the further into the future you go. (This concept applies to many companies, especially those that are young and growing; the concept becomes more relevant for all businesses at three years and beyond.) Bear this thought in mind when you look at your sales forecast in order to make long-term decisions.

Sales Forecasting Methods: Qualitative and Quantitative

Sales forecasting methods break down broadly into qualitative and quantitative techniques. Qualitative forecasts depend on opinions and subjective judgment, while quantitative methods use historical data and statistical modeling.

Qualitative Methods for Sales Forecasting

Sales forecasting often uses five qualitative methods. These are based on different ways of generating informed opinions about sales prospects. Creating and conducting these kinds of surveys is often expensive and time intensive. These five qualitative methods include the following: 

• Jury of Executive Opinion or Panel Method: In this method, an executive group meets, discusses sales predictions, and reaches a consensus. The advantage of this method is that the result represents the collective wisdom of your most informed people. The disadvantage is that the result may be skewed by dominant personalities or the group may spend less time reflecting.
• Delphi Method: Here, you question or survey each expert separately, then analyze and compile the results. The output is then returned to the experts, who can reconsider their responses in light of others’ views and answers. You may repeat this process multiple times to reach a consensus or a narrow range of forecasts. This process avoids the influence of groupthink and may generate a helpful diversity of viewpoints. Unfortunately, it can be time consuming.  
• Sales Force Composite Method: With this technique, you ask sales representatives to forecast sales for their territory or accounts. Sales managers and the head of sales then review these forecasts, along with the product owners. This method progressively refines the views of those closest to the customers and market, but may be distorted by any overly optimistic forecasts by sales reps. The composite method also does not take into account larger trends, such as the political or regulatory climate and product innovation. 
• Customer Surveys: With this approach, you survey your customers (or a representative sample of your customers) about their purchase plans. For mass-market consumer products, you may use market research techniques to get an idea about demand trends for your product.  
• Scenario Planning: Sales forecasters use this technique most often when they face a lot of uncertainty, such as when they are estimating sales for more than three years in the future or when a market or industry is in great flux. Under scenario planning, you brainstorm different circumstances and how they impact sales. For example, these scenarios might include what would happen to your sales if there were a recession or if new duties on your subcomponents increased prices dramatically. The goal of scenario planning is not to arrive at a single accepted forecast, but to give you the opportunity to counter-plan for the worst-case scenarios.

Quantitative Methods for Sales Forecasting

Quantitative sales forecasting methods use data and statistical formulas or models to project future sales. Here are some of the most popular quantitative methods:

• Time Series: This method uses historical data and assumes history will repeat itself, including seasonality or sales cycles. To arrive at future sales, you multiply historical sales by the growth rate. This method requires chronologically ordered data. Popular time-series techniques include moving average, exponential smoothing, ARIMA, and X11. 
• Causal: This method looks at the historical cause and effect between different variables and sales. Causal techniques allow you to factor in multiple influences, while time series models look only at past results. With causal methods, you usually try to take account of all the possible factors that could impact your sales, so the data may include internal sales results, consumer sentiment, macroeconomic trends, third-party surveys, and more. Some popular causal models are linear or multiple regression, econometric, and leading indicators.

Sales Forecasting Techniques with Examples

In reality, most businesses use a combination of qualitative and quantitative methods to produce sales forecasts. Let’s look at the common ways that companies put sales forecasting into action with examples.

Intuitive Method

This forecasting method draws on sales reps’ and sales managers’ opinions about how likely an opportunity is to close, so the technique is highly subjective. Estimates from reps with a lot of experience are likely to be more accurate, and the reliability of the forecast requires reps and managers to be realistic and honest.

This method can be especially helpful if you do not have historical data or if you are assessing  new prospects early in your funnel. In these cases, a rep’s gut feeling after initial contact can be a good indicator. If you are a manager, you will review reps’ estimates with an eye for any outliers and work with those reps to make any necessary adjustments. 

Here is an example of the intuitive method in action: You manage a team of four sales reps. You go to each one and inquire about the leads they are nurturing. You ask each rep which opportunities they believe they will win in the next quarter and how much those sales will be worth. John, your strongest rep, tells you $175,000. Alice, another strong performer, says $115,000. Bob, who is in his second year at your company, reports $85,000. Jennifer, a recent college graduate, projects $100,000. You calculate the total of those forecasts and arrive at an intuitive forecast of $450,000. However, you suspect Jennifer’s forecast is unrealistic, because she is inexperienced, so you ask her more questions. Based on what you learn, you decide that only half of Jennifer’s deals are likely to close, so you reduce her contribution to $50,000 and revise your total quarterly forecast to $400,000.

Scenarios Method

Scenario forecasts are qualitative and involve you projecting sales outcomes based on a variety of assumptions. This process can also be a helpful business planning exercise, because once you identify major risks or uncertainty for your company, you can develop action plans to deal with these circumstances if they arise.

Scenario forecasts require an in-depth knowledge of your business and industry, and the quality of the forecast will vary with the expertise of the person or group who prepares the estimate.

To create a scenario forecast, think about the key factors that affect sales, external forces that could influence the outcome, and major uncertainties. Then, write a narrative and numerical description of how the scenario would play out under various combinations of these key factors, external forces, and uncertainties.

Here is an example of the scenarios method in action: Your company sells components for military vehicles. You notice that the most impactful things your sales reps do are meeting with procurement officers in the defense departments of major nations and holding factory tours and product demonstrations for them. These are your key factors. 

The external forces are the number of tenders or requests for proposals that military procurement departments announce, and the value of those items. The risk of conflict in various parts of the world, scarcity of your raw materials, and trends in budget authorizations for defense by major countries are your critical uncertainties. 

You look at how your key factors, external factors, and major uncertainties might combine. One scenario might entail the outcome if your reps increased the number of meetings and product events by 20 percent, the value of U.S. tenders launched rose by six percent, and France decreased defense spending by two percent. 

Under this scenario, you might forecast a six percent increase in unit sales resulting from the following: 

• Having more in-person sales contacts should boost sales by five percent based on past performance.
• You can increase revenue by three percent due to greater U.S. tender opportunities and your current market share.
• Major customer France will not purchase anything, reducing sales by two percent.

Sales Category Method

The category forecasting method looks at the probability that an opportunity will close and divides opportunities into groups based on this probability. The technique relies somewhat on intuition, as does the intuitive method, but the sales category method brings more structure and discipline to the process.

The categories that each company uses vary widely, but they correspond broadly to stages in the sales pipeline. These are some typical labels and definitions:

• Omitted: The deal has been lost or the prospect is no longer engaging. 
• Pipeline: The opportunity will not realistically close during the quarter.
• Possible, Best Case, Upside, or Longshot: There is a realistic possibility that the deal could close at the projected value in the quarter if everything falls into place, but this is not certain. Overall, fewer than half of the opportunities in this group end up closing in the quarter at the planned value.
• Probable or Forecast: The sales rep is confident that the deal will close at the planned value in the quarter. Most of these opportunities will come to fruition as expected.
• Commit or Confident: The salesperson is highly confident that the deal will close as expected in this quarter, and only something extraordinary and unpredictable could derail it. The probability in this category is 80 to 90 percent. Any deal that does not close as forecast should generally experience only a short, unanticipated delay, rather than a total loss.
• Closed: The deal has been completed; payment and delivery have been processed; and the sale is already counted in the quarter’s revenue. 

To compile your forecast, look at the combined value of the potential deals in the categories under three scenarios:

• Worst Case: This is the minimum value you can anticipate, based on the closed and committed deals. If you have very good historical data for your sales reps and categories and feel confident making adjustments, such as counting a portion of probable deals, you may do so, but it is important to be consistent and objective.
• Most Likely: This scenario is your most realistic forecast and looks at closed, committed, and probable deal values, again with possible adjustments based on historical results. For example, if you have tracked that only 60 percent of your probable deals tend to close in the quarter, adjust their contribution downward by 40 percent.
• Best Case: This is your most optimistic forecast and hinges on executing your sales process perfectly. You count deals in the closed, commit, probable, and possible categories, with adjustments based on past performance. The possible category, in particular, requires a downward adjustment.  

As the quarter or period progresses, you revise the forecast based on updated information. This method can quickly get cumbersome and time consuming without an analytics solution.

Here is an example of the sales category method in action: You interview your sales team and get details from the reps on each deal they are working on. You assign the opportunities to a category, then make adjustments for each scenario based on past results. For example, you see that over the past three years, only half the deals in the possible category each quarter came to fruition. Here’s what the forecast looks like:

Top-Down Sales Forecasting

In top-down sales forecasting, you start by looking at the size of your entire market, called the total addressable market (TAM), and then estimate what percentage of the market you can capture. 

This method requires access to industry and geographic market data, and sales experts say top-down forecasting is vulnerable to unrealistic objectives, because expectations of future market share are often largely conjecture.

Here is an example of top-down sales forecasting in action: You operate a new car dealership in San Diego County, California. From industry and government statistics, you learn that in 2018, 112 dealers sold approximately 36,000 new cars and light trucks in the county. You represent the top-selling brand in the market, you have a large sales force, and your dealership is located in the most populous part of the county. You estimate that you can capture eight percent of the market (2,880 vehicles). The average selling price per vehicle in the county last year was $36,000, so you forecast gross annual sales of $103.7 million. From there, you determine how many vehicles each rep must sell each month to meet that mark.

Bottom-Up Sales Forecasting

Bottom-up sales forecasting works the opposite way, by starting with your individual business and its attributes and then moving outward. This method takes account of your production capacity, the potential sales for specific products, and actual trends in your customer base. Staff throughout your business participates in this kind of forecasting, and it tends to be more realistic and accurate. 

Begin by estimating how many potential customers you could have contact with in the period. This potential quantity of customers is called your share of market (SOM) or your target market . Then, think about how many of those potential customers will interact with you. Then, make an actual purchase.

Of those who do purchase, factor in how many units of your product they will buy on average and then how much revenue that represents. If you aren’t sure how much your customers will spend, you can interview a few. 

Here is an example of bottom-up sales forecasting in action: Your firm sells IT implementation services to mid-sized manufacturers in the Midwest. You have a booth at a regional trade show, and 3,000 potential customers stop by and give you their contact information. You estimate that you can engage 10 percent of those people in a sales call after the trade show and convert 10 percent of those calls into deals. That represents 30 sales. Your service packages cost an average of $250,000. So, you forecast sales of $7.5 million.

Market Build-Up Method

In the market build-up method, based on data about the industry, you estimate how many buyers there are for your product in each market or territory and how much they could potentially purchase. 

Here is an example of the market build-up method in action: Your company makes safety devices for subways and other rail transit systems. You divide the United States into markets and look at how many cities in each region have subways or rail. In the West Coast territory, you count nine. To implement your product, you need a device for each mile of rail track, so you tally how many miles of track each of those cities have. In the West Coast market, there are a total of 454 miles of track. Each device sells for $25,000, so the West Coast market would be worth a total $11.4 million. From there, you would estimate how much of that total you could realistically capture.

Historical Method

The historical sales forecasting technique is a classic example of the time-series forecasting that we discussed under quantitative methods. 

With historical models, you use past sales to forecast the future. To account for growth, inflation, or a drop in demand, you multiply past sales by your average growth rate in order to compile your forecast. 

This method has the advantage of being simple and quick, but it doesn’t account for common variables, such as an increase in the number of products you sell, growth in your sales force, or the hot, new product your competitor has introduced that is drawing away your customers.

Here is an example of the historical method in action: You are forecasting sales for March, and you see that last year your sales for the month were $48,000. Your growth rate runs about eight percent year over year. So, you arrive at a forecast of $51,840 for this March.

Opportunity Stage Method

The opportunity stage technique is popular, especially for high-value enterprise sales that require a lot of nurturing. This method entails looking at deals in your pipeline and multiplying the value of each potential sale by its probability of closing. 

To estimate the probability of closing, you look at your sales funnel and historical conversion rates from top to bottom. The further a deal progresses through the stages in your funnel or pipeline, the higher likelihood it has of closing.

The strong points of this method are that it is straightforward to calculate and easy to do with most CRM systems. 

But, opportunity-stage forecasting can be time consuming. 

Moreover, this method doesn’t account for the unique characteristics of each deal (such as a longtime repeat customer vs. a new prospect). In addition, the deal value, stage, and projected close date have to be accurate and updated. And, the age of the potential deal is not reflected. This method treats a deal progressing quickly through the stages of your pipeline the same as one that has stalled for months. 

If your sales process, products, or marketing have changed, the use of historical data may make this method unreliable.

Here is an example of the opportunity stage method in action: Say your sales pipeline comprises six stages. Based on historical data, you calculate the close probability at each stage. Then, to arrive at a forecast, you look at the potential value of the deals at each stage and multiply them by the probability.

Length-of-Sales-Cycle Method

This is another quantitative method that shares some similarities with the deal stage method. However, this model looks at the length of your average sales cycle. 

First, determine the average length in days of your sales process. This figure is also known as time to purchase or sales velocity . Add the total number of days it took to close all of the past year’s deals and divide by the number of deals. Then, calculate the probability of new deals closing in a certain period of time as a percentage of the average sales cycle length. 

With this method, the biases of individual reps are less of a factor than with the deal stage model. Also, with this technique, you can fine-tune the probabilities for different lead types. (For example, prospects referred by current customers may close in an average of 27 days, while prospects who make contact after an online search need an average of 62 days.) But, this technique requires you to know and record how and when prospects enter your pipeline, which can be time intensive.

Here is an example of the length-of-sales-cycle method in action: You review the 37 deals your company won last year and see that they took a total of 2,997 days to close. To calculate the average length of the sales cycle, you divide 2,997 by 37 and see that the average sales cycle lasted 81 days. You then look at the five deals currently in your pipeline.

Lead Scoring Method

This technique requires you to have lead scoring in place. With lead scoring, you profile your ideal customers based on attributes (like industry, size, and location) as well as behavior (such as whether they have recently raised capital or whether the contact person has requested a demonstration of your product). 

You then classify future leads based on how closely they match your ideal customer. You can label the categories with distinctions such as A, B, or C or hot, warm, or cold, or you can assign numbers up to one hundred using formulas that add and subtract points for different attributes and behaviors. (For example, “They requested a demo, which adds 15 points, but they are not in your ideal industry, which subtracts 10 points.”)  

To create your forecast, you then look at the historical close rate for leads in each category and multiply that by the value of the opportunities currently in the group. 

Here is an example of the lead scoring method in action: Your company sells textbooks for advanced math and science. Your ideal customer is a university with at least 25,0000 students that has an engineering school and is located on the east coast. These are your A prospects. B prospects have at least 10,000 students. C prospects have at least 10,000 students, but are located elsewhere in the country.

You then look at the close rates and potential deal values for each lead score. Finally, you multiply the close rate by the potential value of the deals in the category or by your average sales value.

Lead Source Method

This model forecasts future sales based on how you acquired the lead, using the behavior of previous leads as a benchmark.

For example, say your company sells a software application. Some leads come from search traffic to your website; some originate with demonstration requests at conferences, and some are referrals from existing customers. 

Look at your historical data to track the percentage of leads who converted to sales for each lead source. In addition, calculate the average value of a sale for each source. Then, by using the conversion probability and sales values, you can forecast the sales that the leads at the top of your funnel are likely to generate. 

Here is an example of the lead source method in action: Based on source, you compile your historical data and discover the following conversion rates and sales value for leads.

One advantage of this sales forecasting method is that you can project how many leads of each type you would need to generate in order to hit a target. Suppose you have a conference coming up where participants will be able to request demonstrations of your product, and you would like to win an additional $30,000 in sales from the demo leads. Based on the average lead value of $600, you know you will want to generate 50 leads who request demos at the conference. 

One drawback to lead source forecasting is that the method does not account for potential differences in the length of the sales cycle for the lead types. That makes it difficult to pinpoint the period in which the revenue will occur. Therefore, you should do a separate analysis of time to purchase in order to allocate sales to the right period.

Another challenge is that sometimes you may not be sure of the lead source. For example, suppose that another customer has recommended your product to a contact and that that contact decides to first check you out on your website. You might very well assign a lower lead value to this prospect, assuming they will behave like our web-originated leads, when, in reality, they will probably behave more like the customer referral leads. 

Lastly, remember that this method won’t account for changes in your marketing or pricing that influence conversion rates and customer behavior.

Sales by Row Method

This method is a good fit for small businesses that sell different products or services. Rather than forecasting sales for each individual product type, you project sales for categories. 

Each row in your forecast will cover different physical products (such as pick-up trucks, heavy trucks, and delivery vans) and service units (such as hours of labor or service types like replacing a faucet, unclogging a drain, or installing a toilet). 

You can employ this method to forecast units and then factor them by average prices to arrive at revenue. Or, you can look exclusively at revenue. If you sell a subscription service, you can calculate recurring revenue for each product type.

For each row, you would look at how much you sold in the same period a year earlier and then adjust for factors such as inflation, organic growth, new products, increased workforce, or special circumstances.

Here is an example of the sales by row method: You operate a combination fuel station and mini-market. Your forecast would cover the broad categories of your business, such as sales of gasoline, diesel, food, beverages, and sundries.

For March’s forecast, you take into account that the new housing development near your business, which was under construction last year, is now almost completely sold and that there are many more commuters filling up. Your gas sales have been growing by almost 15 percent year over year. Also, in March, there will be a special event at the nearby fairgrounds that could draw thousands of additional vehicles to your area. 

On the downside, a new retail complex with a full-service grocery store has opened nearby, so your sales of food and drinks have slipped. Also, increased congestion in the neighborhood has caused some long-haul truckers who used to stop for fuel to reroute.

Regression or Multivariable Analysis Method

Regression or multivariable analysis is one of the most sophisticated forecasting methods, and allows you to build a custom model combining any factors that you feel are relevant to your sales.

For regression analysis, you need accurate historical data on all the variables under consideration, expertise in statistics, and, for practical purposes, an analytics solution or application that can perform the analysis. 

Because this method incorporates a multitude of influences on your sales, the resulting forecast is the most accurate. But, the costs tend to be high because of the data collection, expertise, and technology requirements.  

Regression analysis looks at the dependent variable (the factor that you are trying to predict, in this case, the amount of future sales) and independent variables (the factors that you believe affect sales results, such as opportunity stage or lead score). 

In a simple example, you would create a chart, plotting the sales results on the Y axis and the independent variable on the X axis. This chart will reveal correlations. If you draw a line through the middle of the data points, you can calculate the degree to which the independent variable affects sales. 

This line is called the regression line , and, by calculating the slope of the line, you can use numbers to represent the relationship between the variable and sales. The equation for this is Y = a + bX. Excel and other software will perform this analysis and calculate a and b for you. In more sophisticated applications, the formula will also include a factor for error to account for the reality that other variables are also at work.

Going further, you can look at how multiple variables interplay, such as individual rep close rate, customer size, and deal stage. Making these kinds of calculations becomes increasingly difficult with simple charts and demands more advanced math knowledge. 

Remember that correlation is not the same as causation. Bear in mind that while two variables may seem closely related to each other, the reality may be more subtle. 

Here is an example of the regression method in action: You want to look at the relationship between the amount of time a prospect has progressed in your sales cycle and the probability of the deal closing. 

So, plot on a chart the probability of close for past deals when they were at various stages of your sales cycle, which lasts an average of 100 days. Deals early in the sales cycle have a low probability of closing compared to those that occur in the later stages of negotiation and contract signing on day 85 and up. (Be sure to eliminate any prospects that stall or disengage at any stage.)

By drawing a line through those points (i.e., the intersection between the sales close probability and the percentage of the average sales cycle), you can see that there is a nearly one-to-one relationship between percentage point increases in time elapsed relative to the average sales cycle and percentage point increases in the probability of closing.

This calculation becomes more complex when you consider multiple variables. Let’s say you have two sales reps working with prospects. Gloria, your best closer, is giving a product demonstration to a new Fortune 500 account. Leonard, a strong performer, whose close rate is a little lower than Gloria’s, is negotiating with a repeat customer, a mid-sized company. 

Your multivariable analysis of these situations could take into account each rep’s average close rate for an opportunity, given the following factors: the specific stage; deal size; time left in the period; probability of close for a repeat customer versus a new customer; and time to close for an enterprise customer with more than 10 people involved in decision making versus a mid-sized business with a single decision maker.

Time Horizons in Sales Forecasting

Choosing the time period for your sales forecast is an important step. Depending on your business, the purpose of your forecast, and the resources you can devote to making forecasts, the time frame you target will vary. 

A short-term forecast will help set sales rep bonus levels for next quarter, but you need a long-term forecast to decide whether you should plan to build a new factory. A startup that has been doubling revenue every year will have more difficulty making a 20-year forecast than a century-old concern in a mature industry. Here are the three time frames for forecasts: 

• Short-Term Forecasts: These cover up to a year and can include monthly or quarterly forecasts. They help set production levels, sales targets, and overhead costs.
• Medium-Term Forecasts: These range from one to four years and guide product development, workforce planning, and real estate needs.
• Long-Term Forecasts: These extend from five to 20 years and inform capital investment, capacity planning, long-range financing programs, succession planning, and workforce skill and training requirements.

Getting Started with Sales Forecasting: What You Need to Know

Regardless of the sales forecast method you use, you generally need to have certain pieces of information and conditions in place. These include the following:

• Well-Documented and Defined Sales Process: You need to understand your customer journey and have an established sequence for nurturing each prospect. Without this, you cannot predict which opportunities are getting closer to purchasing. This structure creates accountability. 
• Consensus on Pipeline Stages: Your sales team needs to have a clear and shared understanding of what you mean by lead, prospect, qualified, possible, probable, committed, and other relevant terms. 
• Definition of Success: Communicate clearly what your sales team is striving for in terms of sales quotas or goals; include these quotas and goals for each individual rep, for the team as a whole, and for conversion through each stage of your pipeline.
• Historical Data: You require benchmarks for data points, such as average time to close, conversion rates, average deal size, lifetime customer value, win-loss ratio, and seasonal sales trends. These sales metrics and KPIs are often critical pieces of your forecast.
• Current Status: Up-to-date knowledge of your pipeline is essential, including how many opportunities are at each stage and the potential value of these sales.
• Forecasting Tools: This will almost always include a CRM application and may also include financial management or accounting software, analytics solutions, and spreadsheets.

Influences and Assumptions in Sales Forecasting

Sales forecasting should not happen in a vacuum. Take into account changes in the business environment and question assumptions, such as that past growth will continue. Also, be sure to factor in your ideas about global economic trends and competitor behavior.

Here are some common factors to consider regarding your sales forecast. Many of these can have either a positive or negative influence on sales. For example, changing reps’ account assignments may reduce sales, because members of your team will have to familiarize themselves with customers that are new to them. However, sales could increase if your new hotshot gets your biggest opportunity.

• Economic Trends: Inflation, growth, consumer sentiment, risk appetite, and purchasing power
• Regulation: Trade policies such as tariffs, duties, and quotas; health, safety, and environmental rulings on products or processes; court decisions; intellectual property disputes; and competition policy
• Seasonal Trends: Cyclical demand fluctuation, production patterns, and variation in raw material availability 
• Competitor Behavior: New product innovations, pricing changes, and market entries and exits
• Business Economics: Selling prices, direct prices, unit costs, gross margins, and the impact of accrual versus cash accounting on when you can book a sale
• Staffing and Compensation: Hiring or firing new reps, changes in leadership, policies on commissions and bonuses, and training
• Territory Management: Redrawing of territories and changes in account assignments
• Products and Services: Product lifecycle, new products and services, user experience, defects, ticket resolution, changes in distribution, and market entries and exits
• Marketing: Demand generation, advertising, pricing, special campaigns, social media activity, and prospecting

Sales Forecasting for New Businesses and Products

If you are starting a new business or launching a new product, your sales forecasts are crucial because they will determine how much you can spend in order to break even. However, when dealing with a new entity, you lack the advantage of historical data, which you need for almost every forecasting technique. 

If you don’t have historical data, you can use industry benchmarks from trade publications, industry associations, and consultants. For example, if you are launching a new recipe app, look at market research on how other cooking apps have performed. 

Dining establishments can look at number of tables, hours of service, and menu prices to estimate average order amounts and table turnover. Retail outlets use square feet, foot traffic, and average selling prices to forecast sales.

If you are adding a new product to your line, you can forecast sales by looking at how your most similar existing product performed at launch. Then, you can make tweaks based on other relevant information, such as that the new product is harder to master than its predecessor, that it is a later entrant into a crowded space, or that it already has a backlog of orders before launch.

New service businesses can base forecasts on capacity, such as number of staff and service hours and how much to charge for the most popular services. Once you have this data, you can make adjustments accordingly.

Michael Barbarita, President of Next Step CFO , works as a contracted CFO to produce sales forecasts for companies. He likes to tie the sales forecast for service businesses to a metric called sales per direct labor hour , which you can calculate this by dividing sales by the working hours of people in the field performing customer work. For example, an electrical contractor would calculate the sales per direct labor hour of its electricians and multiply that figure by the number of electricians and the hours they work.  

For instance, you may decide that operating at half capacity is a good estimate for your first six months in business. Then, you may operate at three-quarters capacity for the second six months. Therefore, you would multiply maximum capacity by average revenue and then multiply that resulting figure by 0.50 and 0.75, respectively.

Quick-Start: Sales Forecasting Formulas

If you are eager to dive in and want to generate some simple sales forecasts, you can make use of basic equations. Here are a few easy ones:

• Simple Forecast with No Organic Growth: This formula assumes that this period will duplicate the prior period, except for the impact of inflation.  Revenue Prior Period) + (Revenue Prior Period x Inflation Rate) = Sales Forecast  
• Historical Plus Growth: This formula helps you reflect current trends.You look at the prior year and then factor it by your recent growth rate. (Last Year Revenue x Percentage Growth Rate) + Last Year Revenue = Sales Forecast
• Partial Year: In this method, you project the rest of the year based on historical patterns and early results. Imagine that you know your sales for the first two months of the year and that last year these months represented seven and nine percent of your sales respectively and totaled $100,000. Using the formula below, you would forecast sales of $625,00 for the year: ($100,000 x 100) ÷ 16 = $625,000. (Current Period Revenue x 100) ÷ Percent That Equivalent Period Represented Last Year = Forecast Sales
• Pipeline Formula: This formula replicates the opportunity stage method that we discussed earlier. You calculate the value of deals at each stage of your pipeline by multiplying the potential deal value by the close probability and adding up the result for each stage. (Deal Amount x Close Probability) + (Deal Amount x Close Probability) etc. = Sales Forecast

How to Make a Basic Sales Forecast Step by Step

Here are step-by-step instructions for a manually generated sales forecast:

• Pick Your Time Period: The way in which you will use your forecast determines the most appropriate time interval, whether that be monthly, quarterly, annually, or on an even longer timeline. If you are making your first forecast, estimating on a monthly or quarterly basis for the upcoming year is a good starting point. Experts suggest doing monthly estimates for the first year and then doing annual forecasts for years two through five. 
• List Products or Services: Write down the items or services that you sell. If you have a lot of them, group them into categories. For example, if you sell clothing, your rows might include shirts, pants, and shoes. Match these revenue streams to the way you organize your accounting. So, if your books look at women’s and men’s clothing separately, do the same for your sales forecast. That way, you can pair your sales forecast with information on your cost of goods sold and overhead to project profit.  
• Estimate Unit Sales: Predict how many units you will sell in the selected time period. If you have historical data, use that and then factor in assumptions about demand for the upcoming period. For example, is your business growing? Is the economy in recession? Did you launch a big promotion? Use the answers to these questions to make downward or upward adjustments to the historical figure. You can also interview some customers to get insights into their likely purchasing plans. Lastly, don’t forget to factor in seasonal fluctuations. 
• Multiply by the Selling Price: Multiply the unit sales numbers by the average selling price (ASP). Determine the ASP by analyzing historical sales and adjusting for inflation and other factors. To obtain this figure, you also need to consider discounts, free trials, and unsold inventory. 
• Repeat for Each Forecast Period: Go through the same calculation for each category and time interval. As you forecast more distant periods, your estimates are likely to be less accurate, so you may want to make a range of forecasts, such as for best, worst, and average scenarios. As time passes, add the actual values and fine-tune your forecast. For instance, you may see that for the first few months of the year, you underestimated sales by 12 percent. Therefore, you decide to increase your forecasted sales amounts in the upcoming months.

How to Forecast Sales in Excel

Here is a step-by-step guide to building your own sales forecast in Excel:

• Enter Historical Data: Open a worksheet and enter your past date data in the first column. Then, in the second column, enter the corresponding sales values. If possible, make sure you space the dates consistently (e.g., the first day of every month). 
• Create Forecast: In the date column, fill out the next date cell with the future date you are forecasting. Select the corresponding sales value cell and in the function field, type: =(FORECAST( A10, B2:B9, A2:A9)), where A10 is the future date cell, B2 to B9 are the historical sales amounts, and A2 to A9 are the historical dates. Hit enter and the forecast sales amount will appear.
• Repeat: Continue the pattern for your remaining future dates. Remember that the formula uses only known variables, so do not add forecasted amounts to the cell ranges. This function is a linear forecasting method.
• Power Up: If you have Excel 2016, you can use the forecast sheet function, which automates forecasting and adds a chart. To use this function, select both data columns, and, on the data tab, click the forecast sheet. In the create forecast worksheet box, select whether you want a line or bar chart. In the forecast end field, choose an ending date and then click create. Excel will create a new worksheet that contains both historical and forecast sales data as well as a visual representation. 

For a pre-made basic sales forecast, download this template that projects product sales with both units and sales amount.

Basic Sales Forecast Sample Template

Excel | Google Sheets | Smartsheet

For a wide range of pre-built sales forecast templates in a variety of formats, see this comprehensive collection .

How to Choose the Right Sales Forecasting Methodology

Your goal is to build the most reliable forecast possible, with the minimum amount of resources you need to be effective. To choose the method that fits best, consider these seven questions:

• Is the Time Frame Short, Medium, or Long Term? Qualitative methods are a good choice for short-term horizons, but they generally underperform quantitative methods for periods beyond a few months. Similarly, consider where you are in your business or product lifecycle. If you are ramping up or in a high-growth phase, you may be making costly investment decisions, so you need a method with a high degree of accuracy, but also relatively quick production time. When you are in a mature phase of your business, decisions about production and marketing are more routine. 
• How Much Data Do You Have? The less data you have, the more likely you will be to select a qualitative technique. If you have limited data, you will turn toward more simplistic models. A company that has collected a lot of data and has great confidence in its reliability can choose sophisticated quantitative models. 
• How Relevant Will History Be in Predicting the Future?  If your business has undergone big changes, such as launching major new products, experiencing large growth in the sales force, or introducing a different pricing structure, your past results will have less value as a guide to future performance. So, methods that diminish the weight put on historical data and qualitative techniques are a better choice.  
• In Terms of Time and Money, How Much Does It Cost to Produce the Forecast? How Does This Cost Compare to the Value of the Potential Benefits?You will need to make tradeoffs between the time and cost to build your forecast and the potential benefits, such as cost savings. Also, consider the potential cost of error. For example, suppose you are contemplating a high-cost sales-forecasting technique (one that takes a lot of data gathering, the creation of a custom model, and expensive staff and technology to produce). The forecast could allow your company to reduce the amount of inventory it holds. Weigh the value of inventory savings against the forecasting cost. If you reduce inventory and the forecast proves inaccurate, what are the potential costs of lost sales — because you did not stock adequately or because you did not cut back enough?  
• What Degree of Accuracy Do You Need?  Forecast accuracy rises with the cost and complexity of the methodology. Depending on how you will use the forecast, the size of your company, and the variability of your business, you may feel that it’s not cost effective to produce a maximum-accuracy forecast. If you are a giant global company, a fraction of a percentage point error in your sales forecast could represent many millions. So, the bigger the dollar values, the more meaningful every degree of enhanced accuracy becomes.
• How Complex Are the Factors That Will Drive the Forecast?   If your sales dynamic is straightforward — the more sunny days there are, the more beach umbrellas you sell at your beach kiosk — then building a sophisticated, AI-driven forecasting model will be overkill. “It's important not to spend time and energy developing a complex model, when a much simpler one will do the job,” says Nicholas. But when you are facing a subtle and complex interplay of variables, you need a technique that accounts for them. Suppose you have new products, changes in your marketing, and additional sales reps. A sophisticated model would allow you to forecast the net effects and also try out different scenarios in which the variables fluctuated.

Why Accuracy Is Important in Sales Forecasts

According to CSO Insights, 60 percent of forecasted deals do not close and 25 percent of sales managers are unhappy with the accuracy of their forecasts. Inaccuracy in sales forecasts causes problems for businesses and impacts performance. 

People throughout your company depend on your forecasts to make a multitude of decisions — from pay raises to real estate acquisitions. Let’s look at some of the important reasons to strive for accuracy:

• Early Warning: Your sales forecast helps you spot trouble early, like when revenues are not materializing as expected; the forecast also allows you to intervene and problem solve before this underperformance becomes a crisis.
• Decision Making: The forecast gives leaders confidence and a sound basis for deciding how much and where to spend or invest. Production planners, HR, and others will use the forecast.
• Goal Setting: You set achievable targets for sales reps when you have an accurate forecast. Goal setting prevents sales reps from getting discouraged by unrealistic expectations. Following this strategy also ensures that your commission and bonus scale are calibrated appropriately. 
• Customer Satisfaction: When you are prepared for the right level of demand, your company can improve its record of fulfilling orders on time and in full.
• Inventory Management: You will be more likely to have the right level of inventory if your sales forecasts are accurate. Making accurate predictions allows you to better manage your supply chain and order raw materials or parts in a timely fashion. You also gain more control over your pricing if you have the right amount of inventory. When you have to resort to discounting to get rid of excess inventory, your profitability suffers.

How to Improve Sales Forecast Accuracy and More Best Practices from Experts

Producing high-quality forecasts takes organizational commitment and long-term effort, and best practices will help improve accuracy.

”Sales forecasting is both an art and a science. Where companies tend to go wrong is relying too heavily on one or the other. You need a consistent process and reliable data,” says Charlene DeCesare, CEO of sales training and advisory firm Charlene Ignites .

She emphasizes five best practices:

• Ensure that the pipeline feeding the forecast is accurate. You don't need historical data to predict the future when you have a well-defined sales process.
• Everyone must use the CRM, and should enter notes and coding opportunities in a clear, consistent way. 
• Buyer behavior is a much more reliable predictor of future sales than gut feel. Challenge optimism that doesn't align with the applicable stage in the sales cycle or isn't supported by clear, mutually agreed-upon next steps.
• In general, buyer/seller behavior is the leading indicator to rely upon. Too many companies rely on results, which is actually the lagging indicator.
• Sales leadership can have a huge impact. Sales reps must be rewarded for both honesty and accuracy. Sales forecasting must be an individual, team, and company priority. 

Rob Stephens, a CPA whose firm CFO Perspective advises businesses on forecasts, adds: “A big planning mistake is spending too much of your precious time trying to find the one right scenario… Start with a range of reasonable forecasts based on solid fundamentals. For example, you may project from historical growth rates, customer indications of future sales, or projections of market growth. A company with a new product may need to extrapolate from existing products or early indications from potential customers. Use a higher-probability scenario as a beginning base scenario, but identify why the future may deviate from it.”

Common Mistakes and Pitfalls in Sales Forecasts

Sales pros say they see the same sales forecasting errors on a regular basis and that these often relate to letting the discipline of the forecasting process lapse. 

“The most common operational mistakes are basing forecasts on hope rather than evidence, ignoring repeated close date slippage, failing to take into account the historic forecast accuracy (or inaccuracy) of the salesperson concerned, and failing to hold salespeople accountable for the relative accuracy of their forecasts,” notes Bob Apollo, Founder of Inflexion-Point Strategy Partners, a sales training firm.  

“The most common cultural mistake is when sales leaders press salespeople to forecast a target number without any evidence or confidence that it will actually be achieved," he notes.

Evan Lorendo , Director of Revenue Accelerator, which advises service companies on revenue strategies, says he sees companies with monthly recurring revenue (MRR), such as software as a service (SaaS), frequently make mistakes in sales forecasting.

He gives the example of a company with an MRR product that wants to generate $120,000 in revenue a year. How much in new sales do they need each month? “Most of my clients say $10,000/month, but that is wrong. Because a client is paying on a monthly basis, a client that signs up in January is actually paying 12 times during the year. On the flip side, a client signing up in July will make six payments during the year,” he explains. 

That means there are a total of 78 potential payment configurations per year, not 12. The customer who buys in January will make 12 payments, but November’s buyer will make two. (12 + 11 + 10 + 9 + 8 + 7+ 6 + 5 + 4 + 3 + 2 + 1 = 78.)

“If you want to know how much you need to sell in new sales each month to hit that $120,000 goal, the answer is $1,539 ($120,000/78). That actually seems much more manageable, doesn't it? Based on poor forecasting, a miscalculation can turn off good salespeople who can't hit their quota,” he says.

KPIs for Sales Forecasting

As your sales forecasting improves, you reap bigger benefits, such as better planning and higher profits. So, you will want to assess and monitor your forecasting effort by using key performance indicators (KPIs).

Below are the main KPIs for sales forecasting. Some of them draw from statistics concepts, such as standard deviation, and computer applications and statistics guides can help you calculate them.

• Bias or Variance: This KPI tells how much the actual results deviated from the forecast over a given period of time. Calculate bias as an absolute number of dollars or units or as a percent of sales. A positive number means sales exceeded projections and a negative number indicates underperformance. Actual Units - Forecast Units = Bias
• Mean Absolute Deviation (MAD): This metric describes the size of your forecast error in total units or dollars. You calculate how much the actual results deviated from the forecast average, add the deviations, and divide the result by the total number of data points.   
• Mean Absolute Percentage Error (MAPE): This is similar to MAD, but gives the forecast error as a percent of sales volume. 
• Tracking Signal: This is another expression of forecast error and looks at how the error rate varies among forecast values. Normally, you expect all forecast amounts to be wrong by about the same degree. If, from one data point to another, there is a large variation in the error rate, you need to rework your model.  Tracking Signal = Accumulated Forecast Errors ÷ Mean Absolute Deviation
• Forecast Value Added: This metric measures how much better the forecast was than simply using unadjusted historical data. If your forecasting effort got you closer to actual than the so-called naive forecast (i.e., using historical figures as your forecast), you have added positive value. You calculate this metric by comparing the MAPE of your forecast to the naive forecast.
• Linearity: This looks at how sales are paced over the course of the period. As your reps seek to meet quota, you might see a flurry of deals at the end of the quarter. Or, deals might be spread evenly across the time period. The most stable situation is a deal cadence or velocity that is constant. If expressed as a trend line, this stable situation would appear visually as a flat line. This pattern is called highly linear .

Application of Sales Forecasting

Your sales forecast obviously gives you an idea of how much you will sell in the future, but sales forecasting has other important use cases. Here are five ways you can apply your forecast to business questions:

• Sales Planning: As noted earlier, your sales plan encompasses your goals, tactics, and processes for achieving your sales forecast. As part of this plan, your sales forecast helps you decide if you need to hire more sales reps to achieve your forecast and if you need to put more energy and resources into marketing.
• Demand Planning: Demand planning is the process of forecasting how much product your customers will want to buy and making sure inventory aligns with that forecast. In ideal conditions, forecast demand and sales would be virtually the same. But, consider a scenario in which your new product becomes the hot gift of the holiday season. You forecast demand of 100,000 units (the number consumers will want to buy). A large shipment turns out to be defective, and the product is unsellable. So, you forecast sales of just 75,000 units (how much you will actually sell.)   
• Financial Planning: Your sales forecast is vital to the work of your finance department. The finance team will rely on the forecast to build a budget, manage overhead, and figure out long-term capital needs. 
• Operations Planning: The unit-sales numbers in your forecast are also important for operations planners. They will look at the production required to meet those sales and confirm that manufacturing capacity can accommodate them. They will want to know when sales are likely to rise or fall, so they can avoid excess inventory. A big increase in sales will also require operations managers to make changes in warehousing and distribution. Retailers may change the product mix at individual stores based on your sales forecast.
• Product Planning: The trends you foresee in sales will have big implications for product managers too. They will look at products that you forecast as top sellers for ideas about new products or product modifications they should introduce. A forecast of declining sales may signal it is time to discontinue or revamp a product.

Levels of Maturity in Sales Forecasting

Sales forecasts can be simply scribbled-down estimates, or they can be statistical masterpieces produced with the aid of the most sophisticated technology. The style you pursue relates in large part to your level of forecasting maturity (as well as the size and history of your business). 

Below is a description of the four levels of the sales forecasting maturity model:

• Level One: In the beginning stages of sales forecasting, the estimates are usually not very accurate and take a lot of time to produce. The forecasting process depends on reps’ best guesses, and sales managers spend a lot of time gathering these guesses by interviewing each rep. Then, they roll them up into a consolidated forecast. Inconsistent data collection and personal bias can skew the results. Sales managers use spreadsheets, which quickly become outdated, and the forecasts often reflect little more than intuition.
• Level Two: As your forecasting culture grows, you are probably still inputting data by hand, and the forecast is often inaccurate or outdated. But, a CRM solution is enabling your team to have a shared repository for contacts, sales activity, and deal status. Reps don’t see value in spending time contributing to the forecast, and quality is weak. Your CRM automatically aggregates those results, so you can start to examine trends and anomalies. But, your system is not very flexible, and forecasting remains unwieldy and resource intensive.
• Level Three: At this point, automation starts to offer radical improvements in sales forecasting. Solutions backed by artificial intelligence automatically bring together data from a multitude of sources, including email, CRM, marketing platforms, chat logs, and calendars. There is no more manual data entry, and sales managers gain increased visibility into the sales pipeline. KPIs become reliable and an important tool for monitoring performance.
• Level Four: Technology ensures sales that data is accurate and timely. AI and machine learning find patterns and correlations in your historical data, and predictive analytics offer robust forecasting. The forecasting model is continually refined. Forecast accuracy rises, and sales managers can focus more of their time on supporting reps and developing opportunities. These tools make it apparent when reps are sandbagging or being too optimistic, and accountability increases.

Advances in Sales Forecasting Methodologies

While sales forecasting has been around as long as private enterprise, the field continues to evolve, and researchers are looking at ways to improve sales forecasting methodologies. 

Indiana University Professor Douglas J. Dalrymple performed an influential study in 1987 that surveyed how businesses prepared sales forecasts. He found that qualitative and naive techniques predominated, but that early adopters were reducing errors by using computer analysis. At this time, PCs were starting to proliferate and come down in price. 

By 2008, Zhan-Li Sun and his researchers at the Institute of Textiles and Clothing at Hong Kong Polytechnic University were experimenting with an advanced AI-driven technique called extreme learning machine to see if they could improve forecasts for the volatile retail fashion industry by quantifying the influence of factors such as design on sales.  

Scholars F.L. Chen and T.Y. Ou at the National Tsing Hua University in Taiwan took this further with a 2011 study. The study documented sales forecasting advances when combining extreme learning-machine, so-called Taguchi statistical methods for manufacturing quality with novel analysis theories that work on variables with imperfect information.

Features to Look for in a Sales Forecasting Tool

Paper forecasts and Excel spreadsheets quickly become cumbersome. Sales forecasting capability is available in CRM software, sales analytics and automation platforms, and AI-driven sales technology. These capabilities often overlap among these applications.

Here are some of the features to look for when evaluating a sales forecasting tool:

• Integrations with other software, such as ERP, CRM, marketing suites, contact management, calendars, and more
• Automated collection of data and sales rep activity
• Real-time reporting
• Robust data security
• Analytics and automated scoring of deals
• Insights on most promising deals
• Scenario modeling
• Lead scoring
• Automated forecast roll-ups or summaries by category and team
• Dashboards and graphic displays of KPIs
• Benchmarking
• Customizable forecasting algorithms
• Forecast auditing and error analysis

Improve Sales Forecasting with Smartsheet for Sales

Empower your people to go above and beyond with a flexible platform designed to match the needs of your team — and adapt as those needs change. 

The Smartsheet platform makes it easy to plan, capture, manage, and report on work from anywhere, helping your team be more effective and get more done. Report on key metrics and get real-time visibility into work as it happens with roll-up reports, dashboards, and automated workflows built to keep your team connected and informed. 

When teams have clarity into the work getting done, there’s no telling how much more they can accomplish in the same amount of time.  Try Smartsheet for free, today.

Discover why over 90% of Fortune 100 companies trust Smartsheet to get work done.

Close more deals with the latest sales trends and tips from Salesblazers.

The Complete Guide to Building a Sales Forecast

Set your company up for predictable revenue growth with the right forecasting processes and tools.

Paul Bookstaber

Share article.

• Link Copied

Building a sales forecast is both an art and a science. Accurate sales forecasts keep your leaders happy and your business healthy. In this guide, we’ll explain everything you need to know about sales forecasting — so you can get a clear picture of your company’s projected sales and keep everyone’s expectations on track.

We’ve organized this reference guide by the top questions sales teams have about the sales forecasting process, based on our internal conversations and more than 20 years of experience developing  sales solutions .

Build sales forecasts with accuracy

Use the real-time data updates and insights of Sales Cloud to keep your forecasts accurate and your teams on track to hit targets.

What you’ll learn:

What is a sales forecast, why is sales forecasting important, who is responsible for sales forecasts, who uses sales forecasts, what are the objectives of sales forecasting, how do i design a sales forecasting plan.

• What happens to sales forecasting in unpredictable times?

How accurate are sales forecasts?

What tools do you use to forecast sales revenue and how do crm systems forecast revenue, how is forecasting better with crm vs. other methods.

If you’re a sales leader who’s already well-versed in the who and what of sales forecasts, skip to the sections on  designing a sales forecasting plan  and  tools to improve sales forecasts  for more relevant knowledge. Sales forecasting can become especially tough when we face an unexpected turn of events, so head to the section on  what happens to sales forecasts in unpredictable times  for more on that.

A sales forecast is an expression of expected sales revenue. A sales forecast estimates how much your company plans to sell within a certain time period (like quarter or year). The best sales forecasts do this with a high degree of accuracy, and they’re only as accurate as the data that fuels them.

A strong data culture is at the heart of an accurate sales forecast. This means all sales data is available to everyone at the company, and all teams do their part in keeping it updated, leaning on AI and automation to help. More on that in the section on  tools used to forecast sales revenue .

All sales forecasts answer two key questions:

• How much:  Each sales opportunity has its own projected amount it’ll bring into the business. Whether that’s $500 or $5 million, sales teams have to come up with one number representing that new business. To create the number, they take everything they know about the prospect into account.
• When:  Sales forecasts pinpoint a month, quarter, or year when the sales team expects the revenue to hit.

Coming up with those two sales projections is no easy feat. So sales teams factor in the important ingredients of who, what, where, why, and how to make their forecasts:

• Who:  Sales teams are responsible for sales forecasting.
• What:  Forecasts should be based on the exact solutions you plan to sell. In turn, that should be based on problems your prospects have voiced, which  your company can uniquely solve .
• Where:  Where is the buying decision made, and where will the actual products be used? Sales teams see better accuracy when they get closer (at least for a visit) to the center of the action.
• Why:  Why is the prospect or existing customer considering new services from your company in the first place? Is there a compelling event making them consider it now? Without a forcing function and a clear why, the deal may stall inevitably.
• How:  How does this prospect tend to make purchasing decisions? If you’re not accounting for how they do it now and how they’ve done it in the past in your forecast, it may be fuzzy math.

Forecasting lets leaders set realistic sales targets, create attainable and motivating quotas for sales reps, and gauge expected revenue, aiding in budgeting and spending decisions for the whole company. If forecasts are inaccurate, businesses may overspend (putting themselves in a risky spot), and set unreachable quotas (which is demoralizing for reps).

To understand why sales forecasting is so important to business health, think about two example scenarios: one with a car manufacturer and another with an e-commerce shop.

In the case of a car manufacturer, cars take a long time to build. The manufacturer has a complex supply chain to ensure every car part is available exactly when they need to build cars, so the number of cars available to purchase will meet demand.

When you buy something online, whether that’s from a large marketplace or a small boutique, you get a delivery estimate. If your delivery comes a day or a week after it’s promised, that’ll affect your satisfaction with the company — and decrease your willingness to want to do business with them again.

Sales forecasting is similar in both cases. Sales forecasts help the entire business plan resources to ship products, pay for marketing, hire employees, and beyond. Accurate sales forecasting yields a well-oiled machine that meets customer demand, both today and in the future. And internally on sales teams, sales revenue that delivers in its estimated time period keeps leaders and collaborators happy, just like a shipment that arrives on time.

If forecasts are off, the company faces challenges that affect everything from pricing to product delivery to the end user. Meanwhile, if forecasts are on point and  sales quotas  are met, the company can make better investments, perhaps hiring 20 new developers instead of 10, or building a much-needed new sales office in a prime new territory.

Get articles selected just for you, in your inbox

Each organization has its own sales forecast owners. These are some of the teams who are usually responsible:

• Product leaders:  They put a stake in the ground for what products will be available to sell when.
• Sales leaders:  They promise the numbers that their teams will deliver. Depending on the seniority of the leader, how they forecast varies. For example, first-line managers forecast collections of opportunities, where third-line managers consider a wide set of numbers and traditional close rates to come up with an overall forecast.
• Sales reps:  They report their own numbers to their managers.

No matter how a company calculates its sales forecasts, the process should be transparent. And at the end of the day, sales leadership has to be responsible to call a number. Whether met, exceeded, or missed, the forecast responsibility falls on them.

Sales forecasts touch virtually all departments in a business. For example, the finance department uses sales forecasts to decide how to make annual and quarterly investments. Product leaders use them to plan demand for new products. And the HR department uses forecasts to align recruiting needs to where the business is going.

At some level, sales forecasting affects everyone in the company.

The main objective of sales forecasting is to paint an accurate picture of expected sales. Leaders are looking to these numbers when they’re building out their operational roadmap and budget. If they’re confident in the projected growth, they can get to planning.

They could decide to staff more customer service touchpoints, fund more external marketing events, or invest more in the community. They could get ahead of purchasing new equipment or upgrades that get more expensive the longer they wait. Without a sales forecast, leaders are making critical spending decisions in the dark. If sales don’t go as planned, it could lead to cutting workforce, reducing support, or halting product development.

Sales forecasting is a muscle, not an item to check off your to-do list. While you should absolutely design a framework for your sales forecasting plan each year, you should also change up your strategies from time to time so new muscles develop.

Craft a sales forecasting plan with your team by focusing on three primary activities:

• Calculating number and time  period:  Your plan should explain how you’ll calculate the estimated monetary amount and what the timeframes will be. See the section on  how a CRM can help with forecasting  later in this guide for more on the sales forecasting tools you can use to do this.
• Reviewing and revising:  You should also plan to review the forecast at key milestones and revise it if necessary. Most sales leaders track progress against their forecast daily! But you’ll also want to schedule designated check-ins throughout the quarter. Make sure you’re reviewing the latest numbers with  sales automation tools  that sync your CRM’s forecast data.
• Breaking the patterns:  Even the best sales organizations need to shake up their  sales process  once in a while. Breaking your patterns can help you find new ways of crafting even more accurate forecasting. Try skip-level forecasting, ask different questions, have executive sponsorship reviews, and take different angles of the data.

Trending Articles

3 Ways Generative AI Will Help Marketers Connect With Customers

Learn AI Skills on Trailhead

What happens to sales forecasts in unpredictable times.

Unpredictable events have an enormous impact on your sales forecast. Extreme weather or economic crises all dramatically change your forecast. What you thought you knew about expected revenue growth can be suddenly flipped on its head.

As soon as an extraordinary event hits, sales and finance leaders at your company will quickly want to know:

• How’s our  sales pipeline  looking today?
• What are the best- and worst-case scenarios?
• How has the forecast changed from a week or a month ago?

Your forecast implicates resourcing, headcount, and more (see the section on  sales forecasting objectives ). So although things may be changing quickly, you don’t want to give up on your forecast.

Rather than attempt to recalculate your forecast based on dubious estimates or conjecture, your best bet is to  rely on a CRM solution  to get an accurate view of deal status and pipeline in real time.

During a crisis, reps need to feed their CRM with data as events unfold so leaders have clear visibility into the rapidly evolving pipe. That data enables those leaders to support their reps with corporate-level decisions about where they should be focusing their time — and craft the new forecasts. Your forecast is only as good as the data coming into it from your sales teams.

In uncertain times, quick access to sales data and the ability to pivot  sales territory  and resource deployment accordingly can make the difference between business continuity and dissolution. There’s no silver bullet to forecast perfectly in a crisis or unforeseen scenario. But vigilantly updating what’s in the pipeline and analyzing sales data more frequently than usual will help you see trends and retool your forecast accordingly.

Empathy and care are always fundamental, but this is especially true in these situations. Empathizing with your customers’ challenges and caring for your own sales reps should come before anything else. Build trust with internal and external partners. That trust will help you grow again in the future. Learn more about  maintaining customer relationships as a sales leader .

Only 45% of sales leaders are confident in their organization’s sales forecasts,  according to Gartner . While it’s natural for sales reps to bring in some intuition to their sales forecasts, that’s where room for error can creep in.

This brings us back to embracing a  strong data culture . To get a more accurate forecast, everyone in the sales cycle — from reps to managers to execs — should have a stake in making sure those numbers reflect the latest reality. Reps can keep all prospect info up to date, managers can track pipeline progress, and leaders can review how all teams are tracking toward those forecast numbers, with AI playing backup to spot any inaccuracies or chances to adjust along the way.

A  CRM  gives sales leaders a real-time view into their entire team’s forecast. The tool forecasts revenue by giving you:

• An accurate view of your entire business.  Comprehensive forecasts in a CRM come with a complete view of your pipeline.
• Tracking of your top performers.  See which reps are on track to beat their targets with up-to-the-minute leaderboards.
• Forecasting for complex sales teams.  Overlay splits allows you to credit the right amounts to sales overlays, by revenue, contract value, and more.

A forecast is based on the gross rollup of a set of opportunities. You can think of a forecast as a rollup of currency or quantity against a set of dimensions: owner, time, forecast categories, product family, and territory. You can collaborate on forecasts with all the necessary people to see how opportunities are stacking up. Drill down into opportunities by sales leader, operating unit, manager, and individuals.

We also love a CRM with  reports and dashboards . These highlight where the business challenges are, in plain and simple terms. It could be that four of five selling teams are at the right growth rate, and we just need to focus on another one. It could be that a certain product is challenged. The data opens up new doors to grow sales and see what could be working more effectively.

Another thing that’s great about a CRM is the guidance from AI. An  AI for sales  tool offers a neutral perspective on what’s actually happening in sales. For example, AI might note that an opportunity has been pushed out three quarters in a row — a finding that would’ve taken an individual reviewing the data longer to discover. Think of AI as your personal data scientist, taking your forecasting and entire sales operations to a new level.

Predictive AI tools take a look at historical sales data to give you a glimpse of what you might expect in the future. The AI will analyze factors like win rate or number of customer meetings. It takes some of the guesswork out of sales forecasting and helps you get to more accurate numbers. Try to analyze sales data for at least 12 months. Otherwise, there may not be enough data to get accurate sales predictions.

Sales forecasting is significantly more accurate when using a CRM instead of a spreadsheet. When a company is just starting out, sales teams usually rely on spreadsheets or back-of-the-napkin ways to calculate their sales forecasts. This may work for a while, but eventually, you’ll find this doesn’t scale.

The reality is, selling is more complex than ever. It involves everything from how demand generation campaigns are performing to how your phone calls to prospects are landing. The more you want to sell, the more you’ll want to  rely on a CRM .

See how Salesforce manages forecasts with confidence

The secret to an accurate forecast? Reliable, well-maintained pipelines. See how we manage both efficiently (with the help of the right technology), and use our best practices in your business.

Just For You

Uncapped Earnings: The Benefits of Limitless Commission

A Close Look at At-Risk Pay and the Purpose Behind Performance-Based Compensation

Explore related content by topic

• Experience Cloud
• Sales Cloud
• Revenue Cloud
• Service Cloud
• Customer Experience
• Salesblazer
• Forecasting
• Sales Management

Paul Bookstaber is a writer at Salesforce. He has a decade of experience in content marketing in B2B tech. Before that, he published a magazine and ran a tabloid blog. Today, he splits his time between Florida and the Mountain West, and loves to hike, ski, and watch Bravo. He is in a polyamorous relationship with Luke and Roger, who are cats.

Get the latest articles in your inbox.

How Presales Sets the Stage for Your Team’s Next Big Deal

The Sales Team’s Guide to Using Mutual Action Plans

Why Are Commission Caps So Rare in Modern-Day Sales?

What Is Sales Performance Management? Examples and Tips

How to Calculate Your Sales Growth Rate (with Examples)

Why Incentive Compensation Matters – and How to Build the Program that Suits Your Business

Why Sales and Marketing Have to Work Together if You Want to Win

27 Top Sales Influencers You Should Follow in 2024

New to Salesforce?

• What is Salesforce?
• Best CRM software
• Explore all products
• What is cloud computing
• Customer success
• Product pricing

About Salesforce

• Salesforce.org
• Sustainability

Popular Links

• Salesforce Mobile
• AppExchange
• CRM software
• Salesforce LIVE
• Salesforce for startups
• América Latina (Español)
• Brasil (Português)
• Canada (English)
• Canada (Français)
• United States (English)

Europe, Middle East, and Africa

• España (Español)
• Deutschland (Deutsch)
• France (Français)
• Italia (Italiano)
• Nederland (Nederlands)
• Sverige (Svenska)
• United Kingdom (English)
• All other countries (English)

Asia Pacific

• Australia (English)
• India (English)
• Malaysia (English)
• ประเทศไทย (ไทย)

© Copyright 2024 Salesforce, Inc. All rights reserved.  Various trademarks held by their respective owners. Salesforce, Inc. Salesforce Tower, 415 Mission Street, 3rd Floor, San Francisco, CA 94105, United States

Ready to up your game? Subscribe now.

Sales Forecasting 101: Definition, Methods, Examples, KPIs

• April 4, 2023

Sales forecasting is a crucial business exercise.

Accurate sales forecasts allow business leaders to make razor-sharp decisions about quota-setting, budgeting, headcount, and revenue.

By contrast, an inaccurate sales forecast leaves sales managers wondering whether they’ll actually hit quota.

Let’s look at what sales forecasting is, and some of the basics you need to get it right.

Table of contents

What is a sales forecast, what you need for accurate sales forecasts, sales forecast methodology, sales forecasting examples.

• Sales forecasting tools
• Key takeaways

A sales forecast is a prediction of future sales revenue . Just like a weather forecast, your team should view your sales forecast as a plan to work from, not a firm prediction.

What is a sales forecast based on?

Sales forecasts are usually based on historical data, industry trends, and the status of the current sales pipeline.

What are sales forecasts used for?

Businesses use the sales forecast to estimate weekly, monthly, quarterly, and annual sales totals.

Pro tip: Sales forecasting is different from sales goal-setting . A sales goal describes what you want to happen. A sales forecast estimates what will happen.

1. Get reliable data

Good data is the most important requirement for a good sales forecast. That means that  getting hold of good data is crucial .

Is your company fairly established? Use your historical data to model future performance.

If your company is fairly new and you don’t have historical data yet, look at the industry averages to set benchmarks.

Before you begin to think about how to forecast sales, here’s what you need to do, step by step:

2. Document your sales process

Without a  clearly documented sales process  describing the actions and steps it takes to close a deal, you’ll have difficulty predicting whether any single deal will close.

3. Set your quotas

While your forecast may be different from your goals, you won’t know if your forecast is good or bad unless you first have a target.

Make sure each rep has an individual quota, as does the entire sales team. Read more about setting sales goals or quotas here.

4. Set a benchmark or a current average of some basic sales metrics

Having easily accessible measures of the following basic sales metrics will make forecasting much easier:

• The time it takes the customer to express interest
• How long it takes to close a deal
• The average price of a deal
• The duration of the customer on-boarding process
• Average renewal or rates, or how frequently you get repeat business
• Conversion rates at each stage of the sales process

Essentially, you want to define the average duration and performance of your sales process.

5. Understand your current sales pipeline

Make sure you understand  what’s in your current pipeline , and that your CRM is accurate and up-to-date. If you don’t have a CRM, forecasting is more difficult, but not impossible.

There are several  methods you can use to forecast sales . Many businesses use two or more sales forecasting techniques together, to create a range of forecasts. That way, they have a best-case scenario and a worst-case scenario.

Common sales forecasting methods include:

1. Sales reps’ opinions

Many sales managers simply ask their reps: “When will this deal close, and how much will it close for?”

I… don’t think you have to try very hard to guess that this isn’t a great method.

While this is technically a method you could use to create a sales forecast, your accuracy is going to plummet for two reasons:

• Sales reps tend to overestimate sales forecasts
• This method doesn’t offer a repeatable process, so there’s no way to generate a consistent forecast

Unfortunately, many companies rely on this to estimate future sales. Don’t be one of these companies! Read on for better ideas.

2. Historical data

When you use historical data, you review past performance under similar conditions to estimate how you’ll perform today.

For example, you may know that your business typically grows at 15% year over year. You also know you closed $100k of new business this month last year. That would lead you to forecast $115,000 of revenue this month.

This method is slightly more accurate but ignores other factors that may have changed in the last year, like the number of sales reps you have, or how your competitors are doing.

3. Deal stages

In this forecasting method, you assign a probability of closing a deal to each stage in your sales process. Then, at any given time, you can multiply that probability by the size of an opportunity to generate an estimate of the revenue you can expect.

This forecasting method is better still and is very popular because of its simplicity. However, it does have a weakness: it ignores the age of the opportunity. If two opportunities have booked a sales demo, but one is three weeks old and the other is three months old, are they really equally likely to close?

4. Sales cycle forecasting

As a result, an alternate forecasting method is to use the age of the sales opportunity, rather than the probability, to assess the strength of the pipeline.

It compares how long a deal has been in the pipeline, compared to the normal length of time it takes to close a deal. If you have different products, and different sales cycles depending on whether you’ve had a referral or you’re following up a lead from prospecting, then you’ll need to separate those out to get a prediction for how likely a deal is to come off.

This method needs accurate data. Everything needs to be logged correctly in the CRM so you can see the kind of lead it is, and how long it’s been in the system. If you don’t have a CRM that records all of that quickly and easily, it can require your reps to enter a lot of data.

5. Pipeline forecasting

This method is much more accurate but still more reliant on a high quality of data. It looks at each opportunity sitting in your pipeline and analyses it based on a number of factors, which could include age, deal type and deal stage.

This is a relatively sophisticated method which means it’s unlikely to work without custom tools which are capable of analysing what’s in your pipeline.

6. A custom forecast model with lead scoring and multiple variables

It comes as no surprise: This is the clear winner.

This forecasting method relies on a combination of all of the above. It has some similarities to the pipeline forecasting method, but it has greater depth and complexity. Usually, you’d need an analytics tool or advanced CRM reports set up to help create these forecasts. You also need extremely good data in the first place, so you’re relying on your reps to enter a lot of accurate information.

If you have those resources, this method of sales forecasting can be most accurate. Also, you can take into account the age of an opportunity, its current stage in the sales process, the characteristics of the prospect that make them more likely to purchase, and more.

Bonus: Forecasting methods: 7 different approaches to predicting revenue

Here are some basic examples demonstrating how sales forecasting is done in the real world.

Example 1: Forecasting based on historical sales data

Let’s say that last month, you had $150,000 of monthly recurring revenue and that for the last 12 months, sales revenue has grown 12% each month. Over the same period, your monthly churn has been about 1% each month.

Your forecasted revenue for next month would be $166,500.

You multiply last month’s revenue by your expected growth, and subtract your expected churn:

($150,000 * 1.12) – ($150,000 * .01) = $166,500

Example 2: Forecasting based on your current funnel

Let’s say you have three open opportunities this month:

• One where you’ve just had a quick phone call, with an expected value of $1,000.
• One that has received a full demo, with an expected value of $1,500.
• And one with an offer, with an expected value of $1,200.

You’ve done your math, and you know that in each of these stages, any given opportunity has the following likelihood of closing:

• “Connect Call” = 30% chance of closing
• “Demo” = 40% chance of closing
• “Offer” = 70% chance of closing

You multiply that probability with the forecasted value of the deal, and sum them all up to come up with a total sales forecast of $1,740, like in this example:

Example 3: Forecasting based on lead scores and multiple variables

You’ve really done your research, and have lead scoring set up in your CRM. You group your leads into three groups of varying quality: A, B, and C. These determine how likely an opportunity is to close.

You also know that companies with less than 50 employees close at a slightly lower rate, and companies larger than 50 employees are more likely to close.

You could then use average opportunity sizes to calculate the forecasted value of any given opportunity, using a table like this:

Bonus: 3 proven sales forecasting methods for greater accuracy

Sales forecasting tools and tech

Looking for specific tech tools to consider? Check out our top 12 sales forecasting tools list .

CRM : CRM software combines the storage and retrieval power of a database with dedicated sales tools that help reps close deals. These features may include lead tracking, funnel analytics, call sequences, and reporting features. You’ll need to choose a CRM based on the size and nature of your business. There’s a lot you can do  to make the most of your CRM .

Excel or Google Sheets : If your company is just starting out or only has a few products, spreadsheet software like Excel should suffice for building your sales forecast. For a cheap tool, it’s flexible, conditional, and you can build great charts. But it’s also time-consuming and easy to make errors in, so it may not work for a larger operation.

Sales analytics platforms :  Sales analytics tools  combine data for many products and services, build forecasts, and give you deep analytics. Plus, many also have helpful graphs and charts built in.

Dedicated analytics tools also have the advantage of staying updated in real time. They can give clearer insight into sales pipelines, products, and staff performance. And they can give more information about any gaps in the process. They can help with everything from spotting opportunities for growth to working out which team members to assign to which clients.

Lead scoring tools :  Lead scoring tools  help you work out which prospects are worth targeting for sales, and what priority to give them. They allow you to grade prospects according to actions on your website, outcomes of conversations, and any other touches that your team deems pertinent to the sales process.

Also, a lead scoring tool can help your marketing team with campaign segmentation, by helping you identify who’s ready and willing to buy, and who needs more work, as well as the level and reason for engagement. And it can help with content personalization by helping you identify the prospect’s current level of interest in your business, and the areas that the prospect has already shown interest in.

Project management tools with resource allocation : Follow-through is the most important part of your sales cycle, and is the only way to build strong customer relationships.

Project management tools  help your team stay on task and ensure that the team has the resources to complete the project. Project management tools allow you to cut out much of the manual work of tracking what’s been done and when. They can also allow better integration with other teams, who may well be using the same tools.

Accounting Software : If all you want is a new revenue forecast, more basic tools are fine. But the value of a sale depends not just on the size of the deal, but the costs it creates elsewhere in the business.

To make really accurate sales forecasts, you need to understand the run-on impact. If you want to forecast gross margins and account for the cost of goods sold, you may need to include data from  your accounting software  in your forecasting exercise.

Sales forecasting: Key takeaways

• Sales forecasting is an educated guess about future sales revenue that uses historical data and common sense to project monthly, quarterly, and yearly sales totals for a business.
• Your team should view the sales forecast as a plan to work from, not a firm prediction.
• Before you try to build a forecast, estimate the length of your average sales cycle and conversion rate.
• There are several different types of forecasts you can build. Test various methods for accuracy within your business.

Karri Bishop

More like this....

• GTM 89: Bundling the GTM Stack, Secrets of Winning Investors & Landing Key Hires with Daniel Ruiz
• 10 Best Sales Prospecting Tools for B2B Sales Leaders

4 Common Mistakes SaaS Companies Make While Scaling Revenue

Join us today, insider access to the gtm network and the best minds in tech., you may also like....

Want insider access? Sign up here.

Experience, strategy, and insights to help take you from 0 to IPO.

• Customer Success

Watch This Live Event

• Customer Experience
• Follow us on X (formerly known as Twitter)
• Follow us on Linkedin
• Subscribe to our RSS feed
• Listen to our podcasts

What is sales forecasting: Definition, methods, best practices

• Share on X (formerly known as Twitter)
• Share on Facebook
• Share on Linkedin

Listen to article

Sales forecasting is one of the most important things a company does. It fuels sales planning and is used throughout an enterprise for staffing and budgeting. Despite its importance, many organizations use outmoded practices that produce bad forecasts.

A comparison could be drawn with times past, when farmers depended on signals like cats washing behind their ears or the ache in an old-timer’s knee to forecast the weather. With the advent of  supercomputers, weather prediction has vastly improved. But in large enterprises, the tools used to foresee sales remain only somewhat more reliable than an arthritic knee.

Just how dubious are sales forecasts? A full 55% of sales leaders, and 57% of quota-carrying sellers lack confidence in forecast accuracy, according to Gartner.

While you might think this state of affairs will improve over time, Gartner estimates that even by 2025, “90% of B2B enterprise sales organizations will continue to rely on intuition instead of advanced data analytics or their B2B CRM , resulting in inaccurate forecasts, sales pipelines and quota attainment.”

What is sales forecasting?

Sales forecasting is the process of estimating a company’s sales revenue for a specific time period – commonly a month, quarter, or year. A sales forecast is prediction of how much a company will sell in the future.

Producing an accurate sales forecast is vital to business success. Hiring, payroll, compensation, inventory management, and marketing all depend on it. Public companies can quickly lose credibility if they miss a forecast.

Forecasting goes hand-in-hand with sales pipeline management. Getting an accurate picture of qualification, engagement, and velocity for each deal helps sales reps and managers provide data for a reliable sales forecast.

A forecast is different than sales targets, which are the sales an enterprise hopes to achieve. A sales forecast uses a variety of data points to provide an accurate prediction of future sales performance.

Why is sales forecasting important for business?

Sales forecasting isn’t just about predicting numbers; it’s foundational to any business strategy. here’s why:.

• Strategic decision making: Sales forecasts provide a clear picture of where a business is headed, which factors into making decisions about product launches, market expansions, or even potential mergers and acquisitions. Understanding these forward looking projections can help businesses make informed decisions that align with their long-term goals.
• Resource allocation: A close-to-accurate sales forecast ensures that resources – whether it’s labor, capital, or technology – are allocated efficiently. Proper allocation prevents over-spending in areas that might not yield returns, and ensures that high-potential areas receive attention and investment.
• Budgeting and goal setting: Accurate and reliable sales forecast data is foundational to estimating future revenue and costs, as well as setting realistic yet challenging goals for revenue teams. Such data-driven insights help businesses allocate resources efficiently, ensuring that teams are equipped to meet their targets while also safeguarding a company’s financial health.
• Proactive problem solving: One of the most significant roles for sales forecasting is the ability to spot potential issues before they become major problems. For example, if a sales team is trending below its quota, sales managers can take timely action, preventing minor setbacks from escalating into significant ones.

Essentially, sales forecasting is like a compass that guides a business through unpredictable markets. It offers foresight and paves the way for sustained growth. It may be a critical differentiator between businesses that stay ahead of the curve and those that fall behind.

More options. More conditions. More stakeholders. More circling-back. Modern selling is anything but simple. Intelligent sales enablement starts HERE .

Three main sales forecasting methods and techniques .

Although different organizations can have vastly different sales structures and processes, the majority tend to use one or a combination of the following three primary approaches to sales forecasting:

• Use of historical data to forecast future results. Looking at historical data is perhaps the most common as well as most straightforward approach. The data is readily available, and it makes sense that variations based on factors like seasonality and new product introductions would provide directional insight. The limitation, of course, is that external, macro trends that impact sales aren’t necessarily considered – at least not in a systematic fashion.
• Funnel-based forecasting. For many companies, the current state of the sales funnel is viewed as the most accurate predictor of likely sales outcomes. As long as sellers are providing accurate and frequently updated information about the state of given pursuits, use of the funnel can be a reasonably reliable means upon which to make forecasts.
• Forecasting based on multiple variables. Given that both of the above approaches have inherent limitations, some organizations are looking to build more complex forecasting models that incorporate techniques such as intelligent lead scoring alongside macro factors that are likely to impact the closing of deals. The trick is to put in place an approach that’s sophisticated enough to be meaningful without being too complex to manage and maintain.

Beyond these three foundational methods, there are other techniques often used for sales forecasting, including:

• Regression-based analysis: Statistical analysis — specifically a regression-based method — can help analyze the relationships between different micro and macro variables to predict sales outcomes. For instance, it might analyze how a change in advertising spend correlates with sales figures, offering businesses a clearer understanding of market dynamics.
• Quantifying lead potential for revenue projection: This method analyzes various value attributes such as past interactions, purchase history, and engagement metrics, to assign a value to each lead. This approach can help prioritize efforts by helping businesses focus on the most promising leads.
• Forecasting based on the length of the sales cycle: With this technique, an enterprise takes into account the typical duration of a sales cycle in predicting future sales. By understanding how long it generally takes to convert a lead into a sale, businesses can better anticipate their revenue streams, making for more accurate forecasting.
• Combining data with seasoned intuition: This approach combines hard data with the seasoned intuition of veteran sales professionals. By leveraging the experience and insights of a sales team, businesses can make predictions that account for subtleties that might not be immediately evident in the numbers.

Many businesses combine forecasting techniques to navigate market fluctuations, while other businesses might rely on a single forecasting method that they’ve found works reliably well for their individual environment. The choice often hinges on the unique challenges and nuances of each enterprise.

Knocked out by too much data? Sales forecasting AI + CRM pump up wins

Common sales forecasting mistakes.

Unfortunately, enterprises continue to make the same mistakes in their forecasting processes. Here are some of the common pitfalls:

• Sales data fails to provide insight into deal status. A limitation of existing forecast approaches is they are heavily reliant on sellers to provide accurate information about the status of specific opportunities. Given the pressure on sellers, it’s not surprising that the information they provide is often rosier than the reality.
• Time-consuming manual processes cut into valuable selling time. It’s estimated that sales reps spend 2.5 hours per week on forecasting, while their managers spend an average of 1.5 hours. Every hour that’s devoted to these time-consuming – and manual – activities would be better spent on actual sales.
• In the push to commit revenue, accuracy is often sacrificed . Under pressure to provide positive numbers, sellers typically overestimate the number of deals that will close. Perhaps not surprisingly, 79% of sales organizations report typically missing their forecasts by more than 10%. Meanwhile, 54% of the deals forecast by reps never close.

Sales audit process: 5 sales audit steps to better forecast & plan spend

Back to basics.

At the most fundamental level, improving sales forecasting means using data to more accurately  predict performance and manage planning to ensure sales success. This includes steps like:

• Common agreement about the sales process. Seems like a no-brainer, right? Your sales teams operate from a common lexicon about the sales funnel and the stages within it that your organization employs. In reality, there’s frequently a genuine disconnect.
• Set realistic sales goals or quotas and communicate them . Again, this may seem obvious. But many companies either set unrealistic sales quotas, or fail to effectively communicate individual goals and how they ladder up to the broader plan.
• Benchmark your basic sales metrics. Forecasting involves using historical data to effectively estimate future results. Benchmarking ensures that there’s a sound basis for comparison with prior results.
• Understand your current sales pipeline. If you want to achieve better forecasting, accuracy starts now. New technologies provide sales teams with intelligence that enables them to scrub leads that aren’t actually viable, realistically assess those that are, rescue ones at risk, and commit to a higher degree of precision going forward.

One commonality across these points is that they illustrate the need for cultural change in the sales organization. In other words, you can only drive accuracy in forecasting if salespeople don’t feel pressure to inflate the forecast.

And, by extension, they need to feel comfortable sharing information about deals even when it’s not favorable.

Data integration: Key for accuracy

Given all the benefits of accurate sales forecasting, what’s keeping companies from pursuing more modern approaches?

For one thing, regardless of approach, the quality of forecasts is inextricably linked to the quality of the data on which they are based. And it’s not enough to merely have all the data available; it needs to be integrated in such a way that it can be readily analyzed in real time.

Unfortunately, this type of data integration is anything but common. According to APQC’s Planning and Management Accounting Benchmark , only 14% of organizations currently house operational and finance data in a single integrated system. This means that for most companies, forecasting requires the gathering of data across organizational silos and disparate systems, which becomes time consuming and costly.

The good news, however, is that data integration enables organizations to take better advantage of technologies such as AI and machine learning that are ideally suited for spotting the types of trends that data can reveal.

By incorporating state-of-the-art tools into an integrated approach for data analysis, organizations can transform sales forecasting into a strategic advantage.

Always. Be. Closing. Learn what it takes. Get the Aberdeen B2B sales report   HERE .

Share this article

Featured Sections

The future of industries, die zukunft von cx (deutsch), el futuro de la experiencia del cliente (latam), o futuro da experiência do cliente (brasil), the future of e-commerce, future of supply chain, customer data & privacy, sustainability in business, hr + employee experience, search by topic beginning with, subscribe to our newsletter for the most up-to-date e-commerce insights..

Commerce trends and insights presented by SAP Customer Experience

Thanks for contacting us! We will get in touch with you shortly.

• Online Degree Explore Bachelor’s & Master’s degrees
• MasterTrack™ Earn credit towards a Master’s degree
• University Certificates Advance your career with graduate-level learning
• Top Courses
• Join for Free

Sales Forecasting: A Guide to Grow Your Business

Discover sales forecasting methods and how calculating a sales forecast can benefit your business.

What is sales forecasting? 

Sales forecasting is the process of estimating the revenue a company will make during a specific time period, such as a month, a quarter, or a year, usually based on past sales data. Sales forecasting can include predictions of a sales team’s performance in terms of the number of sales the team will make and how a market will respond to go-to-market efforts. 

Sales forecasting is important at all levels of business operations and can help an organization make informed decisions. Sales managers can use representatives’ forecasts to estimate the number of deals that will close. Department directors can use forecasts to predict team performance. Company leaders can share forecasts with board members, stockholders, and stakeholders to inform them of the company’s health. 

Benefits and challenges of sales forecasting

Whether you’re a business owner, a sales leader or representative, a product leader, or a company leader, bringing sales forecasting into your workflow can benefit your business in several ways, including boosting sales and revenue. In addition, you may be able to: 

Gain insight into customer behavior. 

Understand your organization’s health in numbers. 

Plan business moves more strategically.

Get better financing from lenders and investors. 

Predict how much inventory or supply is necessary for an upcoming sales cycle. 

Along with knowing the benefits of sales forecasting, it’s a good idea to be aware of the challenges associated with this business process. That way, you can anticipate challenges or take corrective action if problems arise. 

One challenge you might encounter within an organization is convincing stakeholders or decision makers to make decisions based on sales forecasts. According to a 2019 Gartner survey, only 45 percent of respondents reported that leaders at their organizations showed confidence in the accuracy of forecasts [ 1 ].  

Other challenges include: 

Changes to your sales team, such as when people leave or new hires join, necessitating a period of adjustment 

New competitors entering the market, necessitating new sales or marketing tactics

Updating your current products or introducing new ones, necessitating new go-to-market strategies

Sales forecasting methods

There are different sales forecasting methods you can use to bring more awareness to your company’s sales potential. Explore each of them to find out which ones might work best for your sales goals. 

Opportunity stage forecasting

Accounts for where a deal is in the sales process at any given time 

Assumes that the further along a deal is, the likelier it will be to close.  

Works best when you are not in the process of changing your messaging, products, or sales tactics 

Length of sales cycle forecasting method

Accounts for how long sales cycles typically last for different types of prospects. For example, a sales cycle for a referral prospect may be shorter than a prospect who just subscribed to your newsletter. 

Uses the time a prospect has been in a sales cycle and the type of prospect to determine the likelihood the deal will close 

Works best when you can categorize the different types of prospects your business interacts with and know the typical cycle length for each type 

Intuitive forecasting method

Accounts for the opinions of sales representatives who have the most direct interaction with prospects. 

Assumes that because of sales reps’ close relationship with prospects, they can intuit how likely a deal is to close. 

Works best during later phases of the sales process, when sales reps have gathered more information about prospects’ questions, challenges, hesitations, and needs. 

Historical forecasting method 

Accounts for sales performance from a period of time in the past.

Assumes that sales in a future period will resemble those of a past period.

Works best when markets and buyer demand are steady. 

Multivariate analysis forecasting method

Combines other methods, such as sales rep performance, opportunity stage, and historical forecasting 

Requires that you update data regularly, in terms of tracking deal activity. 

Works best when you use sales forecasting software

Pipeline forecasting method

Considers details of each deal, including the opportunity value, the sales rep’s closing rate, and any fluctuations in the sales pipeline

Relies on accurate, timely data 

Works best when you use sales forecasting software. 

Use these simple formulas, alongside the methods above, to quantify sales forecasts: 

Average monthly sales  = total sales revenue / number of months

Possible sales for the rest of the year = average monthly sales x months left in the year

Annual sales forecast  = total sales revenue + possible sales for the rest of the year

How to forecast sales for your business 

Use the following process to begin or improve a sales forecasting process. 

1. Establish a sales process for your team. 

When everyone on your team uses the same process, it’s easier to predict the likelihood that opportunities will close and pinpoint troublespots in the sales pipeline. The sales process should tell team members what actions to take at each stage of the buyer’s journey, from prospecting to closing. 

2. Set team goals.

Having goals for the whole team and for each member will provide a basis for measuring success and predicting the likelihood of success. What do you want to achieve in sales every month, quarter, and year? 

3. Select sales forecasting software.

Invest in software that will measure different factors and help you track sales activity to create the most accurate and useful sales forecasts. Here are some software programs to investigate: 

Hubspot Forecasting Software

Salesforce Sales Cloud  

4. Select a forecasting method.

Once you have a sales process, goals, and software, your next step is to settle on a forecasting method that corresponds to how established your business or team is.

For example, if your business or sales team is new and you have minimal sales history, you might use the intuitive sales forecasting method while still recording and tracking sales activity in your software. In contrast, established businesses with forecasting software, a full sales team, and historical data would do well to use the multivariate or pipeline forecasting methods. 

5. Review prior sales forecasts. 

To set your team up for accurate sales forecasting, look over any sales forecasts from prior sales periods. Where did actual sales match forecasts? Where did discrepancies occur? What factors contributed to either, including sales team performance, use of forecasting software and methods, or seasonal fluctuations in sales? 

6. Request data from other teams. 

It’s a good idea to gather information from marketing, product, and finance teams to inform your sales forecast. 

What insights can marketers offer on prospects’ needs, as well as what inspires them to make a purchase? 

What new product developments or offerings might affect sales volume in an upcoming sales period? 

How does the financial health of the company align with sales goals? 

7. Create forecasts and discuss them with your team. 

Using all the information you’ve gathered in steps one through six, as well as data from your forecasting software, create your sales forecasts. Then, discuss sales quotas and strategies with sales reps. Communicate important learnings to your employer’s decision makers. For example, it might be necessary to return to step one and adjust sales processes to account for an expected fluctuation in sales. 

To see a glimpse of what sales forecasting looks like inside forecasting software, check out this video from the HubSpot Sales Representative Professional Certificate .

Build sales skills with Coursera

Taking online courses can be a great way to build sales skills, including forecasting, and explore career possibilities. Check out the HubSpot Sales Representative Professional Certificate .

Article sources

Gartner. “ Use Sales Analytics to Improve Pipeline Management and Forecasting , https://emtemp.gcom.cloud/ngw/globalassets/en/sales-service/documents/trends/sales-analytics-improve-pipeline-management-forecasting.pdf.” Accessed September 28, 2022.

Keep reading

Coursera staff.

Editorial Team

Coursera’s editorial team is comprised of highly experienced professional editors, writers, and fact...

This content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

Back to Sales Management

What Is Sales Forecasting: Definition, Methods and Examples

Written by: Victoria Yu

Victoria Yu is a Business Writer with expertise in Business Organization, Marketing, and Sales, holding a Bachelor’s Degree in Business Administration from the University of California, Irvine’s Paul Merage School of Business.

Edited by: Sallie Middlebrook

Sallie, holding a Ph.D. from Walden University, is an experienced writing coach and editor with a background in marketing. She has served roles in corporate communications and taught at institutions like the University of Florida.

Updated on January 30, 2024

Definition and Benefits of Sales Forecasting

Sales forecasting methods, 7 steps of the sales forecasting process, common sales forecasting challenges.

As a sales professional or business leader, your goal might simply be to sell, sell, sell as much as possible. Not only is this unsustainable, but it ignores the reality of whether your business is breaking even or if competitors are outperforming you.

Instead of selling blindly, business leaders use sales forecasting to make smart business decisions, coordinate operations, and accurately judge their sales performance. If you’re new to sales forecasting, this guide will walk you through the definition, methods, steps, and challenges of sales forecasting with examples.

Key Takeaways

Sales forecasting predicts how many sales and how much revenue a company will generate in a given sales period.

Accurate sales forecasting is important to help a business allocate resources, plan financials, persuade investors, and optimize prospecting.

There are two main types of sales forecasting: bottom-up and top-down. Within top-down forecasting, there are also several methods any business can use to make its predictions.

To create a sales forecast, a business should first outline its sales process and set sales goals. Then, it should generate a revenue forecast and adjust it for internal and external factors. Finally, it should distribute that forecast to all involved parties.

Four common challenges for sales forecasting are data accuracy, unpredictable disasters, seasonality, and not performing enough sales forecasts.

In essence, sales forecasting is the practice of estimating your sales team’s performance and business’s revenue in the near future. It uses historical and current sales performance data and industry trends to predict how the company might perform next week, month, quarter, year, or decade.

In particular, sales forecasting aims to quantitatively predict metrics such as:

• How many leads the business will generate
• How much revenue the business will make
• The profit or loss next period
• Level of demand for a product
• Production levels needed to meet that demand
• The number of employees needed to support the business’s operations and goals

An accurate sales forecast will serve as a guiding beacon for your business, giving decision-makers key insights into how the business’s future may pan out. With this information, a business can plan for the future and make better data-driven decisions.

 In particular, here are the four main ways the data and insights from sales forecasting can be leveraged.

1. Resource Management

With a concrete idea of how many product units you’ll sell and customers you’ll serve in the near future, your company will be able to allocate its resources to match demand.

For example, if you forecast an influx of orders near the holiday season, your company would work with suppliers, manufacturers, and distributors ahead of time to ensure there’s enough stock. To do so, your business might need to shift around cash flows, budgets, and employees to meet these requirements.

Alternatively, if your forecast doesn’t meet your business’s required break-even point, you will know you need to allocate more resources to sales to increase your revenue-generating efforts.

Whether good or bad, knowing your expected activity and volume ahead of time will allow your business to set itself up for future success, overcoming roadblocks and positioning operations and resources to capitalize on new opportunities.

2. Financial Planning

If your business has separate sales and finance departments, a sales forecast report is a fundamental piece of information your decision-makers and financiers need to know how much cash flow your business can expect.

Your business’s cash flow predictions are used as the basis for financing operations such as budgeting, debt repayments, loan negotiations, and investments, so it’s crucial that your sales department uses an accurate forecast.

With a sales forecast to predict revenue, your finance team can plan on how to use capital most effectively, while predicting, as accurately as possible, the profits your business will make.

3. Communicate With Investors

If you’re the business owner, a clear and accurate sales forecast is one of the first things investors will ask of you when you seek funding. 

These investors want to know if your business can turn a profit, after all, and a sales forecast proves revenue, demand, and long-term survivability – all things that make for a good investment. Plus, confidently delivering an accurate forecast demonstrates your ability as a business owner to make rational data-driven insights and observations.

4. Optimize Prospecting

By using your sales forecast as a selling goal, your sales team will intrinsically understand how much time they can spend per prospect in order to meet the forecast’s revenue target.

Say, for example, that your sales forecast shows a 10% increase in sales from the previous month. This would tell your sales reps that they need to be at least 10% more efficient when qualifying and nurturing sales leads to meet this goal. 

As such, a sales forecast could signal to your sales reps to reduce the time spent on poorly-qualified leads, and instead focus their prospecting efforts on highly-qualified leads who are more likely to make a purchase.

Now that you know how important sales forecasting is, how exactly can you make your own predictions? 

Just as sales is influenced by a multitude of factors, sales forecasting can also be done in a variety of different ways. In general, there are two main types of sales forecasting methods, bottom-up and top-down. Let’s take a close look at each of these methods.

1. Bottom-Up Sales Forecasting

A bottom-up forecast approach asks each salesperson to assess their own performance and make individual predictions on how many sales they’ll close in the next period. These individual forecasts are then added together to make a department-wide forecast.

While this may be suitable for small businesses with only a few reps, as companies grow, the margin of error will only compound with every new sales rep whose prediction is included. As such, larger companies tend to prefer top-down, the second type of sales forecasting.

Bottom-up sales forecasting can also be called “intuitive forecasting,” as it relies on each salesperson’s intuition and judgment to create a total sales amount.

2. Top-Down Sales Forecasting

In general, top-down forecasting starts at the top by considering high-level data trends first, then works its way down to predicting revenue. Using these revenue predictions, sales managers then set quotas for their sales reps.

If you’ve noticed, “high-level data trends” is quite a vague description. That’s because there are several different top-down forecasting methods depending on the type of data forecasters want or need to use to make their predictions. 

Here are four of the most common top-down sales forecasting methods, along with examples of each one. 

Length of Cycle Sales Forecasting

Length of cycle sales forecasting uses your historical average sales cycle length to determine how many leads in your sales funnel will result in a closed sale. 

For example, if your average sales cycle length for closed sales was 30 days, you would say that a lead that has been in your funnel for 15 days has a 50% chance of closing.

Historical Forecasting

If business has been steady, you can use historical forecasting to take exact past revenue data and adjust it for any minor growth or loss you might expect.

For example, if your sales department made $20,000 in sales in March, you could expect to make another $20,000 in April, or $21,000 if you expect a 5% growth.

Opportunity Stage Forecasting

In opportunity stage forecasting, you multiply the number of leads in each stage of the sales pipeline by the probability of closing at each stage and expected deal amount.

For example, your predictions of closing at each pipeline stage might be:

• Prospecting: 15%
• Lead qualification: 30%
• Meeting Scheduling: 40%
• Proposal: 75%
• Negotiation: 80%
• Closing: 100%

Thus, if you had 10 leads in each stage with a deal size of $100 each, your revenue forecast would look like this:

In total, your forecasted revenue would be $3,400.

3. Multivariable Forecasting

Finally, multivariable forecasting uses advanced multivariable analysis to determine the chances of closing for each individual lead in the sales pipeline, and then summing those revenue chances together. It considers several detailed individual factors such as each lead’s opportunity stage, time spent in the funnel, lead type, and expected close date to forecast future revenue.

As this requires extensive historical data and statistical analysis to calculate, it’s best to leave this type of forecasting to designated sales analysis tools, such as a CRM system.

Now that you know what your options are, all that’s left is to make your sales forecast. To that end, here’s a handy sales forecasting guide that walks you through all seven steps of the process.

1. Standardize Your Sales Process

Before you can make any estimates, you’ll need to have a solid, repeatable, and standardized sales process. After all, if each sale is completed using a different or non-standardized sales process, you can’t make any sort of predictions based on previous sales.

This means you will need to clearly define your sales pipeline stages, describing the step-by-step process each lead takes to become a customer. Plus, your sales team should have a shared definition of what differentiates a sales lead, a prospect, and an opportunity – terms that distinguish potential customers using their qualifications and sales potential.

It would also be intensely helpful to have measurements of key performance indicators (KPIs) for metrics such as your sales team’s:

• Average time to close
• Average deal size
• Average number of leads
• Conversion rates

2. Set Sales Targets

A sales prediction isn’t worth much if it’s not held in comparison to your company’s overarching strategic goals.

Before you get to forecasting, identify your company’s revenue break-even point or goals, and calculate how many sales it would take to meet those targets. You may also choose to further break these down into target quotas for your individual sales reps.

By comparing your forecast to these goals, your sales team will then know if they’re on track to meeting their quotas and targets, or if they’ll have to put in extra effort this sales period.

3. Select a Forecasting Method

Now we’re ready to begin forecasting. From the list of forecasting methods, choose whether a bottom-up or top-down strategy would suit your business better. 

As we mentioned earlier, a bottom-up strategy is more suitable to small sales teams with reliably performing sales reps. If you run a larger business with more variable performance, a top-down method would be more suitable.

If you choose a top-down approach, be sure that you have accurate data from which to make your predictions. A CRM system or other sales data recording system will be a great help in collecting this information.

4. Analyze Your Current Sales Pipeline

Using the forecasting method you chose in the previous step, calculate how many sales you expect to make and how much revenue your sales team will bring in the next period.

For a bottom-up forecast, this means asking your sales reps for a concrete sales number and expected revenue based on how many leads they’re nurturing at the time, and how many they expect to have as prospects in the future.

For a top-down approach, this could mean analyzing a myriad of factors such as your current sales funnel stages, conversion rates, sales velocity, historical sales data, customer lifetime value, and more. Again, this will depend on the methodology you used to calculate top-down forecasting.

By the end, after analyzing your current sales pipeline, you should have a raw estimate for your future revenue.

5. Adjust For Internal Factors

A sales department doesn’t operate in isolation; the activities of all of your other company functions could affect or be affected by your sales team. As such, it’s important to stay in contact with the other departments, and to adjust your sales forecast in accordance with their activities.

To provide examples, the following bullet points represent ways your other company teams and functions could affect sales figures:

• Marketing could plan a new campaign that brings an influx of leads
• HR could plan to hire or let go of sales representatives
• R&D could plan updates that increase interest in the product
• Distribution could plan a new logistics route that increases supply
• The CEO could set a vision for the company’s growth or downsizing

Any of your company’s other operations could drastically change your predicted sales amounts, so it’s important to consult other managers and leaders to understand the extent to which their plans might affect your sales forecast.

6. Adjust for External Factors

Similarly, your company is affected by your industry and the actions of your competitors in the market. For example, if your competitor puts out a brand-new product similar to yours, it could greatly dampen your own sales figures.

As such, carefully research your business environment to determine any upcoming trends in your industry, market, target audience, and competitors. You should also look at broader social, economic, and political trends. 

With these upcoming environmental changes in mind, adjust your sales forecast accordingly.

7. Share With Team Members

Now that you’ve adjusted your revenue projection for both internal and external factors, all that’s left is to distribute your forecast to all relevant parties.

For decision-makers, financiers, and investors, your adjusted revenue projection will be sufficient enough. However, for your own sales team, you should go the extra mile to translate that revenue projection into a discrete number of sales that you expect them to make, and set your team’s sales quota.

With an accurate sales forecast, your sales team and your company will feel confident in planning for the future and working hard to make the forecast a reality.

Of course, with any sort of prediction, there’s always room for inaccuracies. Here are some common challenges businesses face when sales forecasting, and tips on how you can overcome them.

1. Data Accuracy

The largest issue with forecasting is that if the company’s historic sales data isn’t accurate, the forecast will inevitably be inaccurate. 

Utilizing a Customer Relationship Management (CRM) system for sales forecasting isn’t a sure fix for data accuracy. According to Gartner , only four out of ten (41%) sales managers and executives were satisfied with their CRM dashboard’s ability to help them forecast sales and make business decisions. 

To help improve data accuracy, it’s best to collect data at more frequent intervals, and to encourage your sales reps to stay vigilant and honest when it comes to recording their own sales metrics.

2. Unpredictable Disasters

Even the most failproof of sales forecasting methods could never have predicted the travesty that Covid-19 wrought on all businesses. In a similar vein, your own sales forecast will inevitably fail to reflect unpredictable disasters, such as socio-economic crises or extreme weather events.

Though there isn’t a way to predict these with full accuracy, your business can be prepared by carefully paying attention to the world around us, and keeping some cash on hand to cushion unexpected blows.

3. Seasonality

Depending on your industry and product, your business might perform exceptionally well in some seasons or locations as opposed to others. If your forecast fails to account for these variables, it will produce a revenue prediction that’s out of season.

Businesses with seasonal trends can overcome this by being meticulous in only using corresponding historical data to calculate the forecast for the upcoming season. For example, your company might only base its winter sales on the company’s performance the previous winter, rather than using summer data. 

4. Not Enough Forecasts

The final mistake companies make when forecasting sales is not creating enough forecasts. Not conducting enough sales forecasts (such as one after each business quarter) could leave your sales team with a rose-tinted view of the future, rather than providing an updated understanding of what could be a more accurate view of your business’s future.

As a science experiment becomes more trustworthy with more trials, you should improve the accuracy of your sales forecast by using several different methods to estimate future sales. By making predictions, often and from many different angles, you can rest assured that your sales forecast is as accurate as possible.

Some software tools that can help you with sales forecasting are advanced CRMs such as the ones sold by Salesforce , Microsoft Dynamics 365 , or Pipedrive . 

As opposed to more entry-level CRMs, these tend to have complex analytic and predictive capabilities that can measure accurate sales KPIs and make sales forecasts.

To create more accurate forecasts, your business should try to improve the accuracy of its data. To that end, a CRM or other sales management software tool would be a big help in encouraging sales reps to continuously update their lead data.

Additionally, you can improve your forecasting process as a whole by reviewing previous forecasts and comparing them to the real performance for that period. By viewing the forecast in hindsight, you may be able to identify factors that you failed to account for last time that you can now consider in your next prediction.

To make accurate forecasts, it’s best to consult your business’s historical data and current pipeline status, as well as cross-departmental and external industry trends. By taking all of these factors into account, you can create a multifaceted and accurate sales projection.

Sales forecasting isn’t just for the sales team – other decision-makers in the company such as the CEO, financial team, HR team, and marketing team will also need to know the number of forecasted sales the company can expect in order to make decisions and allocate resources.

Featured Resources

Common Sales Objections and How to Address Them

Tamara Siklosi

Published on April 10, 2024

You know the drill. You’re deep into your pitch, and just as you’re about to close the deal, the client throws a curveball.“It’s ...

How To Become A Sales Manager

Whether you’re a student looking to get into sales, a sales representative aiming high, or even a worker in a completely different industry,anyone ...

How to Sell to Gen Z

Published on March 18, 2024

One demographic that’s been making waves and reshaping the business landscape is Generation Z. Born between the mid-1990s and early 2010s,thes ...

How to calculate a sales forecast for a new business

Table of Contents

Definition of a sales forecast

The uses of a sales forecast, how to calculate sales forecast for a new business, calculate a sales forecast using the accounts of your competition , calculate a sales forecast using a target market, manage your finances with countingup.

When you’re running a business, you should always keep one eye on the future. If you don’t have a rough idea of what the next week, month, or year might bring, you’ll be at a disadvantage when making business decisions. This means that calculating a sales forecast is essential, especially when you’re just starting a business or beginning to write a business plan . 

Sales forecasting can be tough if you don’t have much business experience, but we’re here to help. This article will cover a range of different topics related to sales forecasting, including:

Creating a sales forecast is the first step in managing your company’s cash flow . Your cash flow is the movement of money in and out of your business. By forecasting your sales, you’ll be able to predict your gro s s profit and net profit , which means you can start anticipating what money you’ll have to spend on running your business for the next month. 

Put simply, a sales forecast is a prediction of how much you’re going to sell in the coming month. This forecast doesn’t need to be a guess — it’s possible to calculate a fairly accurate forecast with some thorough research. The focus of your research will differ depending on which sales forecast method you pick.

Firstly, your sales forecast is important because it helps you set sales goals . Measuring the success of your business is a vital part of deciding its future, and setting sales goals is one of the simplest ways to measure success. 

If you have an accurate sales forecast, you’ll be able to set realistic sales goals. You’ll want your goals to be realistic, as this will give the clearest picture of how well your company is doing and if significant changes are needed.

Similarly, sales forecasts can also help create an accurate budget for your business. As a sales forecast is essential for predicting the money your business will make, it also plays an important part in working out how much money you’ll have to spend. 

Finally, sales forecasts help with finding investors for your business . If you’re looking for financial support to start your business, any investor you approach will likely be interested in the amount of money you expect the business to make. If you’ve created a sales forecast, you’ll be able to provide this information.

Large, well-established businesses rely on the sales figures of previous months to calculate their sales forecasts for the future. While having previous sales figures helps create more accurate forecasts, it’s not essential. There are a couple of methods new businesses can use to calculate their sales forecasts, even if they don’t have a sales history to look back at.

It’s always a good idea to research the competition when you’re setting up a new business. This is also true when calculating a sales forecast, but it depends on the type of businesses that make up your competition.

If any of your competitors are registered with the government as limited companies , they will have to make their accounts publicly available. These accounts will contain things like their monthly expenses, total profits, and (most importantly) the money they’ve made from sales. 

Using this last figure, you can work out how much your competitors are making from sales each month, and get a reasonable estimate of your own sales. You can find these accounts by searching for your competitor’s business on Companies House .

Please note that this method isn’t effective if your competitors are sole traders , as this means they won’t need to publish their accounts publicly. In this instance, you should use the forecasting method below. 

This method is known as ‘bottom-up’ forecasting, as you start at the bottom — your potential market of customers — and then work up to a forecast — the percentage of those customers that make a purchase.

The first step of this method is identifying your target market . This is the section of the population that you think will be interested in your product. With a little market research — things like sending out surveys, or posting polls on social media — you can work out how many people are in your target market. 

Once you have the size of your target market, you need to make realistic estimates of how many people will make a purchase. For example, if 1000 people in the local area are potential customers, you should expect 10% to visit your store or website, and 1% to actually make a purchase.

This method of calculating a sales forecast is good because it’s very adaptable. If you get many more or far fewer sales than you originally calculated, then you can adjust your figures accordingly and record the new forecast. 

It’s also a good idea to categorise this sort of sales forecast. Instead of estimating your overall sales, estimate the sales of each type of product you sell. That way, you can use the forecast to work out how many of each product to make or order each month. 

Creating a sales forecast is a great start, but it’s only the first part of managing your sales revenue. Once you start making sales and money starts coming in, you’ll need to track that cash so you can work out where to spend it. If you think you might have trouble with this, try using a financial software tool like Countingup.

Countingup is the business current account with built-in accounting software that allows you to manage all your financial data in one place. With features like automatic expense categorisation, invoicing on the go, receipt capture tools, tax estimates, and cash flow insights, you can confidently keep on top of your business finances wherever you are. 

You can also share your bookkeeping with your accountant instantly without worrying about duplication errors, data lags or inaccuracies. Seamless, simple, and straightforward!  Find out more here .

• Counting Up on Facebook
• Counting Up on Twitter
• Counting Up on LinkedIn

Related Resources

What insurance does a self-employed hairdresser need.

As a self-employed hairdresser, you’re open to risks in your everyday work. Whether

What are assets and liabilities in a business?

Anyone going into business needs to be familiar with assets and liabilities. They

Personal car for business use: How does it work?

Access to a car is a must for most businesses, meaning that travel

Advantages and disadvantages of using personal savings in business

Have you got a new business idea? And are you considering using your

How to pay Corporation Tax

Corporation Tax is the main tax your limited company has to pay every

How long do CHAPS & BACS payments take?

If you are making transfers frequently between banks in the UK, you have

11 common costs of running a business

When running a business, the various costs can quickly add up. If you

How to buy a vehicle through a limited company

Buying a vehicle through a limited company works similarly to how you may

What is a sales strategy? (with example)

When you run a small business, it’s important to consider how you’ll optimise

Preparing business packages for distribution

You may think shipping your product is as easy as popping it in

How to use cloud services for a business

The development of cloud computing is a game changer for businesses big and

How do EU imports and exports work?

In January 2022, the UK introduced new EU imports and exports regulations. If

3 Popular Sales Forecast Examples For Small Businesses

• October 9, 2022
• Small Businesses

When creating financial forecasts for their business, entrepreneurs often face difficulties. Yet, there are 3 popular sales forecast examples you can use when creating yours. They work for the most popular revenue models , from restaurants, to retail shops, to software companies and other online businesses.

If you aren’t sure what are sales forecasts, read our article and follow these 5 simple steps to create accurate sales forecasts for your business. Looking for examples instead? In this article we explain what are the most popular 3 sales forecast examples for (almost) any type of business. Let’s dive in.

What is a sales forecast?

A sales forecast is the financial projection of a business’ sales (or revenues, turnover) over a given period. Therefore, sales forecasts are a must have of any financial forecast: by projecting sales and expenses we can then prepare the  4 financial statements  which constitute a financial forecast.

Often, sales forecasts are included within a business plan as part of your projected financial statements. Indeed, investors will want to see your business’ financial projections over a given period. Sales forecasts often are  3 or 5-years projections .

For more information on sales forecasts for small businesses and why they are important, read our article here .

Let’s now dive into the 3 most popular sales forecast examples which work for any type of business, from restaurants, to retail shops, to software companies and other online businesses.

Why are sales forecasts important?

Because sales forecasts are part of your financial forecasts, and ultimately your business plan, it is very important to get it right.

Sales forecasts help you set goals for your business

Sales forecasts aren’t simply a requirement for your business plan. Instead, they also help you set goals for your business. The sales you expect to generate as per your sales forecast should be used as a guidance for your budget and your business decisions later on.

You show you understand your business

Showing investors you’re not only a great entrepreneur but also a well-rounded and omniscient founder is very important to get the best deal. A great sales forecast will help understand how your business generates revenues, what are the different drivers affecting revenue and the potential risks involved.

Investors will give more credit to financial plans based on verified assumptions and reasonable targets. Calculate expected revenue using market size , market share and/or user adoption rates for instance. The more you justify your plan with verified assumptions, the more credible it will be.

You know how much you need to raise

Many entrepreneurs and founders do not really know exactly how much they need to raise.

Sales also drive expenses, so forecasting sales plays a pretty important role when assessing things such as your breakeven or the amount of money you need to raise . Miss the mark and you may be in trouble.

How much cash do you need to cover your losses over the next 12-18 months? The amount of money you need to raise is the result of your financial projections. This is very important to accurately estimate your revenues and expenses.

How to do a sales forecast?

Before we dive into the specifics of creating a rock-solid sales forecast for your small business, let’s first explain which approach you should follow.

Many entrepreneurs make the same mistake when forecasting their sales: they use a top-down approach. So what is bottom-up and top-down sales forecasting? Let’s use an example below.

• Top-down sales forecasting : we forecast sales using from the top down. For example, you make $500k in revenue per year and you forecast the next 3 years revenue by assuming you will capture 3% of your market size (assuming it is $100 million). By following this approach, your annual revenue is 3 years time is $3 million, a 6x increase from today.
• Bottom-up sales forecasting : we forecast sales using operational drivers (from the bottom up). For example, if your $500k sales are a function of your website traffic, we will forecast revenues based on this metric instead. Assuming website traffic increase by 50% each year (as you invest in paid and content), your revenue in 3 years time is $1.7 million, a 3x increase from today.

Bottom-up sales forecasting is the best approach for 2 main reasons:

• It allows us to relate revenues to another metric, helping us making sense of the projection. Does $3 million really make sense given this would mean multiplying website traffic by 6x over the next 3 years?
• Top-down approach requires us to make assumptions on the market size, which is often inaccurate for lack of publicly available data. Instead, bottom-up uses your own business’ historical data

Sales forecasts: 3 popular examples

1. location-based businesses.

If you are running a businesses with a physical location, such as a hotel, a restaurant, a repair shop or a retail store for example, forecasting sales boils down to forecasting street traffic.

Indeed, sales (revenues) are a function of the sales volume you generate (the number of “units” or products you sell). The sales volume itself is a function of the number of people who enter your store, and, by extrapolation, the number of people who pass by your store.

When forecasting sales for a new business, you should look at the location where your business will be based first. Assess the approximate number of people who are passing by.

Note: when assessing traffic, be careful to exclude any external factors (e.g. Christmas day), cyclicality and seasonality. Ideally, your assessment should look at a full week and all work hours in the day.

Once we have established the approximate number of people who pass by the street in a day, we will need to apply conversion rates, in order:

• How many people enter the store?
• Out of the people who enter the store, how many make a purchase?

Of course, if you already have some historical data (if you already run a store and are opening a new one), use your existing conversion rates. Else, make assumptions.

When making assumptions, you should use the data you have collected when making your own observations earlier. Use similar stores to yours, in a different street for example.

For example:

• 5% of people passing by your store enter
• 10% of people entering the store make a purchase

We can now create a simple sales forecast over a week, adding up the average traffic over a typical week:

2. Online businesses

Online businesses often acquire their customers via their website, or any type of online presence.

As such, unlike location-based businesses, sales (revenues) are a function of visitors (and not street traffic). The visitors can be visitors on a website, on a Appstore page (mobile apps) or any type of online lead acquisition page.

We often refer this type of acquisition as inbound acquisition . The traffic is two fold: paid and organic:

• Paid traffic : all visitors coming from paid marketing channels (Google Search, Facebook Ads, etc.). You are either paying for clicks, or impressions. 
• Organic traffic : all visitors landing on your landing page(s) organically (either via a referral link, direct search, social media post, blog article, etc.)

Paid marketing is the easiest way to generate traffic. Yet, because you are paying for each paid visitor, you will need to monitor your  Return on Ad Spend (ROAS)  to make sure your paid marketing campaigns are profitable.

In comparison, whilst you do not directly pay for each organic visitor, organic traffic is not free. Organic traffic is earned from investment into  SEO  and content. Whilst investing into your SEO for instance does not pay immediately, the returns can far outweigh those of your paid marketing in the long run.

So, when forecasting sales for online businesses, we should make assumptions on traffic. For example assuming:

• 30,000 visitors last month: 20,000 paid and 10,000 organic
• 3% monthly increase
• 2% conversion rate
• $50 average purchase price

This is how could look like a simplified sales forecast example for an online business:

3. Lead-acquisition businesses

Lead-acquisition businesses are companies that make sales through their sales teams efforts. This is also known as outbound acquisition (vs. inbound discussed above).

With outbound acquisition, a business acquires customers through its sales team. Whether it is via phone, email, Linkedin or even in-person, the number of acquired customers is a function of the number of sales people.

Outbound acquisition is very common for business-to-business (B2B) companies. For example, Enterprise SaaS and B2B marketplaces use outbound acquisition to acquire their customers.

Outbound customer acquisition is therefore easier to forecast vs. inbound. The simple formula to estimate new customers over time is:

The number of closings per sales person is also referred to as the efficiency of your sales team = the number of customer one sales person acquire (or “close”) each month, in average.

For example, lets’ assume you have 20 sales people. Historically, your sales team has closed (“acquired”) in average 2 B2B clients per month per sales person. Assuming you have the same number of sales persons and the same sales efficiency in the future, we can reasonably expect 40 new customers per month.

Now, assuming 1 new hire every 2 months, a sales forecast example for a lead-acquisition business could look like this:

Expert-built financial model templates for tech startups

Privacy Overview

October 03, 2023

The Complete Guide to Successful Sales Forecasting

Sales forecasting is one of any organization’s most critical activities, as it allows you to plan staffing requirements and capital flows for trading. Despite the importance of such calculations, many enterprises use outdated technologies that create poor commercial predictions.

How reliable are sales forecasts? According to Gartner research, 55% of commercial leaders and 57% of quota-carrying firms are unsure about their retail predictions. If a leader thinks the company’s financial situation will change soon, then according to Gartner’s calculations, even by 2025, 90% of commercial companies will rely on intuition rather than advanced analytics or customer relationship management (CRM) systems when making predictions, limiting the creation of exact forecasts. In this blog, we will talk about why forecasting is vital for the rise of an enterprise and how to make high-quality commercial plans.

What is sales forecasting?

A sales forecast is a procedure that evaluates the potential earnings a company may generate during a specific time frame. In a B2B system, this is the historical data-backed practice of calculating sales profits over time. It includes evaluating real-time commercial information, calculating business performance, and comparing predicted and actual capital inflows.

Such calculations usually rely on historical information, the current situation in the area, and external information that reflects industry tendencies and market conditions.

If you have historical insights, it will be simpler to make predictions, but even new organizations can profit from the proper estimations.

It is essential to understand there is no 100% accurate sales forecast. It is at planning instrument that allows enterprises to prepare for future dangers and opportunities.

Why is sales forecasting critical?

Precise sales forecasting is the key to the prosperity of an enterprise. It enables you to make effective decisions and notice potential threats before they destroy your organization. Consider other benefits of forming commercial plans:

• Goal setting: allows firms to set realistic objectives. An enterprise can define its goals by studying past information, current market conditions, and business potential.
• Resource allocation: commercial forecasts are critical to successful resource management. By creating commercial plans, firms may decide where and how much to invest for optimal results.
• Investor relations: a clear sales plan will show potential investors the firm understands its industry and growth opportunities. It can be a significant argument in favor of investing in an enterprise.
• Risk mitigation: identifying potential challenges in commercial predictions allow organizations to mitigate risk proactively. It may involve the creation of different product lines, the development of new markets, and changes in pricing algorithms.

What can happen if you do not utilize the forecasting process? In the worst case, you may expect cash flow challenges, the need to lay off many employees, and even bankruptcy, as the enterprise’s management spends significant amounts without understanding what awaits them in the future.

Sales forecasting techniques

Although different firms have different structures and commercial procedures, most usually use one or more approaches to commercial predicting. We will examine several popular forecasting techniques using simple estimates and more complex processes.

Historical predicting

This technique involves the study of insides from past intervals. Let’s say your firm made $15,000 in sales last month, so you can assume the same numbers will be in this period.

To create more accurate predictions, consider the change in revenue over time. Let’s assume that for the last three months, the income was:

• $13,000 in May
• $14,000 in June
• $15,000 in July.

With sales volumes increasing by $1,000 per month, this trend can be expected to continue.

Opportunity phase prediction

This forecasting technique assesses the likelihood of closing a deal depending on the funnel stage at that moment. There is a rule of thumb that deals farther down the funnel are more likely to close. You may examine your historical performance data and make predictions.

Suggest, last month, the amount of identified leads: was 240, while the sum of closed deals was 60. To comprehend how many identified leads can be closed, you need 240/60*100% = 40%. It means there is a 40% chance that leads found now will close the deal.

Prediction with multiple variables

Sales results depend on various factors, meaning errors can occur when solely relying on the simple calculations described above.

The multi-variable predicting method considers several factors, resulting in greater prediction accuracy because it involves more mathematics and less intuition. Consider the main factors you should add to the forecast:

• Percentage of deals closed by different sales representatives for a specific time interval.
• The estimated value of the transaction in dollars, considering the client’s needs.
• The number of days remaining until the end of the period.
• The stage of the sales funnel where the lead is located.

To perform calculations, we recommend using CRM software. It works with complex formulas and considers different points, which provides a more exact forecast.

Who is responsible for sales predictions?

Commercial predicting is a critical job for any enterprise. Without such plans, it is difficult to make the right decisions about inventory, recruiting, marketing, and other areas of development. Although salespeople often make predictions, other professionals can be involved in this procedure.

At the initial stage of forecasting, it is necessary to collect information from various sources, including financial documents, communication with clients, market analysis, etc. Once information is collected, it must be studied to determine tendencies. It is the responsibility of sales managers.

After analyzing insights, it is necessary to compute future demand. Sales leaders do such work. They successfully apply their industry knowledge and information to generate commercial targets for future periods.

When the trading goals are ready, you must transfer them to the sales representative for execution. They must develop commercial tactics and methodologies to ensure goals are achieved.

Commercial success depends on the accuracy of the information and the ability of the sales team to implement innovative practices. If any of these are missing, it could affect the enterprise’s profitability.

Sales forecasting tips

Making commercial forecasts means predicting an enterprise’s future sales and earnings. While procedures may vary depending on your field and job circumstances, we have developed a general framework to assist you in developing commercial predictions.

Set up commercial activity

Unless you have implemented a single sales process for your entire organization, it won’t be straightforward to compute the probability of closing deals. The fact is that the commercial process defines the standard stages of opportunity in the sales funnel.

Your commercial reps must clearly define each phase of the sales funnel. This way, your predictive information will be as exact as possible, and the commercial team will understand how to work with leads in different trading cycles.

Define commercial quotas

You won’t know if your plan is working without setting sales targets. The whole team should have a common goal, but it is also necessary to set personal goals for each salesperson.

The simplest option is to study the historical results of representatives and interact with them to calculate and adjust plans. In this way, you may create a point of reference that can be compared with the forecast to make adjustments without waiting for the period to end.

Add CRM structures

Your predictions are only as good as the data they are based on. If you rely only on evaluations and assumptions, then the future of the business remains bleak.

Regular implementation of CRM systems provides access to information in real-time. You may reallocate resources in time if you understand the sales funnel accurately.

Define forecasting technology

After implementing a single commercial procedure, quotas, and CRM, you should choose a sales forecasting technique. The choice of technology depends on the company’s age, the number of employees, the quality of information, and the habit of monitoring data.

Successful forecasting means finding the right balance: it should be detailed enough to be useful but not overly complicated to handle.

Examine past sales forecasts

If your firm has previously generated commercial predictions, you may utilize this information as a starting point. Compare actual information with past forecasts to evaluate the performance of the sales department, determine which fields need improvement, how realistic the aims set were, etc.

Check and update forecasts regularly

Market conjuncture, sales techniques, and other factors may change, negatively impacting your forecast’s quality. Regular checks will enable you to change predictions, consider new information, and maintain its accuracy.

Basic predictions errors

Sales professionals must actively engage in forecasting. In a highly competitive and volatile market environment, expectations from sellers are rising, and predictions are essential in tracking buyer activity and enterprise health. Unfortunately, many businesses make the following mistakes during forecasting:

• Refusal from studying historical data: one of the most vital things you can do when planning sales is to research information about past deals. It will create a full picture of what to expect from the area. It is also essential to be mindful of any changes that have taken place in the business if they may change shipping volumes.
• Utilize manual labor: according to research, sales representatives spend approximately 2.5 hours a week on forecasting, and their managers spend up to 1.5 hours. The implementation of automation enables you to spend this time on actual trading.
• Ignoring the seasonality of commodities: sales volumes may vary significantly in different periods. If you deal with products in demand during specific periods, this should be reflected in commercial forecasts.

Many specialists strive to provide positive dynamics, so they often overestimate the number of transactions that can be completed. Coincidentally, 79% of business firms report their predictions typically fall short of reality by more than 10%. At the same time, 54% of transactions that sales representatives expect remain unclosed.

Final thoughts

Now that you comprehend the power and importance of sales forecasting, it’s time to put this knowledge into practice. If you lack experience creating commercial predictions, we recommend you contact BooksTime for help.

Our experts are ready to know everything about commercial planning, resources, and budget. Whether you’re a startup looking to engage investors or an established enterprise looking to increase profit, BooksTime has the instruments to assist you in achieving your aims.

This article is not intended to provide tax, legal, or investment advice, and BooksTime does not provide any services in these areas. This material has been prepared for informational purposes only, and should not be relied upon for tax, legal, or investment purposes. These topics are complex and constantly changing. The information presented here may be incomplete or out of date. Be sure to consult a relevant professional. BooksTime is not responsible for your compliance or noncompliance with any laws or regulations.

Share This Article

Author: Charles Lutwidge

Talk To A Bookkeeping Expert

A bookkeeping expert will contact you during business hours to discuss your needs.

• Search Search Please fill out this field.
• Corporate Finance
• Financial Analysis

What Is Business Forecasting? Definition, Methods, and Model

What Is Business Forecasting?

Business forecasting involves making informed guesses about certain business metrics, regardless of whether they reflect the specifics of a business, such as sales growth, or predictions for the economy as a whole. Financial and operational decisions are made based on economic conditions and how the future looks, albeit uncertain.

Key Takeaways:

• Forecasting is valuable to businesses so that they can make informed business decisions.
• Financial forecasts are fundamentally informed guesses, and there are risks involved in relying on past data and methods that cannot include certain variables.
• Forecasting approaches include qualitative models and quantitative models.

Understanding Business Forecasting

Companies use forecasting to help them develop business strategies. Past data is collected and analyzed so that patterns can be found. Today, big data and artificial intelligence has transformed business forecasting methods. There are several different methods by which a business forecast is made. All the methods fall into one of two overarching approaches: qualitative and quantitative .

While there might be large variations on a practical level when it comes to business forecasting, on a conceptual level, most forecasts follow the same process:

• A problem or data point is chosen. This can be something like "will people buy a high-end coffee maker?" or "what will our sales be in March next year?"
• Theoretical variables and an ideal data set are chosen. This is where the forecaster identifies the relevant variables that need to be considered and decides how to collect the data.
• Assumption time. To cut down the time and data needed to make a forecast, the forecaster makes some explicit assumptions to simplify the process.
• A model is chosen. The forecaster picks the model that fits the dataset, selected variables, and assumptions.
• Analysis. Using the model, the data is analyzed, and a forecast is made from the analysis.
• Verification. The forecast is compared to what actually happens to identify problems, tweak some variables, or, in the rare case of an accurate forecast, pat themselves on the back.

Once the analysis has been verified, it must be condensed into an appropriate format to easily convey the results to stakeholders or decision-makers. Data visualization and presentation skills are helpful here.

Types of Business Forecasting

There are two key types of models used in business forecasting—qualitative and quantitative models.

Qualitative Models

Qualitative models have typically been successful with short-term predictions, where the scope of the forecast was limited. Qualitative forecasts can be thought of as expert-driven, in that they depend on market mavens or the market as a whole to weigh in with an informed consensus.

Qualitative models can be useful in predicting the short-term success of companies, products, and services, but they have limitations due to their reliance on opinion over measurable data. Qualitative models include:

• Market research : Polling a large number of people on a specific product or service to predict how many people will buy or use it once launched.
• Delphi method : Asking field experts for general opinions and then compiling them into a forecast.

Quantitative Models

Quantitative models discount the expert factor and try to remove the human element from the analysis. These approaches are concerned solely with data and avoid the fickleness of the people underlying the numbers. These approaches also try to predict where variables such as sales, gross domestic product , housing prices, and so on, will be in the long term, measured in months or years. Quantitative models include:

• The indicator approach : The indicator approach depends on the relationship between certain indicators, for example, GDP and the unemployment rate remaining relatively unchanged over time. By following the relationships and then following leading indicators, you can estimate the performance of the lagging indicators by using the leading indicator data.
• Econometric modeling : This is a more mathematically rigorous version of the indicator approach. Instead of assuming that relationships stay the same, econometric modeling tests the internal consistency of datasets over time and the significance or strength of the relationship between datasets. Econometric modeling is applied to create custom indicators for a more targeted approach. However, econometric models are more often used in academic fields to evaluate economic policies.
• Time series methods : Time series use past data to predict future events. The difference between the time series methodologies lies in the fine details, for example, giving more recent data more weight or discounting certain outlier points. By tracking what happened in the past, the forecaster hopes to get at least a better than average view of the future. This is one of the most common types of business forecasting because it is inexpensive and no better or worse than other methods.

Criticism of Forecasting

Forecasting can be dangerous. Forecasts become a focus for companies and governments mentally limiting their range of actions by presenting the short to long-term future as pre-determined. Moreover, forecasts can easily break down due to random elements that cannot be incorporated into a model, or they can be just plain wrong from the start.

But business forecasting is vital for businesses because it allows them to plan production, financing, and other strategies. However, there are three problems with relying on forecasts:

• The data is always going to be old. Historical data is all we have to go on, and there is no guarantee that the conditions in the past will continue in the future.
• It is impossible to factor in unique or unexpected events, or externalities . Assumptions are dangerous, such as the assumption that banks were properly screening borrowers prior to the subprime meltdown .  Black swan events have become more common as our reliance on forecasts has grown.
• Forecasts cannot integrate their own impact. By having forecasts, accurate or inaccurate, the actions of businesses are influenced by a factor that cannot be included as a variable. This is a conceptual knot. In a worst-case scenario, management becomes a slave to historical data and trends rather than worrying about what the business is doing now.

Negatives aside, business forecasting is here to stay. Appropriately used, forecasting allows businesses to plan ahead for their needs, raising their chances of staying competitive in the markets. That's one function of business forecasting that all investors can appreciate.

Kesh, Someswar and Raja, M.K. "Development of a Qualitative Reasoning Model for Financial Forecasting."  Information Management & Computer Security, vol. 13, no. 2, 2005, pp. 167-179.

Infiniti Research. " Business Forecasting: The Challenges in Knowing the Unknown ."

• Terms of Service
• Editorial Policy
• Privacy Policy
• Your Privacy Choices

• Wholesale & Distribution
• Other Industries

Intact Xline

Agile development, implementation, technical support, digital transformation, training academy.

• Careers HIRING

Graduate Programme

Partnership program, customer stories, customer hub, news & events.

Discover how our Merchant customers operate at their best with Intact iQ.

• Builders Merchants
• Plumbing & Heating Merchants
• Timber Merchants
• Tiles, Bathrooms & Kitchens
• Electrical & Lighting

Discover how our Wholesale & Distribution customers operate at their best with Intact iQ.

• Office Supplies
• Pharma & Medical Supplies
• Flooring & Timber
• Food, Beverage & Cash and Carry
• Work Wear & Safety Wear
• Janitorial & Cleaning
• Tools, Fixtrues & Equipment Supplies
• Paper & Packaging
• Giftware, Homeware, Furniture

Discover how our Retail customers operate at their best with Intact iQ.

• DIY & Agri Stores
• Central Distribution
• Furniture & Fittings
• Agri Co-operatives
• Homewares & Value Stores

Discover how businesses from a wide range of sectors operate at their best with Intact iQ Design Suite.

Our flagship product, Intact iQ, is next-generation ERP software designed for today’s digital economy.

By Industry

Intact Xline is a powerful business management software solution designed for small to medium-sized companies.

Valued additions

• Intact Cliqx - eCommerce Solution
• Intact Access - Enterprise Mobililty Solution

Intact Cliqx

Our range of online options make it easier for your customers to do business with you.

Online Options

• NEW - Online Account Management

Intact Access

Boost the productivity of your remote teams with access to the key business information and controls they need 24/7.

• Enterprise Mobility

Our agile development framework enables us to quickly develop and regularly deliver new features that provide the most business value.

Our consultants work directly with our project team to future-proof your business, facilitate your long-term goals and accelerate growth.

Our local, dedicated technical support specialists are on hand to ensure your system is always operating at its best.

Our qualified and experienced team of professionals will advise and help you on all your digital transformation needs.

We offer a range of courses to help you get the most out of your software and further deliver on your overall business objectives.

Implementing and supporting our leading ERP and business management software solutions since 1992

We are instigators. Change makers. Future thinkers. Determined to take your business to the next level.

Hear what our team of Intacters have to say about life inside Intact

If you are looking to make a significant impact, support meaningful change and help transform businesses across the globe, then come join us and ignite your career at Intact, beginning September 2022.

Provides a unique range of benefits to enable partners to differentiate themselves in the marketplace and add exceptional customer value.

Our local, expert team are on hand to answer any queries you may have. Get started and elevate your business with Intact.

Find out how our software solutions enable our customers to elevate their businesses

We’re here to partner, collaborate and innovate with you. Our mission is to ensure your perfect fit software solution continuously enables you to elevate your business.

Explore our range of ebooks, white-papers, videos and product brochures

Keep up to date with the latest Intact news and events

Our technology and industry experts keep you informed of the latest trends, expert advice and best practice applications impacting your business

How to Create a Sales Forecast Business Plan

Sales forecasting is a powerful way to improve decision-making and make smarter choices as a business. But the reality is, many organisations don’t get it right.

Accurate sales forecasts rely on astute insights driven from robust, holistic data. If your business has struggled to accurately predict future sales revenue in the past, our guide could help you get it right in the future.

Ready to get started? Use the links below to navigate or read on for our full guide to accurate sales forecasting.

Quick Links

What is a Sales Forecast?

Why is sales forecasting important, what factors can affect sales forecasting, how to create a sales forecast, tools to help with sales forecasting.

A sales forecast is an estimate of what a company will sell in a week, month, quarter or year. It’s used to predict future revenue, accounting for the number of units an individual, team or company is likely to sell over a set period.

Sales forecasting offers many benefits when leveraged as part of a broader business strategy. At all levels and across all functions within a business, forecasting can facilitate shrewd decision-making, whether that’s setting goals and budgets, prospecting for new leads, deciding on the best time to hire new staff, or effective stock management to help maximise cashflow.

Accurate sales forecasting is a projection of where a company will stand in the future. And that’s important, not only for business continuity and growth, but for cultivating credibility, trust and advocacy with key stakeholders – be it partners, investors, clients or customers.

Let’s take a look at some of the reasons why sales forecasting matters:

• Bolsters decision-making – accurate predictions about future revenue can facilitate improved decision-making across all business functions, from hiring managers tasked with recruiting new talent, to procurement teams discerning when and how much stock to source.
• Adds value to all business functions – sales forecasting defines the value brought by different departments across the business. It highlights how different functions and channels contribute to revenue generation, helping businesses manage their resources.
• Accurate sales and buying for reduced costs – a sales forecast simplifies inventory management, with accurate stock predictions reducing costs and freeing up valuable resources, like warehouse space.
• Allocation of sales and marketing budget – Forecasting helps account for peaks and troughs in sales, so you can assign marketing budgets and determine which products and services need attention.
• Guarantees timely recruitment and outsourcing to drive business growth – understanding the areas of your business that drive the most revenue can make for seamless recruitment. Reinvesting revenue in personnel is a seismic driver of business growth, and sales forecasting can help you decide where to make hires and when. Not only that, but it can help companies decide whether they should look at outsourcing or whether to bring outsourced activities back in-house, e.g., the use of courier companies versus investing in your own delivery fleet.
• Provides valuable revenue expectations to outside stakeholders, like investors – sales forecasting quantifies your revenue predictions, making it easier and less risky to attain outside support from investors and stakeholders.
• Allows for simple company benchmarking against competitors – where your business ranks against competitors is important, and sales forecasting highlights how your trajectory compares to your closest rivals.
• Offers a powerful means of motivating sales personnel – a sales forecast is the best way of benchmarking the performance of salespeople within your business. It’s also a great motivator, particularly for staff incentivised by the promise of commission.

Many internal and external factors can impact the accuracy of your sales forecasts. You’ll need to account for all sorts of influences when predicting sales activity, including:

• Economic uncertainty and conditions
• Competitor changes
• Market trends and seasonality
• Product changes and future innovations
• Internal pricing or policy changes
• Available marketing spend and budgets
• Staff levels (more or fewer sales personnel will affect figures, for example)
• Future business plans e.g., expansion or diversification plans

This isn’t an exhaustive list of factors that can affect sales forecasting, but it does provide a steer for the types of influences that you’ll need to factor into your predictions.

Sales forecasting isn’t rocket science, but it does require a methodical approach to guarantee accuracy. Here, we’ll demonstrate how to make accurate sales predictions in five easy-to-follow steps.

Step 1: Consider Sales History

The first step to accurate sales forecasting is to look not to the future, but the past. By examining sales data over the past 12 months, you’ll glean insights that you can use as the basis of your future sales predictions, noting things like volumes, trends, and seasonality changes that caused peaks and troughs in demand.

When exploring historic sales data, be mindful of your ‘sales run rate’ – the number of projected sales for a particular period. For example, sales data may reveal a large disparity between quarterly sales figures, affecting the overall run rate; you’ll need to factor this into your forecasts for the future.

Step 2: Anticipate Changes and External Influences

While historic sales data provides a clear view of when and where sales typically happen over a year, it doesn’t guarantee the same sales figures for the future. Depending on a plethora of external and internal influences, next year’s sales could be up or down – so how do you accurately predict future revenue?

Start by taking each influence in turn and assess how such a force would have impacted last year’s sales figures. For example, do you plan to increase prices over the next 12 months? If so, how might this affect sales in relation to previous figures?

Here are some of the factors you should consider when predicting future sales performance:

• Pricing changes – will your prices change? How might this affect custom?
• Customer changes and trends – are consumer trends turning in your favour, or going the other way? Market awareness is crucial for accurate sales forecasting.
• Promotions – do you have any sales or promotions lined up to increase demand? How might these affect sales targets?
• Product alterations – are you improving your products and services?
• Sales channels – do you plan to expand into additional sales channels in the near future or acquire new branches?

Step 3: Lean on the Right Systems for Accurate Data Capture and Analysis

Sales forecasting becomes much simpler and more accurate when the right tools are used to capture and analyse data. Integrated ERP software, for example, collates sales data from every channel of your business – including trade counter or EPOS sales, telesales, sales rep orders, ecommerce etc. – so you can make data-backed predictions with confidence.

A great example of the types of tools you can use for accurate sales forecasting is predictive stock management. Automating the forecasting process, it presents the user with a forecast prediction aligned to their stock preferences, e.g., how much buffer stock you want to carry, as well as stock lead times.

Presented with this data, the procurement team can then use their insight and knowledge to tweak this forecast where necessary. It’s a great example of the marriage of automation to reduce manual work, whilst still allowing people to have input on the end result.

Elsewhere, utilising customised dashboards or control desks, instead of static reports, to differentiate pipeline value by rep, branch, prospect customer etc., can give businesses dynamic information to adjust their forecasts and be agile around expectations and demand.

What’s more, clever use of the CRM in conjunction with opportunity probability management enables you to allocate an estimated percentage chance that you think you will win a sales deal. By giving each sales opportunity/quotation a probability, you can produce a sales weighting forecast that will give you a fairly accurate idea of what your sales will be.

This will give you a better chance of forecasting the revenue and stock position of months and years ahead.

Step 4: Align Sales Predictions with Your Business Strategy

Many businesses have a five-year plan, a strategy that looks to drive business growth and profitability. But remember, such a plan will impact sales in one way or another, so it’s important that you align your sales forecasts with your short and long-term business objectives.

Say, for example, your business plan sets out a period of growth in the form of new hires or the creation of a whole new department. How will this affect sales? And to what extent should it be factored into your revenue forecasts?

Aligning your business strategy and sales forecasts is a crucial step. It helps prioritise business activity, ensuring that the right decisions are made to drive the business forward.

Step 5: Set Out Your Sales Forecasts in the Right Way

Charts, graphs and annotations can all be used to set out your sales forecasts for the year ahead. These should be included in your business plan, providing an accessible means of sharing forecasts with key stakeholders, personnel and investors.

As well as charting forecasts in number terms, you should set out your sales strategy, including how you arrived at the quoted figures. This not only quantifies your reasoning, but serves as a reminder of the market position at the time of writing – something that could prove useful if you need to refer back to where the figures came from at a later date.

Sales forecasting can be a laborious process, particularly if you want to guarantee accuracy. There are, however, a range of tools and software which can be leveraged to automate some elements of the process, removing some of the legwork associated with sales forecasting.

At Intact, we’re well aware of the importance of sales forecasting – and the arduous nature of it. That’s why we offer specialist expertise and solutions to help automate and simplify the process, from ERP software and predictive stock management to data analytics tools designed to improve data-driven decision-making.

We hope this guide helps you take stock of sales forecasting. If you’d like to optimise this area of your business, the Intact team can help. For more information or to speak to a member of our specialist team, visit the homepage . Alternatively, for more help and advice on ways to manage your inventory, take a look at our free guide to effective stock management .

Thinking of upgrading your business management software?

This e ssential step-by-step guide will help you make your software implementation journey as seamless and effective as possible.

Other posts you might also like

WTH (What the heck) is IFTTT: How codeless customisation tools like Nexus work

Intact attending the NMBS Exhibition 2024

Sign me up for intact news and updates.

• Phone This field is for validation purposes and should be left unchanged.

7-step guide to financial forecasting & planning for any business

What is financial forecasting, why is it important, and how to properly conduct financial planning and forecasting

• What is financial forecasting?
• Why is it important?
• 4 common types of financial forecasting
• How to do financial forecasting in 7 steps
• Financial forecasting FAQs

Join our newsletter for the latest in SaaS

By subscribing you agree to receive the Paddle newsletter. Unsubscribe at any time.

Uncertainty is one of the constant aspects of doing business. Many factors beyond your control can potentially influence the market in ways you didn't expect. For example, new technologies are constantly changing operations across almost all industries at a fundamental level. 

It pays to know what to expect in the near future and plan ahead, hence the need for financial forecasting. Every business (including monopolies) could benefit incredibly from regular  financial forecasting . Here is a comprehensive guide on the importance of financial forecasting for your business model and how to do it.

Failure to conduct regular financial forecasting leaves you flying blind.

What is financial forecasting? 

Financial forecasting refers to financial projections performed to facilitate any decision-making relevant for determining future business performance. The financial forecasting process includes the analysis of past business performance, current  business trends , and other relevant factors.

However, some aspects of financial forecasting may change depending on the type and purpose of the forecast, as will be discussed later. 

Importance of financial forecasting 

Hypothetically speaking, failure to conduct regular financial forecasting leaves you flying blind. Regular forecasting has extensive benefits for some of your business' fundamental operations, including: 

Annual budget planning 

A budget represents your business' cash flow, financial positions, and future goals and expectations for a set fiscal period.  Financial forecasting and planning  work in tandem, as forecasting essentially offers an insight into your business' future—these insights help make budgeting accurate.  

Establishing realistic business goals 

Accurate forecasting will help predict whether (and by how much) your business will grow or decline. As such, you can set realistic and achievable goals—and manage your expectations. 

Identifying problem areas 

Financial forecasting  can help you identify ongoing problems by analyzing the business' past performance. Additionally, you can identify potential problems by getting an insight into what the future holds. 

Reduction of financial risk 

You risk overspending by creating a budget without financial forecasting. In fact, most of your financial decisions would be ill-informed without the input of a financial forecast's results. 

Greater company appeal to attract investors 

Investors use a company's financial forecast to predict its future performance—and the potential ROIs on their investments. Additionally, regular forecasting shows your investors that you are in control and have a solid business plan prepared for the future.

4 common types of financial forecasting 

Businesses conduct financial forecasting for varying purposes. Consequently, forecasting practices are categorized into four types: 

1. Sales forecasting 

Sales forecasting entails predicting the amounts of products/services you expect to sell within a projected fiscal period. There are two sales forecasting methodologies: top-down forecasting and bottom-up forecasting. 

Sales forecasting has many uses and benefits, including budgeting and planning production cycles. It also helps companies manage and allocate resources more efficiently. 

2. Cash flow forecasting 

Cash flow forecasting  entails estimating the flow of cash in and out of the company over a set fiscal period. It's based on factors such as income and expenses. It has many uses and benefits, including identifying immediate funding needs and budgeting. However, it is worth noting that cash flow financial forecasting is more accurate over a short term. 

3. Budget forecasting 

As a financial guide for your business' future, a budget creates certain expectations about your company's performance. Budget forecasting aims to determine the ideal outcome of the budget, assuming that everything proceeds as planned. It relies on the budget's data, which relies on financial forecasting data. 

4. Income forecasting 

Income forecasting entails analyzing the company's past revenue performance and current growth rate to estimate future income. It is integral to doing  cash flow  and balance sheet forecasting. Additionally, the company's investors, suppliers, and other concerned third parties use this data to make crucial decisions. For example, suppliers use it when determining how much to credit the company in supplies. 

How to do financial forecasting in 7 steps 

Many integral aspects of your company's current and future operations hinge on the results of your financial forecasts. For example, forecasting results will influence investors' decisions, determine how much your company can get in credit, and more. 

As such, accuracy cannot be overemphasized. Here is a step-by-step guide to ensure that you do it right: 

1. Define the purpose of a financial forecast 

What do you hope to learn from the financial forecast? Do you hope to estimate how many units of your products or services you will sell? Or perhaps you wish to see how the company's current budget will shape its future? Defining your financial forecast's purpose is essential to determining which metrics and factors to consider when doing it. 

2. Gather past financial statements and historical data 

One of the components of financial forecasting involves analyzing past financial data, as explained. As such, it is important to gather all relevant historical  data and records , including: 

• Liabilities 
• Investments 
• Expenditures 
• Comprehensive income 
• Earnings per share 
• Fixed costs

It's important to ensure that you gather all required information as your financial forecast's results will be inaccurate if you exclude relevant data.

3. Choose a time frame for your forecast 

Financial forecasts are designed to give business owners an insight into the company's future. You get to decide how far into the future to look, and it can range from several weeks to several years. However, most companies do forecasts for one fiscal year. 

Financial forecasts change over time as factors such as business and market trends change. Consequently, it is worth noting that financial forecasting is more accurate in the short term than in the long term.

4. Choose a financial forecast method 

There are two financial forecasting methods: 

• Quantitative forecasting uses historical information and data to identify trends, reliable patterns, and trends. 
• Qualitative forecasting analyzes experts' opinions and sentiments about the company and market as a whole. 

Each method is suitable for different uses and has its strengths and shortcomings. However, qualitative forecasting is more suitable for startups without past data to which they can refer. 

5. Document and monitor results 

Financial forecasts are never 100% accurate and tend to change over time. As such, it is important to document and monitor your forecast's results over time, especially after major internal and external developments. It is also important to update your forecasts to reflect the latest developments. Using  forecasting software  to automate related tasks may help too.

6. Analyze financial data 

Regularly analyzing financial data is the best way to tell whether your financial forecasts are accurate. Additionally, continuous financial management and analysis helps you prepare better for the next financial forecast and gives you crucial insights into the company's current financial performance. 

7. Repeat based on the previously defined time frame 

Smart companies conduct regular financial forecasting to stay in the know and in control. As such, it is advisable to repeat the process once the time period set for the current financial forecast elapses. It's also prudent to keep collecting, recording, and analyzing data to improve your financial forecasts' accuracy.

Get accurate metrics for financial forecasting—absolutely free 

An efficient system of collecting, storing, and analyzing data is necessary for accurate financial forecasting. ProfitWell Metrics is a subscription analytics software designed to do all of this on one platform. Some of the metrics that you can get using this program include: 

• Monthly and annual recurring revenues 
• Market and customer segments 
• Customer acquisition and retention 
• Customer lifetime value 
• Churn rate 
• The average revenue per user 

ProfitWell Metrics collects and records all  important metrics , giving you enough data to work with when conducting a financial forecast. Additionally, the data collected in real-time offers crucial insights to help you update your forecasts and other projects accordingly. 

ProfitWell Metrics also integrates seamlessly with other popular data analytics programs, including Google Sheets and Stripe. More importantly, it's 100% free and secure. 

Take the headache out of growing your software business

We handle your payments, tax, subscription management and more, so you can focus on growing your software and subscription business.

Financial forecasting FAQs 

Some of the most frequently asked questions regarding financial forecasting include: 

What is the role of forecasting in financial planning? 

Financial forecasting estimates important financial metrics such as sales, income, and future revenue. These metrics are crucial for finance-related operations such as budgeting and financial planning as a whole. Consequently, forecasting functions as a guiding tool (or marking scheme) for financial planning. 

What is the difference between financial forecasting and modeling? 

On the one hand, financial forecasting entails predicting the business' future performance. On the other hand, financial modeling entails simulating how financial forecasts and other data may affect the company's future if everything goes according to plan. Financial modeling is done for very specific and often discrete purposes. 

What is the difference between financial forecasting and budgeting? 

Financial forecasting and budgeting work in tandem and are often misinterpreted as meaning the same thing. However, financial forecasting entails estimating and predicting the company's future performance (financially and in other aspects). On the other hand, budgeting is the company's financial expectations for the future (expectations based on financial forecasts and other data). 

What are the three pro forma statements needed for financial forecasting? 

Pro forma statements are financial reports designed to give insights into how different scenarios would play out based on hypothetical circumstances. There are three pro forma statements: 

• Pro forma statements of income 
• Pro forma cash flow statements 
• Pro forma balance sheets 

Pro forma statements may be hypothetical, but they help companies prepare for an uncertain future. Consequently, they're useful when conducting financial forecasts. 

Related reading

• Travel, Tourism & Hospitality ›

Accommodation

Industry-specific and extensively researched technical data (partially from exclusive partnerships). A paid subscription is required for full access.

• Overnight accommodation cost in Moscow monthly 2020-2023

Average cost of overnight accommodation in Moscow from May 2020 to September 2023 (in euros)

• Immediate access to 1m+ statistics
• Incl. source references
• Download as PNG, PDF, XLS, PPT

Additional Information

Show sources information Show publisher information Use Ask Statista Research Service

September 2023

May 2020 to September 2023

Cost of a standard double room. Release date is the date of access.

Other statistics on the topic Travel and tourism in Russia

Leisure Travel

• Number of outbound tourists from Russia 2022, by territory
• Number of outbound tourism trips from Russia 2014-2022
• Number of inbound tourist arrivals in Russia 2014-2022
• Number of domestic airline passengers in Russia monthly 2020-2022

To download this statistic in XLS format you need a Statista Account

To download this statistic in PNG format you need a Statista Account

To download this statistic in PDF format you need a Statista Account

To download this statistic in PPT format you need a Statista Account

As a Premium user you get access to the detailed source references and background information about this statistic.

As a Premium user you get access to background information and details about the release of this statistic.

As soon as this statistic is updated, you will immediately be notified via e-mail.

… to incorporate the statistic into your presentation at any time.

You need at least a Starter Account to use this feature.

• Immediate access to statistics, forecasts & reports
• Usage and publication rights
• Download in various formats

You only have access to basic statistics. This statistic is not included in your account.

• Instant access  to 1m statistics
• Download  in XLS, PDF & PNG format
• Detailed  references

Business Solutions including all features.

Statistics on " Travel and tourism in Russia "

• Countries with the highest outbound tourism expenditure worldwide 2019-2022
• Travel industry revenue distribution in Russia 2021, by segment
• Tourism spending in Russia 2019-2022, by travel purpose
• Travel and tourism's total contribution to GDP in Russia 2019-2023
• Travel and tourism's total contribution to employment in Russia 2019-2023
• Outbound travel expenditure in Russia 2011-2022
• Leading outbound travel destinations in Russia 2021-2022
• Outbound tourist flow growth in Russia 2022, by destination
• European Union (EU) Schengen visas issued in Russia 2010-2021
• International tourism spending in Russia 2011-2022
• Leading source markets for travel to Russia 2020-2022, by arrivals
• Domestic travel spending in Russia 2019-2022
• Number of nature protected areas in Russia 2015-2022, by type
• Estimated demand for inbound tourism in Russia Q1 2014-Q3 2023
• Inbound tourist flow growth in Russia 2020-2023
• Travel industry organizations distribution in Russia 2021, by segment
• Number of tourism companies in Russia 2010-2022
• Most popular travel websites in Russia 2023, by traffic
• Number of package tours sold in Russia 2014-2021, by type
• Value of package tours sold in Russia 2014-2021, by type
• Package tour cost in Russia 2014-2022, by type
• Most popular travel destinations on package tours in Russia 2022
• Passenger traffic growth of airlines in Russia 2021
• Travel transportation consumer price in Russia 2021, by type
• Paid travel accommodation services value in Russia 2015-2022
• Travel accommodation establishments in Russia 2022, by federal district
• Total room area in travel accommodation in Russia 2013-2022
• Number of visitors in hotels in Russia 2010-2022
• Number of hotel visitors in Russia 2022, by travel purpose
• Hotel occupancy rate in Moscow 2023, by segment
• Average daily hotel rate in Moscow 2023, by segment
• Reasons to not travel long-haul in Russia 2022
• Intention to travel to Europe in Russia 2019-2022
• Summer vacation plans of Russians 2012-2023
• Travel frequency for private purposes in Russia 2023
• Average holiday spend per person in Russia 2011-2023
• Attitudes towards traveling in Russia 2023
• Travel product online bookings in Russia 2023

Other statistics that may interest you Travel and tourism in Russia

• Premium Statistic Countries with the highest outbound tourism expenditure worldwide 2019-2022
• Premium Statistic Travel industry revenue distribution in Russia 2021, by segment
• Premium Statistic Tourism spending in Russia 2019-2022, by travel purpose
• Basic Statistic Travel and tourism's total contribution to GDP in Russia 2019-2023
• Basic Statistic Travel and tourism's total contribution to employment in Russia 2019-2023

Outbound tourism

• Basic Statistic Outbound travel expenditure in Russia 2011-2022
• Premium Statistic Number of outbound tourism trips from Russia 2014-2022
• Premium Statistic Leading outbound travel destinations in Russia 2021-2022
• Premium Statistic Number of outbound tourists from Russia 2022, by territory
• Premium Statistic Outbound tourist flow growth in Russia 2022, by destination
• Premium Statistic European Union (EU) Schengen visas issued in Russia 2010-2021

Inbound and domestic tourism

• Basic Statistic International tourism spending in Russia 2011-2022
• Premium Statistic Leading source markets for travel to Russia 2020-2022, by arrivals
• Basic Statistic Domestic travel spending in Russia 2019-2022
• Basic Statistic Number of nature protected areas in Russia 2015-2022, by type
• Premium Statistic Estimated demand for inbound tourism in Russia Q1 2014-Q3 2023
• Premium Statistic Inbound tourist flow growth in Russia 2020-2023
• Premium Statistic Number of inbound tourist arrivals in Russia 2014-2022

Travel companies

• Premium Statistic Travel industry organizations distribution in Russia 2021, by segment
• Premium Statistic Number of tourism companies in Russia 2010-2022
• Premium Statistic Most popular travel websites in Russia 2023, by traffic

Package tours

• Premium Statistic Number of package tours sold in Russia 2014-2021, by type
• Premium Statistic Value of package tours sold in Russia 2014-2021, by type
• Premium Statistic Package tour cost in Russia 2014-2022, by type
• Premium Statistic Most popular travel destinations on package tours in Russia 2022

Transportation

• Premium Statistic Number of domestic airline passengers in Russia monthly 2020-2022
• Premium Statistic Passenger traffic growth of airlines in Russia 2021
• Premium Statistic Travel transportation consumer price in Russia 2021, by type
• Basic Statistic Paid travel accommodation services value in Russia 2015-2022
• Premium Statistic Travel accommodation establishments in Russia 2022, by federal district
• Basic Statistic Total room area in travel accommodation in Russia 2013-2022
• Premium Statistic Number of visitors in hotels in Russia 2010-2022
• Basic Statistic Number of hotel visitors in Russia 2022, by travel purpose
• Premium Statistic Overnight accommodation cost in Moscow monthly 2020-2023
• Premium Statistic Hotel occupancy rate in Moscow 2023, by segment
• Premium Statistic Average daily hotel rate in Moscow 2023, by segment

Travel behavior

• Premium Statistic Reasons to not travel long-haul in Russia 2022
• Premium Statistic Intention to travel to Europe in Russia 2019-2022
• Basic Statistic Summer vacation plans of Russians 2012-2023
• Premium Statistic Travel frequency for private purposes in Russia 2023
• Basic Statistic Average holiday spend per person in Russia 2011-2023
• Premium Statistic Attitudes towards traveling in Russia 2023
• Premium Statistic Travel product online bookings in Russia 2023

Further related statistics

• Premium Statistic Overnight accommodation costs in Milan 2015-2017, by month
• Premium Statistic Overnight accommodation costs in Greece 2015-2017, by month
• Premium Statistic Overnight accommodation costs in the Czech Republic 2015-2017, by month
• Premium Statistic Overnight accommodation costs in Vienna 2023, by month
• Premium Statistic Overnight accommodation costs in Norway 2015-2017, by month
• Premium Statistic Overnight accommodation costs in Switzerland 2015-2017, by month
• Premium Statistic Overnight accommodation costs in France 2015-2017, by month
• Premium Statistic Overnight accommodation costs in Spain 2015-2017, by month
• Premium Statistic Overnight accommodation costs in London 2019-2022, by month
• Premium Statistic Overnight accommodation costs in Venice 2015-2017, by month
• Premium Statistic Overnight accommodation costs in Munich 2015-2017, by month
• Premium Statistic Overnight accommodation costs in Germany 2015-2017, by month
• Premium Statistic Overnight accommodation costs in Russia 2015-2017, by month
• Premium Statistic Overnight accommodation costs in Budapest 2015-2017, by month
• Premium Statistic Overnight accommodation costs in Finland 2015-2017, by month

Further Content: You might find this interesting as well

• Overnight accommodation costs in Milan 2015-2017, by month
• Overnight accommodation costs in Greece 2015-2017, by month
• Overnight accommodation costs in the Czech Republic 2015-2017, by month
• Overnight accommodation costs in Vienna 2023, by month
• Overnight accommodation costs in Norway 2015-2017, by month
• Overnight accommodation costs in Switzerland 2015-2017, by month
• Overnight accommodation costs in France 2015-2017, by month
• Overnight accommodation costs in Spain 2015-2017, by month
• Overnight accommodation costs in London 2019-2022, by month
• Overnight accommodation costs in Venice 2015-2017, by month
• Overnight accommodation costs in Munich 2015-2017, by month
• Overnight accommodation costs in Germany 2015-2017, by month
• Overnight accommodation costs in Russia 2015-2017, by month
• Overnight accommodation costs in Budapest 2015-2017, by month
• Overnight accommodation costs in Finland 2015-2017, by month

2018 Primetime Emmy & James Beard Award Winner

R&K Insider

Join our newsletter to get exclusives on where our correspondents travel, what they eat, where they stay. Free to sign up.

A History of Moscow in 13 Dishes

Featured city guides.