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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)

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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

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How to write a sales forecast for a business plan

Table of Contents

What is a sales forecast?

Why do you need a sales forecast, how do you write a sales forecast, top-down or bottom-up, writing your sales forecast, calculating a sales forecast, how can countingup help manage your forecasting.

Sales forecasts are an important part of your business plan . If done correctly, they can give accurate projections of your business’ cash flow, and let you better prepare for the year ahead. They can also make it easier to find the right investors . While it’s easier for existing businesses with plenty of data, you can still calculate a sales forecast for a new business .

In this guide, we’ll explore:

• How can you manage your forecasting?

A sales forecast is a prediction of your business’ future revenue. In order to be an accurate prediction, the forecast is based on previous sales, current economic trends, and industry performance. Having a sales forecast is a useful tool, because it gives you a better idea of how to manage your business. 

Having a sales forecast is like using the past to have a peek into the future of your company. It might not be 100% accurate, but it can help you plan any future spending, or prevent any cash flow issues from occurring. 

You can also use your sales forecast to monitor your business’ progress. For instance, if your business regularly performs better than your forecast, it could be a sign that your business is continuing to grow. On the other hand, if your actual sales are frequently less than expected, this could be a sign that your business is struggling and needs adjustment. 

It’s important to remember that any projections you make aren’t guaranteed, there can be advantages and disadvantages of financial forecasting . 

Now we’ve run through why having a sales forecast can help you run your business, let’s look at how to write one. 

While there are two types of sales forecasting (top-down and bottom-up), one is a lot more accurate for small businesses than the other. A top-down forecast looks at the market as a whole and attributes a portion of the market to your business. 

A top-down approach may work for large businesses that already own a significant chunk of the market. When forecasting for a small business, it’s easy to overestimate your market share. For example, a 1% market share may not seem like a lot, but a small restaurant owning 1% of the £89.5 billion UK market is extremely unrealistic.

The alternative to top-down is bottom-up. A bottom-up sales forecast starts with existing company data (like customer or product information) and works up to revenue. Since this starts with the company, it’s easier to 

Your sales forecast is ultimately a prediction of your revenue over a set period. It considers the amount you think you’ll sell, and the cost of those sales. We’ve included how to calculate a sales forecast below.

A sales forecast consists of three separate values: revenue, cost of goods sold, and gross profit. For estimating values in the calculations below, it’s best to use any existing business data to be as accurate as possible. 

To calculate your predicted revenue:

• Make a list of your available goods and services
• Note the price of each of your goods and services
• Estimate the expected sales of each good or service
• Multiply the price by the estimated sales to get your estimated revenue
• Add them all together to get your total revenue

For example, if your food truck business sold pizzas at £10 and burgers at £5, you would multiply these values by how much you expected to sell. For calculating a weekly sales forecast, you might estimate selling 60 pizzas and 80 burgers. Your predicted revenue for that week would be £600 for pizzas and £400 for burgers — giving £1,000 total.

In order to figure out how much profit you’ll make, you also need to calculate your costs for those predicted sales. To calculate your predicted costs:

• Figure out how much each good or service will cost per unit
• Multiply each cost by the projected sales

Using the same example as above, assume a single pizza cost £3.50 to make and a burger cost £2. Using the estimated sales, the total cost for your pizzas (3.5 x 60) would be £210, and £160 for your burgers (2 x 80). Combining these two figures gives you a total cost of £370.

The last step is to work out your gross profit , and it’s a relatively simple calculation.

• Subtract the total predicted cost from your total predicted revenue

Continuing with the example above, your revenue (£1,000) minus your costs (£370), leaves you with a projected gross profit of £630 for the week. Using this estimate, you can then plan how much working capital your business should have access to. It’s important to remember that these are only estimates, and your actual values can be higher or lower than your forecast.

If you want your forecasts to be as accurate as possible, you need to refer to all of your business’ financial data. Since collecting and collating this data can be challenging, you may want to use financial management software like the Countingup app. 

When trying to calculate your sales forecasts, having an up-to-date log of your current sales can be hugely beneficial. By combining a business current account with accounting software, Countingup is the only software that provides real-time cash flow tracking. 

The Countingup app also provides business owners with access to automatically generated profit and loss statements. These can prove invaluable when trying to stay aware of all your business’ costs.

Start your three-month free trial today. Find out more here .

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10 Sales Forecasting Methods & How to Pick One in 2024

Dozie Anyaegbunam is the Senior Editor of The CMO, digital marketing firepower for SaaS pioneers. He's a marketing strategist with years of experience in Marketing, Communications, Ecommerce, and SEO. And has worked across verticals ranging from software to edu-tech, apparel, and F&B, leading teams at B2B SaaS startups, global multinationals, and the public sector. He’s the Founder & Host of The Newcomer’s Podcast featuring immigrants and their stories of moving to a new country, and he’s currently producing a documentary on the immigrant’s experience.

Which sales forecasting method should you pick? How do you forecast using your chosen method? I've got all the deets and more.

Why should you care about sales forecasting? Simple. It's the backbone of your entire sales strategy. Ignore it, and you and your sales team are flying blind. And considering how topsy-turvy the economy has been in recent times, this is not the time to depend on luck or gut feelings to hit your sales targets.

In this article, we'll break down the following:

• Why sales forecasting is crucial to hitting your commitment goals
• The top forecasting methods that separate the winning sales teams from the rest
• How to identify the best marketing software for forecasting
• And what you need to consider when forecasting, no matter the method you choose.

Let's goooo.

Sales forecasting is key to financial management: Sales forecasting is essential for informed decision-making, resource allocation, and optimizing business strategy to maximize revenue. Ignoring it leaves your sales team flying blind, especially during volatile economic times.

It's a great strategy for boosting morale and and building alignment: Accurate sales forecasts boost the sales team's morale by setting clear targets, help identify process bottlenecks, align marketing efforts, and enable resource planning, contributing to overall team motivation and performance.

Your business context is key to picking a sales forecasting method: Choosing the best forecasting method requires understanding your business and aligning with other departments. Internal cooperation ensures complete data, realistic assumptions, and shared responsibility.

What is Sales Forecasting?

Sales forecasting is the process of predicting future sales revenue over a specific period. It combines historical sales data, market trends, and business intelligence to estimate how much a company will sell in the coming weeks, months, or years.

When done well, sales forecasting enables your business to make informed decisions about resource allocation, manage cash flow, set goals, and optimize the overall business strategy to maximize revenue and growth.

Key components of sales forecasting include:

• Historical sales data analysis
• Market trend evaluation
• Customer behavior insights
• Economic indicators
• Sales pipeline assessment

Why is Sales Forecasting Important?

Yes, sales forecasting helps predict future sales performance and enables companies to make informed decisions. But it also...

• Highlight potential issues with your sales process: This can uncover bottlenecks or inefficiencies in the sales process. For example, reviewing sales forecasting can highlight areas where the sales team may be struggling, such as lead generation or closing deals.
• Boost the sales team's morale: Accurate sales forecasts provide the sales team with clear targets and expectations. When the team meets or exceeds these targets, it boosts their morale and motivation. If you celebrate and acknowledge the team's hard work, this can lead to increased job satisfaction.
• Align marketing and sales teams: The Marketing team can use the sales forecasts to plan campaigns and allocate resources to support the sales team's goals. Working together ensures consistent messaging and a seamless customer experience, increasing the chances of conversions, and helps with marketing funnel optimization .
• Plan for additional investments in the team: If forecasts indicate strong growth potential, companies can allocate resources for hiring additional sales representatives, providing training, or investing in tools and technology to support the team. These investments help the sales team scale and capitalize on growth opportunities.
• Enable positive investor relationships: Investors rely on accurate forecasts to assess the company's financial health and make informed investment decisions. With reliable sales forecasts, companies can build trust with investors and secure the necessary funding for growth and expansion.

Effective sales forecasting ultimately contributes to the business's overall success and long-term sustainability.

10 Sales Forecasting Methods

Sales forecasting methods vary in complexity and the type of data they rely on. In this section, we'll explore 10 popular sales forecasting methods that businesses use to predict future sales performance.

Picking a particular method will depend on factors such as available data, the your business, and your specific goals.

1. The Historical Sales Forecasting Method

The historical sales forecasting method is a simple yet effective approach that relies on past sales data to predict future sales performance. This method assumes that future sales will follow a similar pattern to past sales, making it a reliable choice for businesses with stable sales cycles and consistent growth patterns.

It considers factors such as seasonality, growth trends, and other patterns the team identifies in the historical data. Sales leaders like it because it is:

• Easy to implement and understand, even for those without extensive forecasting experience
• Requires minimal data collection and analysis, making it a cost-effective option
• Provides a solid foundation for future forecasts, especially when combined with other methods.

Some pro tips for getting the best results out of this forecasting method include:

• Use a sufficiently long period to capture any seasonal or cyclical trends in your sales data
• Adjust for any anomalies or one-time events that may skew the historical data
• Regularly update your forecast as new sales data becomes available to ensure accuracy

While this method may only account for some of the market's complexities, it serves as an excellent starting point for many businesses looking to improve their sales forecasting process.

2. Lead-Driven Sales Forecasting Method

The lead-driven sales forecasting method focuses on the sales pipeline's quality and quantity of leads to predict future sales performance. This method recognizes that the success of a business's sales efforts depends heavily on the strength of its lead generation and nurturing processes.

With this method, you analyze the number and quality of leads at each sales funnel stage, from initial contact to closed deals. Businesses can create a more accurate forecast of future sales by assigning a probability of closing to each lead based on factors such as lead source, engagement level, and historical conversion rates.

Some of the benefits of this approach include:

• Provides a clear picture of the sales pipeline and identifies areas for improvement
• Helps sales teams prioritize their efforts by focusing on the most promising leads
• Enables businesses to make data-driven decisions about resource allocation and marketing strategies.

If you're looking to get the best out of the lead-driven approach, ensure you:

• Establish clear criteria for qualifying leads and assigning them to different stages of the sales funnel
• Regularly review and update lead probabilities based on new information and engagement levels
• Collaborate with the marketing team to personalize at scale your lead generation and nurturing processes.

This method requires close collaboration between sales and marketing teams and a commitment to continuous optimization based on the data from your lead generation campaigns.

3. Intuitive Sales Forecasting Method

The intuitive sales forecasting method relies on the expertise and judgment of experienced sales professionals to predict future sales performance. This approach recognizes that intangible factors, such as market sentiment, competitive dynamics, and customer preferences, often influence sales outcomes that may not be captured by the data.

Here, sales managers and representatives use their industry knowledge, understanding of customer needs, and intuition to estimate future sales. This usually happens over brainstorming sessions where sales team members share their insights and collectively develop a forecast based on their expertise.

A few reasons why some sales teams prefer this approach include:

• Leverages the deep industry knowledge and experience of sales professionals
• Accounts for intangible factors and market nuances that may not be reflected in historical data
• Fosters collaboration and knowledge-sharing among sales team members.

If you're looking to adopt this method, some pro tips for getting the best results include:

• Involve a diverse group of sales professionals with varying levels of experience and expertise
• Encourage open and honest discussion and create a safe space for sharing dissenting opinions
• Combine intuitive forecasts with data-driven methods to balance qualitative and quantitative insights

However, it's essential to recognize that intuitive forecasts can be subject to bias and should be balanced with data-driven methods to ensure accuracy.

4. Opportunity Stage Sales Forecasting Method

With the opportunity stage sales forecasting method, you focus on the progress of individual sales opportunities through the sales pipeline to predict future revenue. This method recognizes the likelihood of closing a deal increases as opportunities move through different stages, from initial contact to negotiations and final decision-making.

To do this, track the status of each sales opportunity and assign a probability of closing based on its current stage in the pipeline. Then, analyze the number and value of opportunities at each stage and consider the average time it takes for opportunities to move through the pipeline.

Benefits of the opportunity stage forecasting approach include:

• Provides a detailed view of the sales pipeline and helps identify bottlenecks or areas for improvement
• Enables sales teams to focus their efforts on the most promising opportunities
• Allows for more accurate revenue predictions based on the probability of closing at each stage.

If you're looking to adopt this approach, some tips to consider are:

• Clearly define the stages of your sales pipeline and the criteria for moving opportunities from one stage to another
• Regularly update opportunity statuses and probabilities based on new information and customer interactions
• Use historical data to refine your probability estimates and average time-to-close for each stage.

This method requires a disciplined approach to pipeline management and a commitment to regularly updating opportunity statuses based on new information.

5. Length of Sales Cycle Sales Forecasting Method

The length of the sales cycle forecasting method is a valuable approach that considers the time it typically takes for a prospect to move through the sales process, from initial contact to closing the deal. This method recognizes that understanding the average length of the sales cycle is crucial for accurately predicting future revenue and making informed decisions about resource allocation.

Sales teams implement this method by analyzing historical data to determine the average time it takes for a prospect to progress through each stage of the sales pipeline. Based on the number of prospects at each stage and the average time-to-close, the team forecasts the expected revenue based on the typical sales cycle length.

The benefits of the length of sales cycle method are:

• Helps businesses set realistic expectations for revenue generation based on the average sales cycle length
• Enables sales teams to identify opportunities to streamline the sales process and reduce the time-to-close
• Allows for more accurate resource planning and budgeting based on expected revenue timelines.

Some pro tips for getting the best results include:

• Segment your analysis by product line, customer type, or region to account for variations in sales cycle length
• Regularly review and update your average sales cycle length based on new data and changing market conditions
• Use this method with other forecasting techniques to gain a more comprehensive view of future revenue.

This method is beneficial for businesses with longer sales cycles or complex sales processes, as it helps to account for the time lag between initial contact and revenue generation.

6. Multivariable Analysis Sales Forecasting Method

If you're looking for a complex, the multivariable analysis sales forecasting method is one. It considers multiple internal and external factors to predict future sales performance. This method recognizes that a complex interplay of variables, such as market trends, competitive landscape, economic conditions, and company-specific factors influences sales outcomes.

Here, you use statistical techniques, such as regression analysis or machine learning algorithms, to analyze historical sales data alongside relevant variables to identify the most significant variables and their impact on sales performance.

The benefits of adopting this approach are:

• Provides a holistic view of the factors influencing sales performance, enabling more informed decision-making
• Helps identify the most critical drivers of sales success and areas for strategic focus
• Enables businesses to create multiple forecast scenarios based on different assumptions and market conditions.

Some pro tips for getting the best results:

• Identify and collect data on a wide range of relevant variables, both internal and external to the organization
• Use appropriate statistical techniques and tools to analyze the data and identify significant relationships
• Regularly update your model with new data and refine your variable selection based on changing market conditions.

This approach requires a significant investment in data collection and analysis and expertise in statistical modeling and interpretation.

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7. Consumption-Based Sales Forecasting Method

Consumption-based sales forecasting focuses on predicting future sales based on customers' actual consumption or usage of a product or service. This method is particularly relevant for businesses that offer subscription-based services, consumables, or products with a regular repurchase cycle.

To get this right, you need to look at historical data on customer usage patterns, such as the frequency and volume of product consumption or the average duration of service usage. You also must consider factors like customer churn, acquisition, and changes in usage behavior to get an accurate picture of future sales.

• Provides a more accurate picture of future revenue by considering actual customer behavior and usage patterns
• Helps businesses optimize inventory management and production planning based on expected consumption levels
• Enables targeted marketing and sales efforts to drive increased consumption and customer loyalty.

Some pro tips for getting the best results are:

• Collect detailed data on customer usage patterns, including frequency, volume, and any seasonal or cyclical trends
• Analyze customer segments to identify different usage profiles and tailor forecasts accordingly
• Monitor changes in customer behavior and adjust forecasts based on factors like churn, acquisition, and shifts in usage patterns.

You need a team that is skilled at data collection and analysis and deeply understands your customer behaviour, demand patterns, and market dynamics.

8. Test-Market Analysis Sales Forecasting Method

Suppose your business wants to introduce new offerings or expand into unfamiliar markets. In that case, the test-market analysis approach is a great way to garner insights into market receptiveness and potential demand.

It involves selecting a smaller, representative market that closely resembles the target market regarding demographics, preferences, and buying behaviors. The product or service is launched in this test market, and sales data is collected and analyzed to assess customer response, market penetration, and sales velocity.

You then use the insights gained from the test market to refine the offering, adjust marketing strategies, and create a more accurate forecast for the full-scale launch.

Here's why you should consider this approach if you are looking to launch a new product offering:

• Provides real-world data on customer reception and market demand for a new product or service
• Allows businesses to refine their offering and marketing approach based on actual customer feedback
• Identifying potential issues early on reduces the risk and cost associated with a full-scale launch.
• Select a test market that closely mirrors the target market in terms of critical characteristics and buying behaviors
• Set clear objectives and metrics for the test market analysis, such as sales volume, market share, and customer satisfaction
• Use the insights gained from the test market to refine the product, pricing, and marketing strategy before the full-scale launch.

To get the most out of this sales forecasting method, you must be willing to adapt based on the insights gained from the test market.

9. Regression Sales Forecasting Method

The regression sales method is another sophisticated forecasting approach. It's a statistical method that analyzes the relationship between sales performance and various independent variables, such as price, advertising spending, economic indicators, and competitor activities.

Sales teams use historical sales data and relevant independent variables to create a mathematical model that predicts future sales performance. The model identifies the most significant variables influencing sales and quantifies their impact. The team then uses the data to create accurate forecasts and simulate different scenarios based on changes in these variables.

Some reasons why this is a popular forecasting approach with some teams include:

• Provides a deep understanding of the factors that drive sales performance and their relative importance
• Enables businesses to create accurate, data-driven forecasts that account for multiple variables and their interactions
• Allows for scenario planning and what-if analysis to optimize sales strategies and resource allocation.

Before you consider adopting this approach, here are some pro tips for getting it right:

• Identify and collect data on a wide range of relevant independent variables that may influence sales performance
• Use appropriate regression techniques, such as multiple linear regression or machine learning algorithms, based on the complexity of the data and the relationships between variables
• Regularly update the model with new data and refine the variable selection to ensure the model remains accurate and relevant.

You must invest in data collection, analysis, and modeling expertise.

10. Time Series Sales Forecasting Method

The time series forecasting method uses historical sales data over a specific period to identify patterns, trends, and seasonality, which are then used to predict future sales performance. This method is handy for businesses with a long sales history and consistent sales patterns, as it helps them make accurate forecasts and plan for future growth.

You'll need to collect and analyze sales data regularly, such as daily, weekly, monthly, or quarterly. The data is then plotted on a graph to visualize trends and patterns over time.

Statistical techniques, such as moving averages, exponential smoothing, or autoregressive integrated moving averages (ARIMA) models, are applied to the data to create a forecast that accounts for historical patterns and trends.

• Provides a clear visual representation of sales trends and patterns over time, making it easier to identify seasonality and other cyclical factors
• Enables businesses to create accurate short-term and long-term forecasts based on historical data
• Helps companies to plan for future demand, optimize inventory management, and allocate resources effectively.
• Ensure that sales data is collected consistently and accurately over a sufficiently long period to identify meaningful patterns and trends
• Choose the appropriate time series forecasting technique based on the complexity of the data and the presence of trends, seasonality, or other patterns
• Regularly update the forecast with new data and adjust the model parameters to remain accurate and relevant.

However, the accuracy of the time series sales forecasting method depends on the quality and consistency of the historical data and the choice of an appropriate forecasting technique.

How to Forecast Sales Using Your Chosen Method

Decided on which forecasting method is your go-to approach yet? While at it, here's how to apply your chosen approach effectively.

1. Review Historical Data

This is a crucial first step in the sales forecasting process. This step entails collecting and organizing past sales data from various sources, such as your CRM system, marketing automation data, financial reports, and marketing analytics.

The data should cover a sufficient period to identify meaningful patterns and trends, typically from several months to a few years, depending on your business cycle and your chosen forecasting method.

Pro tips for getting the best results:

• Ensure data accuracy and completeness by cleaning and validating your sales data, removing any duplicates or inconsistencies, and filling in missing information where possible
• Analyze sales data at different levels of granularity, such as by product line, customer segment, geographic region, or sales channel, to gain a more nuanced understanding of your sales performance
• To better contextualize your historical data, look for external factors that may have influenced past sales, such as economic conditions, competitor activities, or market trends.

2. Set Sales Goals and Quota

Next, you'll need to provide a clear target for your sales team to work towards. This helps align your forecasting efforts with your overall business objectives. Establishing ambitious yet achievable sales goals and quotas helps motivate your team and track progress so you can optimize your sales performance if necessary.

You can set these targets at various levels, such as individual sales rep quotas, team goals, or company-wide revenue targets. Given your resources and market conditions, sales goals and quotas should be challenging enough to drive performance but realistic enough to be achievable.

• Use your historical data analysis to inform your sales goals and quotas, considering factors such as past performance, growth trends, and seasonality
• Involve your sales team in the goal-setting process to ensure buy-in and alignment, gathering their input on what is achievable and what resources they need to succeed
• Break down larger sales goals into smaller, more manageable milestones to help your team stay motivated and track progress throughout the forecasting period.

3. Choose Your Preferred Sales Forecasting Method

Now it's time to decide. Yes, don't put it off any longer. Each forecasting method has its strengths and limitations. However, choosing your preferred method means evaluating and selecting the approach that best aligns with your business needs, data availability, and resource constraints.

This step requires a deep understanding of your sales process, market conditions, and the key drivers of your sales performance.

• Consider your business objectives, sales cycle, and data availability when selecting a forecasting method, ensuring that the chosen approach aligns with your needs and constraints
• Evaluate the complexity and interpretability of different forecasting methods, choosing one that balances sophistication with ease of use and communication with stakeholders
• Feel free to experiment with multiple forecasting methods and compare their accuracy and reliability over time, refining your approach as you gain more insights and experience.

4. Align with Other Departments

Internal alignment is vital. It ensures your predictions are accurate, actionable, and supported by the entire organization. Collaborating with key stakeholders across different functions, such as marketing, finance, and operations, enables you to create a more comprehensive, realistic forecast that takes into account various factors influencing your sales performance.

Spend time workshopping with all the other stakeholders to gather insights, validate assumptions, and ensure buy-in for your forecasting efforts. Be willing to listen to different perspectives and incorporate them into your forecasting model.

• Identify key stakeholders across different departments who can provide valuable insights and support for your forecasting efforts, such as marketing leaders, financial analysts, and operations managers
• Schedule regular cross-functional meetings to discuss your forecasting assumptions, share updates on your progress, and gather feedback and input from other departments
• Communicate the impact of your sales forecasts on other departments' goals and objectives, highlighting how accurate predictions can help them plan and allocate resources more effectively.

5. Invest in Sales Forecasting Software

With the right forecasting tools, you can automate much of the data collection, analysis, and modeling, freeing up time and resources to focus on more strategic tasks and decision-making.

The best sales forecasting software often uses advanced analytics, machine learning, and data visualization capabilities to help you gather, process, and interpret large volumes of sales data more effectively.

Pro tips for identifying and adopting specialized sales forecasting tools:

• Evaluate multiple sales forecasting software options based on your specific needs, budget, and technical requirements, considering factors such as data integration, scalability, and ease of use
• Look for software that offers robust data visualization and reporting features, enabling you to communicate your forecasts and insights more effectively to stakeholders across the organization
• Invest in training and support to ensure that your team can fully leverage the capabilities of your chosen sales forecasting software, maximizing its impact on your forecasting accuracy and efficiency.

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Typical Sales Forecasting Challenges

Creating accurate and reliable forecasts can be challenging due to various factors, such as data quality issues, market volatility, and organizational silos. However, inaccurate forecasting can also have disastrous consequences, including misallocated resources, missed opportunities, financial instability, and strained stakeholder relationships.

Here are the typical sales forecasting challenges to watch out for and how to prevent them from happening.

1. Misaligned Marketing, Sales, and Finance Teams

Misalignment between marketing, sales, and finance teams occurs when these functions operate in silos, pursuing different goals and metrics without clear communication or collaboration. This disconnect can manifest in various ways, such as marketing focusing on lead generation without considering sales quotas, sales prioritizing short-term deals over long-term profitability, or finance setting budgets without input from marketing and sales.

This leads to inconsistent data and assumptions across teams, misallocating resources and budgets due to conflicting priorities, missed opportunities for growth, and erosion of trust and accountability between teams, damaging morale and performance.

Pro tips for preventing this from happening:

• Establish clear, shared goals and metrics that align marketing, sales, and finance objectives
• Implement regular cross-functional meetings and communication channels to foster collaboration and information sharing
• Invest in integrated technology platforms that provide a single source of truth for data and insights across teams.

2. Inaccurate Data

With reliable, high-quality data, even the most sophisticated forecasting methods and tools will produce good results, leading to misguided decisions and suboptimal outcomes.

This can stem from various sources, such as manual data entry errors, disparate data systems, or a need for more data governance and quality control processes. Inaccurate data can also result from a failure to capture critical variables or external factors that influence sales, such as market trends or competitor activities.

• Implement robust data governance and quality control processes to ensure data accuracy and consistency
• Invest in data integration and automation tools to minimize manual data entry and reduce errors
• Regularly review and validate data inputs and assumptions used in forecasting models.

3. Incomplete or Non-existent Sales History

The lack of historical records of past sales performance means companies lack the foundation to identify trends, patterns, and key drivers of success. This can occur for various reasons, such as being a new business, launching a new product or service, or failing to track and record sales data consistently.

Without the data, everything else is assumptions and guesswork. This often increases the risk of over- or underestimating future sales, leading to resource misallocation. The sales team also finds it difficult to identify trends, seasonality, and other patterns that have influenced sales performance in the past.

• Prioritize consistent, accurate sales data tracking and recording from the outset of the business or product launch
• Leverage external data sources, such as industry benchmarks or market research, to inform forecasting assumptions
• Invest in sales forecasting software that can help fill in data gaps and provide intelligent predictions based on limited information.

4. Limitations of Your Sales Tools

Choosing the right sales forecasting tools is a must. Limitations can manifest in various ways, such as a lack of data integration, limited reporting and visualization capabilities, or an inability to handle the complexity and scale of your sales operations. When your sales tools are not up to the task, it can create bottlenecks, data silos, and blind spots that undermine the accuracy and effectiveness of your forecasting process.

• Regularly assess your sales tools and technologies to identify gaps and limitations
• Invest in scalable, flexible solutions that can adapt to your evolving needs and integrate with other vital systems
• Prioritize user experience and adoption to ensure your team can fully leverage the capabilities of your sales tools.

How to Improve the Accuracy of Your Sales Forecasting Method

Here's how...

1. Review and Update Your Sales Forecasts Regularly

By treating forecasting as an ongoing process rather than a one-time event, you can continuously refine your assumptions, incorporate new data and insights, and adapt to changing market conditions.

This means setting a cadence for revisiting your predictions, comparing them against actual performance, and making necessary adjustments. You'll need a systematic approach for monitoring key metrics, gathering stakeholder feedback, and analyzing variances between forecasted and actual results.

This way, you can identify areas for improvement, test new hypotheses, and ensure your predictions remain a reliable guide for decision-making.

2. Consider Internal and External Factors when Forecasting

To ensure your sales predictions are realistic and grounded in the broader context of your business and market, look beyond historical sales data and consider internal and external factors when forecasting.

Internal factors may include sales team capacity, product innovations, or marketing campaigns, while external factors could encompass economic conditions, competitor actions, or regulatory changes. By identifying and analyzing these factors, you can build more robust forecasting models that capture the full range of influences on your sales performance.

3. Take Advantage of AI

AI enables you to harness the power of advanced algorithms, machine learning, and predictive analytics to create more accurate, efficient, and actionable predictions. These tools can unlock valuable insights hidden in your sales data, automate complex analyses, and help you make data-driven decisions faster and more confidently.

However, this also requires a deliberate approach to identifying the right AI tools and techniques for your specific needs and a commitment to data quality, model validation, and continuous improvement. Do this well, and you can augment human expertise and judgment with AI's processing power.

4. Take Advantage of Sales Forecasting Tools

One sure-fire way to save time, reduce errors, and gain deeper insights into your sales performance and potential is to introduce purpose-built sales forecasting software into your sales workflow.

These specialized software solutions can significantly improve your sales prediction process's accuracy, efficiency, and effectiveness. Depending on your specific forecasting needs and goals, many of these tools offer a range of features, such as data integration, predictive modeling, scenario planning, and interactive dashboards. All of which can help automate and scale your forecasting process.

Introducing shared tools and data also encourages collaboration and alignment among sales, finance, and other teams.

Factors to Consider When Sales Forecasting

When creating accurate and reliable sales forecasts, you'll need to consider numerous factors. Here are the seven most prominent ones.

1. Market Changes

You must stay attuned to shifts in customer preferences, economic conditions, technological advancements, regulatory updates, and industry trends, as these can impact your sales performance and forecasting accuracy.

These changes can create opportunities and challenges for your sales efforts, affecting everything from pricing and positioning to target audiences and sales strategies. If you don't adjust your forecasts to reflect shifts in customer demand, competitive pressures, or market conditions, you risk making decisions based on outdated or inaccurate assumptions. This can result in missed targets, wasted resources, and lost opportunities.

2. Economic Conditions

From consumer spending and business investment to interest rates and inflation, the state of the economy can significantly influence the demand for your products or services, as well as your ability to achieve your sales targets.

These changes impact customer budgets and alter purchasing priorities. So, ignoring economic conditions in your sales forecasts can lead to significant disconnects between your expectations and reality. Doing so ensures you don't misallocate resources, and you make predictions that are grounded in reality.

3. Competitive Context Changes

Changes in the competitive context can impact your sales performance and forecasting accuracy. Rival companies entering or exiting the market, launching new products, or changing their approach can affect customer preferences, pricing, and market share.

Disregarding pricing adjustments or new market entrants can lead to a wrong view of your sales potential, leading to inaccurate predictions and suboptimal decision-making. To prevent this from happening, regularly update your sales forecasts based on new competitive developments and consider scenario planning to prepare for different competitive outcomes.

4. Product Changes

Failing to account for product changes in your sales forecasts can result in a significant disconnect between your projections and actual performance. You risk basing your estimates on outdated or irrelevant assumptions without considering how new offerings or enhancements may affect customer interest, deal sizes, or sales timelines.

New product launches, feature enhancements, packaging or pricing adjustments, or even the sunset of existing products can all influence customer demand, the sales cycles, and the revenue potential of your product offerings. Collaborating closely with your product management and marketing teams to gain early visibility into any competitive planned product changes and their expected market impact.

5. Policy and Legislative Changes

Ignoring policy and legislative changes in your sales forecasts can leave you vulnerable to sudden market changes or customer preferences. This includes changes in tax policies, trade agreements, industry-specific regulations, or government spending priorities.

As new laws, regulations, or policy initiatives are introduced or amended, the game's rules can change quickly, affecting customer demand, compliance requirements, and the overall business environment in which you operate.

To stay informed about relevant policy and legislative developments, regularly monitor government announcements and industry publications and set up legal or regulatory alerts.

6. Job Changes

Job changes within your sales team or broader organization are one change we need to talk about more.

As crucial personnel move into new roles, leave the company, or are replaced by new hires, the dynamics within the sales team can shift, affecting team morale, productivity, and the continuity of customer relationships. These changes often disrupt established workflows, alter your team's skills and experience mix, and impact the relationships and trust built with customers.

To minimize the effect this can have on your forecasting process, work on developing robust onboarding, training, and knowledge transfer processes to reduce the learning curve and productivity impact of personnel transitions. You should also build contingency plans and adjust your sales forecasts based on different job change scenarios, considering ramp-up times, territory reassignments, and customer relationship handovers.

7. Territory Changes

When you expand into new countries, redistribute territories among sales reps, or change the criteria for account ownership, you risk disrupting established sales patterns, altering the workload and focus of your team, and impacting relationships and knowledge built within specific territories.

These changes can significantly impact the sales pipeline. So, you’ll need to develop clear communication and transition plans to support sales reps adapting to territory changes. This also minimizes the disruptions to customer relationships

It's Your Turn to Create Accurate, Actionable Sales Forecasts

We've explored the importance of sales forecasting and the key steps, methods, and factors involved in creating accurate, reliable predictions.

By understanding the different forecasting techniques, aligning with other departments, and considering a wide range of internal and external factors, you can develop a robust sales forecasting process that empowers your team to make informed decisions and drive better performance.

Doing so also creates a culture of data-driven decision-making and continuous learning within your sales organization. This ensures your team can adapt quickly to changing market conditions, customer needs, and industry changes.

Keep in mind it's an ongoing process of iteration and improvement. So, stay committed to regularly reviewing and updating your forecasts, incorporating new data and insights, and seeking feedback from your team and stakeholders.

Frequently Asked Questions

What is the most important factor in sales forecasting.

The most important factor in sales forecasting is the accuracy and reliability of the data used. More accurate forecasts can be made by combining historical sales data with predictive analytics and regular updates.

How can businesses improve their sales forecasting accuracy?

To improve sales forecasting accuracy, businesses can utilize forecasting software, update forecasts regularly, consider external factors, and balance intuition with data. This can lead to more accurate predictions and better decision-making.

What is the role of seasonality in sales forecasting?

Seasonality significantly impacts sales forecasting by influencing customer purchasing behaviors, and understanding seasonal trends is crucial for making accurate predictions.

Why is it important to integrate CRM and sales data?

Integrating CRM and sales data is crucial because it ensures that forecasts are based on clean, reliable data. This helps maintain accurate records and provides valuable insights for more accurate sales predictions, which can significantly improve the overall effectiveness of sales strategies.

What are the benefits of test market analysis forecasting?

Test market analysis forecasting is beneficial as it helps businesses refine product offerings and gauge market response before a full-scale launch, thereby reducing risks and improving forecast accuracy. Therefore, it provides valuable insights into customer preferences and buying behavior.

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• Sales forecasting: How to create a sale ...

Sales forecasting: How to create a sales forecast template (with examples)

A strong sales team is the key to success for most companies. They say a good salesperson can sell sand at the beach, but whether you’re selling products in the Caribbean or Antarctica, it all comes down to strategy. When you’re unsure if your current strategy is working, a sales forecast can help.

What is a sales forecast?

A sales forecast predicts future sales revenue using past business data. Your sales forecast can predict a number of different things, including the number of new sales for an existing product, the new customers you’ll gain, or the memberships you’ll sell in a given time period. These forecasts are then used during project planning to determine how much you should allocate towards new products and services. 

Why is sales forecasting important?

Sales forecasting helps you keep a finger on your business’s pulse. It sets the ground rules for a variety of business operations, including your sales strategy and project planning. Once you calculate your sales projections, you can use the results to assess your business health, predict cash flow, and adjust your plans accordingly.

An effective sales forecasting plan:

Predicts demand: When you have an idea of how many units you may sell, you can get a head start on production.

Helps you make smart investments: If you have future goals of expanding your business with new locations or products, knowing when you’ll have the income to do so is important. 

Contributes to goal setting: Your sales forecast can help you set goals outside of investments as well, like outshining competitors or hiring new team members.

Guides spending: Your sales forecast may be the wake-up call you need to set a budget and use cost control to reduce expenses.

Improves the sales process: You can change your current sales process based on the sales projections you’re unhappy with.

Highlights financial problems: Your sales forecast template will open your eyes to problem areas you may not have noticed otherwise. 

Helps with resource management: Do you have the resources you need to fill orders if it’s an accurate sales forecast? Your sales forecast can guide how you allocate and manage resources to hit targets.

When you have an accurate prediction of your future sales, you can use your projections to adjust your current sales process.

Sales forecasting methods

Sales forecasting is an important part of strategic business planning because it enables sales managers and teams to predict future sales and make informed decisions. But why are there multiple sales forecasting methods? Simply put, businesses vary in size, industry, and market dynamics, so no single methodology suits all.

Choosing the right sales forecasting method is more of an art than a science. It involves:

Analyzing your business size and industry

Assessing the available data and tools

Understanding your sales cycle's complexity

A few telltale signs that you've picked the correct approach include:

Improved accuracy in sales target predictions

Enhanced understanding of market trends

Better alignment with your business goals

Opportunity stage forecasting

Opportunity stage forecasting is a dynamic approach ideal for businesses using CRM systems like Salesforce. It assesses the likelihood of sales closing based on the stages of the sales pipeline. This method is particularly beneficial for sales organizations with a clearly defined sales process.

For example, a software company might use this method to forecast sales by examining the number of prospects in each stage of their funnel, from initial contact to final negotiation.

Pipeline forecasting method

The pipeline forecasting method is similar to opportunity stage forecasting but focuses more on the volume and quality of leads at each pipeline stage. It's particularly useful for businesses that rely heavily on sales forecasting tools and dashboards for decision-making.

A real estate agency could use it by examining the number of properties listed, the stage of negotiations, and the number of closings forecasted in the pipeline.

Length of sales cycle forecasting

Small businesses often prefer the length of sales cycle forecasting. It's straightforward and involves analyzing the duration of past sales cycles to predict future ones. This method is effective for businesses with consistent sales cycle lengths.

A furniture manufacturer, for instance, might use this method by analyzing the average time taken from initial customer contact to closing a sale in the past year.

Intuitive forecasting

Intuitive forecasting relies on the expertise and intuition of sales managers and their teams. It's less about spreadsheets and more about market research and understanding customer behavior. This method is often used with other, more data-driven approaches.

A boutique fashion store, for example, might use this method, relying on the owner's deep understanding of fashion trends and customer preferences.

Historical forecasting

Historical forecasting uses past performance data to predict future sales. This method is advantageous for businesses with ample historical sales data. It's less effective for new markets or rapidly changing industries.

An established book retailer could use historical data from previous years, considering seasonal trends and past marketing campaigns, to forecast next quarter's sales.

Multivariable analysis forecasting

Multivariable analysis forecasting is a more sophisticated method that's ideal for larger sales organizations. It analyzes factors like market trends, economic conditions, and marketing efforts to provide a holistic view of potential sales outcomes.

An automotive company, for example, could analyze factors like economic conditions, competitor activity, and past sales data to forecast future car sales.

How to calculate sales forecast

Sales forecasts determine how much you expect to do in sales for a given time frame. For example, let’s say you expect to sell 100 units in Q1 of fiscal year 2024. To calculate sales forecasts, you’ll use past data to predict future trends. 

When you’re first creating a forecast, it’s important to establish benchmarks that determine how much you normally sell of any given product to how many people. Compare historical sales data against sales quotas—i.e., how much you sold vs. how much you expected to sell. This type of analysis can help you set a baseline for what you expect to achieve every week, month, quarter, and so on.

For many companies, this means establishing a formula. The exact inputs will vary based on your products or services, but generally, you can use the following:

Sales forecast = Number of products you expect to sell x The value of each product

For example, if you sell SaaS products, your sales forecast might look something like this: 

SaaS FY24 Sales forecast = Number of expected subscribers x Subscription price

Ultimately, the sales forecasting process is a guess—but it’s an educated one. You’ll use the information you already have to create a data-driven forecasting model. How accurate your forecast is depends on your sales team. The sales team uses facts such as their prospects, current market conditions, and their sales pipeline. But they will also use their experience in the field to decide on final numbers for what they think will sell. Because of this, sales leaders are more likely to have better forecasting accuracy than new members of the sales team.

Sales forecast vs. sales goal

Your sales forecast is based on historical data and current market conditions. While you always hope your sales goals are attainable—and you can use data to estimate what your team is capable of—your goals might not line up directly with your forecast. This can be for a number of reasons, including wanting to create stretch goals that push your sales team beyond what they’ve done in the past or big, pie-in-the-sky goals that boost investor confidence.

How to create a sales forecast

There are different sales forecasting methods, and some are simpler than others. With the steps below, you’ll have a basic understanding of how to create a sales forecast template that you can customize to the method of your choice. 

1. Track your business data

Without details from your past sales, you won’t have anything to base your predictions on. If you don’t have past sales data, you can begin tracking sales now to create a sales forecast in the future. The data you’ll need to track includes:

Number of units sold per month

Revenue of each product by month

Number of units returned or canceled (so you can get an accurate sales calculation)

Other items you can track to make your predictions more accurate include:

Growth percentage

Number of sales representatives

Average sales cycle length

There are different ways to use these data points when forecasting sales. If you want to calculate your sales run rate, which is your projected revenue for the next year, use your revenue from the past month and multiply it by 12. Then, adjust this number based on other relevant data points, like seasonality.

Tip: The best way to track historical data is to use customer relationship management (CRM) software. When you have a CRM strategy in place, you can easily pull data into your sales forecast template and make quick projections.

2. Set your metrics

Before you perform the calculations in your sales forecast template, you need to decide what you’re measuring. The basic questions you should ask are:

What is the product or service you’re selling and forecasting for? Answering this question helps you decide what exactly you’re evaluating. For example, you can investigate future trends for a long-standing product to decide whether it’s worth continuing, or you can predict future sales for a new product. 

How far in the future do you want to make projections? You can decide to make projections for as little as six months or as much as five years in the future. The complexity of your sales forecast is up to you.

How much will you sell each product for, and how do you measure your products? Set your product’s metrics, whether they be units, hours, memberships, or something else. That way, you can calculate revenue on a price-per-unit basis.

How long is your sales cycle? Your sales cycle—also called a sales funnel—is how long it takes for you to make the average sale from beginning to end. Sales cycles are often monthly, quarterly, or yearly. Depending on the product you’re selling, your sales cycle may be unique. Steps in the sales cycle typically include:

Lead generation

Lead qualification

Initial contact

Making an offer

Negotiation

Closing the deal

Tip: You can still project customer growth versus revenue even if your company is in its early phases. If you don’t have enough historical data to use for your sales forecast template, you can use data from a company similar to yours in the market. 

3. Choose a forecasting method

While there are many forecasting methods to choose from, we’ll concentrate on two straightforward approaches to provide a clear understanding of how sales forecasting can be implemented efficiently. The top-down method starts with the total size of the market and works down, while the bottom-up method starts with your business and expands out.

Top-down method: To use the top-down method, start with the total size of the market—or total addressable market (TAM). Then, estimate how much of the market you think your business can capture. For example, if you’re in a large, oversaturated market, you may only capture 3% of the TAM. If the total addressable market is $1 billion, your projected annual sales would be $30 million. 

Bottom-up method: With the bottom-up method, you’ll estimate the total units your company will sell in a sales cycle, then multiply that number by your average cost per unit. You can expand out by adding other variables, like the number of sales reps, department expenses, or website views. The bottom-up forecasting method uses company data to project more specific results. 

You’ll need to choose one method to fill in your sales forecast template, but you can also try both methods to compare results.

Tip: The best forecasting method for you may depend on what type of business you’re running. If your company experiences little fluctuation in revenue, then the top-down forecasting method should work well. The top-down model can also work for new businesses that have little business data to work with. Bottom-up forecasting may be better for seasonal businesses or startups looking to make future budget and staffing decisions.

4. Calculate your sales forecast

You’ve already learned a basic way to calculate revenue using the top-down method. Below, you’ll see another way to estimate your projected sales revenue on an annual scale.

Divide your sales revenue for the year so far by the number of months so far to calculate your average monthly sales rate.

Multiply your average monthly sales rate by the number of months left in the year to calculate your projected sales revenue for the rest of the year.

Add your total sales revenue so far to your projected sales revenue for the rest of the year to calculate your annual sales forecast.

A more generalized way to estimate your future sales revenue for the year is to multiply your total sales revenue from the previous year.

Example: Let’s say your company sells a software application for $300 per unit and you sold 500 units from January to March. Your sales revenue so far is $150,000 ($300 per unit x 500 units sold). You’re three months into the calendar year, so your average monthly sales rate is $50,000 ($150,000 / 3 months). That means your projected sales revenue for the rest of the year is $450,000 ($50,000 x 9 months).

5. Adjust for external factors

A sales forecast predicts future revenue by making assumptions about your growth rate based on past success. But your past success is only one component of your growth rate. There are external factors outside of your control that can affect sales growth—and you should consider them if you want to make accurate projections. 

Some external factors you can adjust your calculations around include:

Inflation rate: Inflation is how much prices increase over a specific time period, and it usually fluctuates based on a country’s overall economic state. You can take your annual sales forecast and factor in inflation rate to ensure you’re not projecting a higher or lower number of sales than the economy will permit.

The competition: Is your market becoming more competitive as time goes on? For example, are you selling software during a tech boom? If so, assess whether your market share will shrink because of rising competition in the coming year(s).

Market changes: The market can shift as people change their behavior. Your audience may spend an average of six hours per day on their phones in one year. In the next year, mental health awareness may cause phone usage to drop. These changes are hard to predict, so you must stay on top of market news.

Industry changes: Industry changes happen when new products and technologies come on the market and make other products obsolete. One instance of this is the invention of AI technology.

Legislation: Although not as common, changes in legislation can affect the way companies sell their products. For example, vaping was a multi-million dollar industry until laws banned the sale of vape products to people under the age of 21. 

Seasonality: Many industries experience seasonality based on how human behavior and human needs change with the seasons. For example, people spend more time inside during the winter, so they may be on their computers more. Retail stores may also experience a jump in sales around Christmas time.

Tip: You can create a comprehensive sales plan to set goals for team members. Aside from revenue targets and training milestones, consider assigning each of these external factors to your team members so they can keep track of essential information. That way, you’ll have your bases covered on anything that may affect future sales growth. 

Sales forecast template

Below you’ll see an example of a software company’s six-month sales forecast template for two products. Product one is a software application, and product two is a software accessory. 

In this sales forecast template, the company used past sales data to fill in each month. They projected their sales would increase by 10% each month because of a 5% increase in inflation and because they gained 5% more of the market. They kept their price per unit the same as the previous year.

Putting both products in the same chart can help the company see that their lower-cost product—the software accessory—brings in more revenue than their higher-cost product. The company can then use this insight to create more low-cost products in the future.

Sales forecast examples

Sales forecasting is not a one-size-fits-all process. It varies significantly across industries and business sizes. Understanding this through practical examples can help businesses identify the most suitable forecasting method for their unique needs.

Sales forecasting example 1: E-commerce

In the e-commerce sector, where trends can shift rapidly, intuitive forecasting is often useful for making quick, informed decisions.

Scenario: An e-commerce retailer specializing in fashion accessories is planning for the upcoming festive season.

Trend analysis phase: The team spends the first week analyzing customer feedback and current fashion trends on social media, using intuitive forecasting to predict which products will be popular.

Inventory planning phase: Based on these insights, the next three weeks are dedicated to selecting and ordering inventory, focusing on products predicted to be in high demand.

Sales monitoring and adjustment: As the holiday season approaches, the team closely monitors early sales data, ready to adjust their inventory and marketing strategies based on real-time sales performance.

This approach allows the e-commerce retailer to stay agile , adapting quickly to market trends and customer preferences.

Sales forecasting example 2: Software development

For a software development company, especially one working with B2B clients, opportunity stage forecasting can help predict sales and manage the sales pipeline effectively.

Scenario: A software development company is launching a new project management tool.

Lead generation and qualification phase: In the initial month, the sales team focuses on generating leads, qualifying them, and categorizing potential clients based on their progress through the sales pipeline.

Proposal and negotiation phase: For the next two months, the team works on creating tailored proposals for high-potential leads and enters negotiation stages, using opportunity stage forecasting to predict the likelihood of deal closures.

Closure and review: In the final phase, the team aims to close deals, review the accuracy of their initial forecasts, and refine their approach based on the outcomes.

Opportunity stage forecasting enables the software company to efficiently manage its sales pipeline , focusing resources on the most promising leads and improving their chances of successful deal closures.

Pair your sales forecast with a strong sales process

A sales forecast is only one part of the larger sales picture. As your team members acquire leads and close deals, you can track them through the sales pipeline. A solid sales plan is the foundation of future success.  

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How to Do a Sales Forecast for Your Business the Right Way

Posted june 8, 2021 by noah parsons.

New entrepreneurs frequently ask me for advice about forecasting their sales . These entrepreneurs are always optimistic about the future of their new company. However, when it comes to the details, most aren’t sure how to predict future sales and how much money they’re going to make.

It’s an intimidating task, looking into the future. The good thing is, none of us are fortune tellers and none of us know any more about your new business than you do. (If you do happen to be able to see into the future, please just skip the whole startup thing and go play the stock market. It’ll be much easier and make you richer!)

So, my advice is always to just take a deep breath and relax. You’re as well equipped as everyone else to put together a credible, reasonably accurate forecast. Let’s dive right in and figure it out.

What is sales forecasting?

Sales forecasting is the process of estimating future sales with the goal of better informing your decisions. A forecast is typically based on any combination of past sales data, industry benchmarks, or economic trends. It’s a method designed to help you better manage your workforce, ash flow, and any other resources that may affect revenue and sales

It’s typically easier for established businesses to create more accurate sales forecasts based on previous sales data. Newer businesses, on the other hand, will have to rely on market research, competitive benchmarks, and other forms of interest to establish a baseline for sales numbers. 

Why is sales forecasting important?

Your sales forecast is the foundation of the financial story that you are creating for your business. Once you have your sales forecast complete, you’ll be able to easily create your profit and loss statement , cash flow statement , and balance sheet.

Sales forecasts help you set goals

But beyond just setting the stage for a complete financial forecast, your sales forecast is really all about setting goals for your company . You’re looking to answer questions like:

• What do you hope to achieve in the next month? Year? 5-years? 
• How many customers do you hope to have next month and next year?
• How much will each customer hopefully spend with your company?

Your sales forecast will help you answer all of these questions and potentially any others that involve the future of your business.

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Sales forecasts inform investors

Having a solid sales forecast also provides a picture of your performance and performance milestones for potential investors. Like you, they want to be sure you have established goals and a firm trajectory for your business laid out. The more detailed, organized, and up-to-date your forecast is, the better you explain the position of your business to third parties and even employees.

How to use your sales forecast for budgeting

Your sales forecast is also your guide to how much you should be spending. Assuming you want to run a profitable business, you’ll use your sales forecast to guide what you should be spending on marketing to acquire new customers and how much you should be spending on operations and administration. 

Now, you don’t always need to be profitable, especially if you are trying to expand aggressively. But, you’ll eventually need your expenses to be less than your sales in order to turn a profit.

How detailed should your forecast be?

When you’re forecasting your sales , the first thing you should do is figure out what you should create a forecast for. You don’t want want to be too generic and just forecast sales for your entire company. On the other hand, you don’t want to create a forecast for every individual product or service that you sell.

For example, if you’re starting a restaurant, you don’t want to create forecasts for each item on the menu. Instead, you should focus on broader categories like lunch, dinner, and drinks. If you’re starting a clothing shop, forecast the key categories of clothing that you sell, like outerwear, casual wear, and so on.

You’ll probably want between three to ten categories covering the types of sales that you do. More than ten is going to be a lot of work to forecast and fewer than three probably means that you haven’t divided things up quite enough.

You really can’t get this wrong. After all, it’s just forecasting and you can always come back and adjust your categories later. Just pick a few to get started and move on.

Which forecasting model is best? Top-down or bottom-up?

Before they have much historical sales data, lots of startups make this mistake—and it’s a big one. They forecast “from the top down.” What that means is that they figure out the total size of the market (TAM, or total addressable market) and then decide that they will capture a small percentage of that total market.

For example, in 2015, more than 1.4 billion smartphones were sold worldwide. It’s pretty tempting for a startup to say that they’re going to get 1 percent of that total market. After all, 1 percent is such a tiny little number, it’s got to be believable, right?

The problem is that this kind of guessing is not based on any kind of reality. Sure, it looks like it might be credible on the surface, but you have to dig deeper. What’s driving those sales? How are people finding out about this new smartphone company? Of the people that find out about the new company, how many are going to buy?

So, instead of forecasting “from the top-down,” do a “bottom-up” forecast. Just like the name suggests, bottom-up forecasting is more of an educated guess, starting at the bottom and working up to a forecast.

Start by thinking about how many potential customers you might be able to make contact with; this could be through advertising, sales calls, or other marketing methods. This is your SOM (your “share of the market”), the subset of your 1 percent of the market that you will realistically reach—particularly in the first few years of your business. This is your target market .

Of the people you can reach, how many do you think you’ll be able to bring in the door or get onto your website? And finally, of the people that come in the door, get on the phone, or visit your site, how many will buy?

Here’s an example:

• 10,000 people see my company’s ad online
• 1,000 people click from the ad to my website
• 100 people end up making a purchase

Obviously, these are all nice round numbers, but it should give you an idea of how bottom-up forecasting works.

The last step of the bottom-up forecasting method is to think about the average amount that each of those 100 people in our example ends up spending. On average, do they spend $20? $100? It’s O.K. to guess here, and the best way to refine your guess is to go out and talk to your potential customers and interview them. You’ll be surprised how accurate a number you can get with a few simple interviews.

How to create a sales forecast

Keep in mind that your sales forecast is an estimate of the number of goods and services you believe you can sell over a period of time. This will also include the cost to produce and sell those goods and services, as well as the estimated profit you’ll come away with.

We’ll dive into specific methods, assumptions, and questions you’ll need to ask in order to build a viable sales forecast. But to start, here are the general steps you’ll need to take to create a sales 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

This is a super basic rundown of what is included in your sales forecast to give you an idea of what to expect. For example, you may find the need to aggregate similar items into unified categories, if you sell a large variety of items. And if at all possible, try to keep your forecasted items grouped similarly to how they appear on your accounting statements to make updates easier.

Check out this video for a quick overview of how to forecast sales:

Now let’s dive into some specific elements of your forecast you’ll need to define ahead of time.

Should you forecast in units or dollars?

Let’s start by talking about “unit” sales.

A “unit” is simply a stand-in for whatever it is that you are selling. A single lunch at a restaurant would be a unit. An hour of consulting work is also a unit. The word “unit” is just a generic way to talk about whatever it is that you are selling.

Now that’s out of the way, let’s talk about why you should forecast by units.

Units help you think about the number of products, hours, meals, and so on, that you are selling. It’s easier to think about sales this way rather than to think just in dollars (or yen, or pounds, or rand, etc.).

With a dollar-based forecast, you are only thinking about the total amount of money that you’ll make in a given month, rather than the details of the number of units that you are selling and the average price you are selling each unit for.

To forecast by units, you predict how many units you’re going to sell each month—using the bottom-up method of course. Then, you figure out what the average price is going to be for each unit. Multiply those two numbers together and you have the total sales you plan on making each month.

For example, if you plan on selling 1,000 units at $20 each, you’ll make $20,000.

When you forecast by units, you have a couple of different variables to play with: What if I’m able to sell more units? What if I raise or lower my prices?

Also, there’s another benefit: At the end of a month of sales, I can look back at my forecast and see how I did compared to the forecast in greater detail. Did I meet my goals because I sold more units? Or did I sell for a higher price than I thought I would? This level of detail helps you guide your business and grow it moving forward.

Sales forecast assumptions

One thing to remember is that your sales forecast is built on assumptions. You’re not predicting the future, but aggregating information to help define your future outlook. These assumptions are always changing, meaning that you’ll need to have a pulse on the following:  

Market conditions

Having a general understanding of the macro effects on your business can help you better predict overall growth. A growing or shrinking market can either provide a low or high ceiling for potential sales increases. So, you need to understand how your business can react to any changes.

What does the broader market look like? Is the economy slowing or growing? Is the industry you operate in seeing an influx of competition? Maybe there’s a labor or material shortage? Are there new customers you now have access to?

Products and services

You may find yourself making regular changes to your products and services. This can be sales factors that impact the customer, or production factors that impact the overall cost. 

Are you making any changes or updates to current offerings? Are you launching a new product or service that compliments or disrupts your existing sales? Are you adjusting prices or sales channels? Are you able to decrease the cost of production? Or are expenses rising due to material, labor, or other production costs?

Seasonality

Depending on what you’re selling, you may find dips or increases in sales at specific times during the year. This seasonality may have to do with the weather, holidays, product/feature releases, or a number of other predictable factors. 

If you have been operating for a while, you can likely look at your accounting data to identify any trends. If you’re a new business look to your competitors to see how they act during specific times of the year to help you identify these trends earlier on.

Marketing efforts

How much you spend on marketing, and even your messaging may have an impact on your overall sales. Make sure that you connect any performance changes to marketing efforts that may affect your performance.

Are you launching a new marketing campaign? Are you spending more or less on advertising? Are you adjusting your targeting for digital ads? Are you branching out or removing specific marketing channels from your overall strategy?

Regulatory changes

You may find that specific laws or regulations directly impact your industry. It’s difficult to anticipate what legislation will provide a negative or positive impact, and just how often this type of regulatory change may occur. The best thing you can do is keep your ear to the ground, and be ready to adjust expenses or sales when any changes appear to make traction.

How far forward should you forecast?

I recommend that you forecast monthly for 12 months into the future and then just develop an annual sales forecast for another three to five years.

The further your forecast into the future, the less you’re going to know and the less benefit it’s going to have for you. After all, the world is going to change, your business is going to change, and you’ll be updating your forecast to reflect those changes.

12 months from now is far enough into the future to guess. You’ll have to update your forecasts regularly with actual performance to help keep them accurate. 

And don’t forget, all forecasts are wrong—and that’s O.K. Your forecast is just your best guess at what’s going to happen. As you learn more about your business and your customers, you can change and adjust your forecast. It’s not set in stone.

Why using visuals will make forecasting easier

My final word of advice is to make sure that you graph your monthly sales with a chart.

A chart will make it easy to see how your sales might dip during a slow period of the year and then grow again during your peak season. A chart will also highlight potentially unreasonable guesses at your sales growth. If for example, you show a big jump in sales from one month to the next, you should be able to back this up with a strategy that’s going to deliver those sales.

Adjust your forecasts based on actual results

Your sales forecast isn’t done when you start sharing it with lenders and investors. Instead, smart businesses use their sales forecast to measure their progress and ensure that they’re on the right track. Their sales forecast becomes a live forecast . An up-to-date management tool that helps them run their business better.

The easiest way to convert your sales forecast into a management tool is to have a monthly financial review meeting where you look at your business’s finances. You shouldn’t just look at your accounting system, though. You should compare the numbers from your accounting software to your forecast and see if you’re on track. 

Are you exceeding your goals? Or maybe you’re falling a little bit short. Either way, knowing if you’re meeting your goals or not will help you determine if you need to make some shifts in strategy. This way, your business numbers drive your strategy.

Forecasting is easier with LivePlan

Sales forecasting tools like LivePlan can help with this. LivePlan uses a smart dashboard to automatically compare your forecast to your numbers from your accounting system—no cutting and pasting or complicated spreadsheets required. And with LivePlan’s LiveForecast feature , you can update the forecasts within your Profit and Loss Statement, with the push of a button. 

This allows you to spend less time updating and more time analyzing performance to make better decisions. In fact, the LiveForecast feature allows you to expand the details of your performance and identify the variance in performance within your statements. You’ll know your current cash position and the impact on projected year-end totals at a glance. It provides you with enough information to then explore the dashboard with questions and potential steps in mind.

Sales forecasting isn’t as difficult as you think

Just remember that sales forecasting doesn’t have to be hard. Anyone can do it and you, as an entrepreneur, are the most qualified to do it for your business. You know your customers, and you know your market, so you can forecast your sales.

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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 .

Fiona McGuinness

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Home > Financial Projections > Sales Forecast in a Business Plan

Sales Forecast in a Business Plan

The sales forecast sometimes referred to as the revenue forecast or revenue projection, is one of the most crucial set of numbers used in the business plan. Many of the numbers developed later in the financial projections such as inventory levels, staff costs, cash flow, funding requirements, and ultimately the business valuation, depend on the numbers used in the sales forecast.

Most sales forecasts will be wrong. Investors are not looking to see whether you can predict the future (you can’t), they are looking for you to demonstrate that you understand the issues that will impact on your forecast and to show that even in the worst case scenario, your business can survive.

Sales Forecast for New Business

A bottom up sales forecast should take into account many factors including the following:

Competitor Comparisons

If possible, start the sales forecast by looking at how others in the same industry (competitors) have performed over the past few years by obtaining copies of their published annual accounts. This will show at the very least whether the market for your product is growing or declining, and if the business is of a similar scale to your intended business, will show you the level of sales achievable, and how fast the sales can grow.

So for example, if you plan to open a retail outlet, monitor the number of customers passing, entering, and purchasing goods at a similar retail premises over say a period of a week. Using these estimates, and estimates of the average sale value per customer from sources such as trade magazines, it is possible to forecast the weekly sales for a typical retail outlet at that location.

If trade magazines and websites reveal the seasonality for the industry and show that this month normally represents 6% of annual sales, then the annual sales forecast might be 6,100 / 6% = 102,000 per year.

Business Operational Limitations

All businesses have operational limitations due to such factors as the number of staff, the size of the available premises, or the availability of finance. When producing a sales forecast it is important to check whether the forecast arrived at is achievable within the operational capabilities of the business.

For example, a restaurant has a given number of tables, seats and therefore covers available. The sales forecast needs to be developed such that the number of available covers is not exceeded. This can be seen in operation in our restaurant revenue projection template.

Market Research

The sales forecast can be improved using market research and customer surveys. By attending trade shows, interviewing a selection of potential customers, or placing a small advert for the product, it is possible from the numbers of positive responses, to estimate the number of customers your business is likely to get when it opens for trade. With this information, using the average sales value for the product, an estimated opening sales forecast can be developed.

Seasonality

The sales forecast needs to take into account the seasonality of the industry in which you operate. Few businesses have steady sales throughout the year. Many businesses are dependent on the weather or holiday periods such as Christmas, others are dependent on major trade show activity.

Rules of Thumb used in the Industry

Research in trade magazines and websites or discussion with people already in the industry will reveal any useful rules of thumb which can be applied to the business. For example it might be possible to estimate the level of repeat business using a rule of thumb.

One final approach, if information is not available, is to work out the sales forecast needed to generate the owner a required level of net income. While this approach will not have any foundation on which to support a financial projection, it will allow the owner of the business to decide whether the level of sales required is achievable before investing too much time and effort in the new venture.

Forecasting Sales and the Financial Projections Template

A good sales forecast should look five years ahead with the first year sales forecast on a monthly basis. How you forecast sales will depend on the type of industry in which it operates. We have created simple forecast templates for a number of industries, some which are listed below.

• Vacation Rental Business Plan Revenue Projection
• Hotel Revenue Projection Excel Template
• Drop Shipping Business Revenue Projection
• Food Truck Revenue Projection Template

More templates are available in our Business Templates Section , and more will be added in the future. If your industry is not listed contact us and let us know, and we’ll try to help.

About the Author

Chartered accountant Michael Brown is the founder and CEO of Plan Projections. He has worked as an accountant and consultant for more than 25 years and has built financial models for all types of industries. He has been the CFO or controller of both small and medium sized companies and has run small businesses of his own. He has been a manager and an auditor with Deloitte, a big 4 accountancy firm, and holds a degree from Loughborough University.

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Product Forecast

Table of Contents

What is a product forecast.

A product forecast is a prediction of the demand for a new product. Product forecasting involves analyzing past trends, market conditions, customer feedback, and other data to determine the likely sales volume of a product when it is launched. Businesses use product forecasting to plan their production and marketing efforts accordingly. It also helps them measure their potential for success or failure with a particular product.

Product forecasting is an essential part of product management. By accurately predicting demand, businesses can ensure they have enough stock to cover expected orders without overstocking and risking financial losses. 

Furthermore, product forecasting can help enterprises make sales projections and assess their pricing strategy and adjust it if necessary to maximize profits. In addition, it can be used to identify areas where additional marketing could be beneficial to increase awareness and boost sales.

• Product forecasting
• Premarketing forecasting
• Forecasting demand for a new product
• New product demand forecast

Benefits of Product Forecasting

Product forecasting, or demand forecasting, is an essential tool companies use to anticipate customer demand and plan product launches accordingly. It provides critical market insights to help companies make better marketing, distribution, and product development decisions.

Plan for Product Launches

The main benefit of product forecasting is that it allows companies to plan and be proactive in their approach to product launches. It helps companies gain insight into which products are likely to be successful and which may need more research or attention before launch. 

Improved Customer Service

With product forecasting, businesses can ensure that they have enough products on hand to meet customer demands. This allows them to provide a higher level of customer satisfaction by avoiding product shortages and delays in delivery times. Furthermore, product forecasting can help businesses better understand the needs of their customers and plan for any potential changes in demand.

Understand Customer Sentiment

Product forecasting can also help a company understand how customers view their product offerings compared to others on the market. This can provide valuable insight into what features customers find most appealing when selecting a product, which is then used to modify existing offerings or create new ones for future product launches. 

Reduced Costs

By accurately forecasting product demand, businesses can reduce their overhead costs as they only need to purchase and carry the inventory necessary to meet customer demands. This also helps companies to avoid costly excess stock, which can lead to financial losses due to storage fees or products becoming outdated before being sold.

Improved Revenue Streams

Knowing exactly what products are in high demand allows companies to focus their marketing efforts on those items that can increase revenue streams by maximizing sales opportunities. Additionally, product forecasting helps companies determine the pricing of new products by providing insight into market trends and consumer behaviors and preferences.

Predict Inventory Needs

Finally, product forecasting increases efficiency in stock management and inventory control measures, allowing companies to optimize supply chains and storage space while maintaining sufficient inventory levels for maximum profitability. With reliable forecasts, businesses have greater visibility into potential issues that may arise regarding meeting customer demands and keeping up with changing industry trends. With this insight, they can proactively address any issues before a new product launch.

Methods of Forecasting a New Product

Accurately anticipating the demand for a product can give companies an edge over their competitors in the market. Various forecasting models can be used to forecast product demand, such as qualitative forecasting, quantitative forecasting, time-series analysis, and sales volume estimation.

Qualitative Forecasting

Qualitative forecasting involves using subjective judgments from experts or stakeholders to develop product forecasts. This method usually requires market research using interviews, surveys, focus groups, and other similar activities. It is particularly effective when limited data is available about an unfamiliar product or industry.

Quantitative Forecasting

Quantitative forecasting utilizes mathematical models to make predictions based on historical data, such as sales information and customer feedback. This type of forecasting is typically used to predict future trends in product demand by looking at past performance patterns. 

Time-Series Analysis

Time-series analysis is another type of quantitative forecasting that utilizes statistical techniques to evaluate relationships between variables over time and predict product sales based on these findings. Time-series analysis considers changes in product features and external conditions, such as economic developments and consumer preferences, so that more accurate forecasts can be made.

Sales Volume Estimation

Sales volume estimation is another popular method used for product forecasting. This technique estimates the number of units sold in a given period based on factors like manufacturer’s price discounts and promotions and market influences like competition and consumer behavior shifts. Sales volume estimates are essential for pricing strategies and inventory management plans for specific products or product lines.

Utilizing these methods for product forecasting can help businesses make better decisions regarding product development, marketing strategies, inventory management, pricing strategies, and more—allowing them to maximize their profits while meeting customer needs effectively.

Product Forecasting Challenges

Businesses face various challenges when forecasting demand for a new product. This can be especially difficult due to the lack of consumer data and the uncertainty around market acceptance.

Consumer Behavior

One of the most pressing issues is predicting consumer behavior. To forecast product demand, businesses must understand how their product fits into the larger market and how consumers will react to it. They need to have data on what features are attractive, which ones are not, and any potential substitutes that could replace their product in the market. This information can be hard to come by when launching a product for the first time, as there is no established record of consumer response or past sales analysis to draw on.

Estimating Product Life Cycles

Another challenge businesses face is estimating product life cycles. Designing a product with a long life cycle requires careful consideration of its components and production costs relative to its worth in the marketplace over time. Companies must anticipate changes in technology and economic conditions that may affect how well their product performs and consider any external factors, such as competitive pressures and government regulations, that may influence product performance or desirability.

Market Disruptions

Accounting for potential disruptions in the market is also difficult when forecasting new product demand. With ever-changing consumer preferences and technologies driving rapid transformation in many industries, businesses must be agile and adjust their forecasts accordingly. This can be especially tricky for products whose life cycles are short or evolving quickly due to technological changes or market saturation. Therefore, companies must constantly monitor these trends to ensure their product forecasts remain accurate.

Finally, pricing plays a vital role in new product forecasting. Factors such as production costs and competitive pricing must be considered when setting prices for a product. Pricing too high may scare off potential customers, while pricing too low may result in lower profit margins than expected. Therefore, businesses must find the optimal balance between price and profitability to maximize profits while still meeting customer needs and expectations effectively.

People Also Ask

How do you create a product forecast.

Creating an accurate product forecast is an essential part of product planning. It helps businesses to anticipate customer demand and develop strategies to meet their expectations. Product forecasting involves predicting the quantity of products customers will likely buy in a given period. The first step in product forecasting is to identify customer needs and preferences. Companies need to understand the product’s target market, including the demographic characteristics of its users, as well as their interests and buying habits. Businesses can use surveys, focus groups, interviews, or other data collection methods to gather information about customer segments. Once they have identified customer preferences, companies can estimate how much product will be needed based on historical sales patterns or market trends. The next step is to create a comprehensive forecast model that considers both external factors – such as economic conditions and competitive product launches – and internal factors – such as marketing campaigns or product launch dates. The model should also include historical sales data for past periods and projections for future periods to be used for both short-term and long-term product planning. Once the model has been created, it should be tested and validated regularly to ensure accuracy. Companies should also track changes in customer preferences over time to update their forecasts accordingly. By creating an accurate product forecast and keeping it up-to-date, businesses can more effectively plan for their product launches and anticipate customer demand.

Why is product forecasting important?

Product forecasting is an important part of product management , and it’s used to help companies plan for the future. It helps them anticipate demand for new products or predict which product features will be popular in the marketplace. It also helps companies forecast the resources needed to produce a product. Accurately forecasting product demand is essential for businesses to make sound decisions about product development, production, and inventory planning. Accurate product forecasting is essential for meeting customer needs and maximizing sales opportunities. Companies must have accurate projections of product demand to properly allocate resources and design marketing plans that tap into customer preferences. By anticipating product needs, businesses can better manage inventory levels and reduce backorders while minimizing costs associated with excess stock or lost sales due to insufficient inventory levels. Product forecasting also helps companies accurately estimate the cost of production, distribution, and customer service support by considering the cost associated with supply chain disruptions due to product shortages or delays in shipment arrivals. By better understanding customer needs, a company can plan and implement solutions to address potential problems before they occur.

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How To Create Financial Projections for Your Business Plan

Building a financial projection as you write out your business plan can help you forecast how much money your business will bring in.

Planning for the future, whether it’s with growth in mind or just staying the course, is central to being a business owner. Part of this planning effort is making financial projections of sales, expenses, and—if all goes well—profits.

Even if your business is a startup that has yet to open its doors, you can still make projections. Here’s how to prepare your business plan financial projections, so your company will thrive.

What are business plan financial projections?

Business plan financial projections are a company’s estimates, or forecasts, of its financial performance at some point in the future. For existing businesses, draw on historical data to detail how your company expects metrics like revenue, expenses, profit, and cash flow to change over time.

Companies can create financial projections for any span of time, but typically they’re for between one and five years. Many companies revisit and amend these projections at least annually. 

Creating financial projections is an important part of building a business plan . That’s because realistic estimates help company leaders set business goals, execute financial decisions, manage cash flow , identify areas for operational improvement, seek funding from investors, and more.

What are financial projections used for? 

Financial forecasting serves as a useful tool for key stakeholders, both within and outside of the business. They often are used for:

Business planning

Accurate financial projections can help a company establish growth targets and other goals . They’re also used to determine whether ideas like a new product line are financially feasible. Future financial estimates are helpful tools for business contingency planning, which involves considering the monetary impact of adverse events and worst-case scenarios. They also provide a benchmark: If revenue is falling short of projections, for example, the company may need changes to keep business operations on track.

Projections may reveal potential problems—say, unexpected operating expenses that exceed cash inflows. A negative cash flow projection may suggest the business needs to secure funding through outside investments or bank loans, increase sales, improve margins, or cut costs.

When potential investors consider putting their money into a venture, they want a return on that investment. Business projections are a key tool they will use to make that decision. The projections can figure in establishing the valuation of your business, equity stakes, plans for an exit, and more. Investors may also use your projections to ensure that the business is meeting goals and benchmarks.

Loans or lines of credit 

Lenders rely on financial projections to determine whether to extend a business loan to your company. They’ll want to see historical financial data like cash flow statements, your balance sheet , and other financial statements—but they’ll also look very closely at your multi-year financial projections. Good candidates can receive higher loan amounts with lower interest rates or more flexible payment plans.

Lenders may also use the estimated value of company assets to determine the collateral to secure the loan. Like investors, lenders typically refer to your projections over time to monitor progress and financial health.

What information is included in financial projections for a business?

Before sitting down to create projections, you’ll need to collect some data. Owners of an existing business can leverage three financial statements they likely already have: a balance sheet, an annual income statement , and a cash flow statement .

A new business, however, won’t have this historical data. So market research is crucial: Review competitors’ pricing strategies, scour research reports and market analysis , and scrutinize any other publicly available data that can help inform your projections. Beginning with conservative estimates and simple calculations can help you get started, and you can always add to the projections over time.

One business’s financial projections may be more detailed than another’s, but the forecasts typically rely on and include the following:

True to its name, a cash flow statement shows the money coming into and going out of the business over time: cash outflows and inflows. Cash flows fall into three main categories:

Income statement

Projected income statements, also known as projected profit and loss statements (P&Ls), forecast the company’s revenue and expenses for a given period.

Generally, this is a table with several line items for each category. Sales projections can include the sales forecast for each individual product or service (many companies break this down by month). Expenses are a similar setup: List your expected costs by category, including recurring expenses such as salaries and rent, as well as variable expenses for raw materials and transportation.

This exercise will also provide you with a net income projection, which is the difference between your revenue and expenses, including any taxes or interest payments. That number is a forecast of your profit or loss, hence why this document is often called a P&L.

Balance sheet

A balance sheet shows a snapshot of your company’s financial position at a specific point in time. Three important elements are included as balance sheet items:

• Assets. Assets are any tangible item of value that the company currently has on hand or will in the future, like cash, inventory, equipment, and accounts receivable. Intangible assets include copyrights, trademarks, patents and other intellectual property .
• Liabilities. Liabilities are anything that the company owes, including taxes, wages, accounts payable, dividends, and unearned revenue, such as customer payments for goods you haven’t yet delivered.
• Shareholder equity. The shareholder equity figure is derived by subtracting total liabilities from total assets. It reflects how much money, or capital, the company would have left over if the business paid all its liabilities at once or liquidated (this figure can be a negative number if liabilities exceed assets). Equity in business is the amount of capital that the owners and any other shareholders have tied up in the company.

They’re called balance sheets because assets always equal liabilities plus shareholder equity. 

5 steps for creating financial projections for your business

• Identify the purpose and timeframe for your projections
• Collect relevant historical financial data and market analysis
• Forecast expenses
• Forecast sales
• Build financial projections

The following five steps can help you break down the process of developing financial projections for your company:

1. Identify the purpose and timeframe for your projections

The details of your projections may vary depending on their purpose. Are they for internal planning, pitching investors, or monitoring performance over time? Setting the time frame—monthly, quarterly, annually, or multi-year—will also inform the rest of the steps.

2. Collect relevant historical financial data and market analysis

If available, gather historical financial statements, including balance sheets, cash flow statements, and annual income statements. New companies without this historical data may have to rely on market research, analyst reports, and industry benchmarks—all things that established companies also should use to support their assumptions.

3. Forecast expenses

Identify future spending based on direct costs of producing your goods and services ( cost of goods sold, or COGS) as well as operating expenses, including any recurring and one-time costs. Factor in expected changes in expenses, because this can evolve based on business growth, time in the market, and the launch of new products.

4. Forecast sales

Project sales for each revenue stream, broken down by month. These projections may be based on historical data or market research, and they should account for anticipated or likely changes in market demand and pricing.

5. Build financial projections

Now that you have projected expenses and revenue, you can plug that information into Shopify’s cash flow calculator and cash flow statement template . This information can also be used to forecast your income statement. In turn, these steps inform your calculations on the balance sheet, on which you’ll also account for any assets and liabilities .

Business plan financial projections FAQ

What are the main components of a financial projection in a business plan.

Generally speaking, most financial forecasts include projections for income, balance sheet, and cash flow.

What’s the difference between financial projection and financial forecast?

These two terms are often used interchangeably. Depending on the context, a financial forecast may refer to a more formal and detailed document—one that might include analysis and context for several financial metrics in a more complex financial model.

Do I need accounting or planning software for financial projections?

Not necessarily. Depending on factors like the age and size of your business, you may be able to prepare financial projections using a simple spreadsheet program. Large complicated businesses, however, usually use accounting software and other types of advanced data-management systems.

What are some limitations of financial projections?

Projections are by nature based on human assumptions and, of course, humans can’t truly predict the future—even with the aid of computers and software programs. Financial projections are, at best, estimates based on the information available at the time—not ironclad guarantees of future performance.

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How To Get An Accurate Sales Forecast With Demand Forecasting

By QuotaPath Team | August, 2024 | 9 mins

Sales forecasting is one of the most essential yet challenging aspects of business. However, having an accurate estimate of revenue through a sales forecast can shape your success.

Everything from developing budgets to planning production capacity relies on this forecast. That’s why accurate insights are crucial. 

The solution? Demand forecasting. Here, we’ll explore why this process is so beneficial and strategies to implement.

What is demand forecasting and why is it important?

Demand forecasting is the process of estimating future sales of your products or services by using relevant data to predict demand. The aim is to remove the guesswork by gaining a more accurate view of predicted revenue streams to help better manage budgets and sales cycles .

Why is this important? One aspect is streamlining. Accurate forecasts allow you to anticipate fluctuations in demand to better allocate resources. Determining stock levels helps avoid understocking inventory or product obsolescence. It’s also beneficial for avoiding lost sales opportunities. 

All of this has a knock-on effect on operational efficiency and, consequently, brand awareness . It ensures you’re always able to meet customer demand. This, in turn, can increase your company’s profitability, protect your brand reputation, and ensure steady business growth. 

Key benefits of accurate demand forecasting

As we mentioned, demand forecasting offers numerous benefits, from resource allocation to sales opportunities. Let’s dive into these in more detail.

Inventory management

Demand forecasting in supply chain and inventory management is essential for maintaining optimal stock levels throughout the year. 

Rather than guessing what you need and when, you can use forecasts to reduce the potential of stockouts, improve ordering efficiency, optimize revenue management, and save on the cost of storage. By ensuring a healthy fill rate , you can meet customer demand consistently while minimizing the risk of understocking or overstocking inventory. You could even save on transport costs by spotting ways to consolidate orders.

Resource allocation

Anticipating demand equips you with the knowledge to better plan and allocate resources. Whether it’s production capacity, manpower, or marketing budgets, you can approach allocation strategically to be more effective during times of high demand and scale back during quieter periods.

Budgeting and planning

Demand forecasting gives you some of the best insights to plan budgets. This can help you decide how much to spend on areas like marketing, hiring, or product development, depending on what resources you will need and how much revenue you anticipate coming in.

Utilizing budgeting software can streamline this process further by automating data analysis and providing real-time insights into budget allocation. With budgeting software, you can efficiently track expenses, identify areas for cost-saving, and make informed decisions to maximize your resources and optimize financial performance.

You may even be able to spot investment opportunities. Automation is becoming increasingly prevalent in businesses today, so you may free up the budget for click to call dialer software to support your sales team’s outreach efforts or customer service chatbots to improve conversion rates.

Risk management

Demand forecasting helps identify potential risks and uncertainties related to sales performance. This way, you can be better prepared to manage challenges.

For example, if your demand forecast indicates a potential downturn in sales during a specific season, you can adjust inventory levels or implement targeted email marketing campaigns to give sales a boost.

Improved decision-making

Any forecasting model replaces guesswork with reliable information specific to your business and customers. With that information, you can make more informed decisions about future sales trends. 

For example, if your forecast indicates a surge in demand for a particular product, you can adjust your pricing strategies. This could mean offering promotions or increasing sales incentives during peak demand periods to capitalize on increased customer interest.

Understanding cross-channel demand patterns, particularly in the context of omnichannel ecommerce , becomes crucial for effectively allocating resources and maximizing sales across multiple sales channels. 

5 steps for effective demand forecasting

While demand forecasting can benefit your company, it’s important to do it correctly if your strategy is to be successful. We’ve broken it down into five easy steps.

1. Collect data relevant to your goals

Begin by collecting and analyzing relevant data available that aligns with your sales and business growth goals. This information could include any or all of the following: 

• Historical data: Past sales data can tell you a lot about what might happen in the future. Pull data from sources like your CRM, inventory management software, call center reporting tools , customer forms, and even other departments. Review previous demand, looking out for patterns, trends, and seasonal fluctuations that are likely to repeat. 
• Market research: Gather information about your target customers, including their preferences, buying habits, and what influences their purchasing decisions. This could be done through surveys, interviews, or analyzing existing market studies. 
• External factors: Industry trends and competitor activities can impact your forecast. But it’s also worth gathering data on economic conditions and socio-political factors like regulation changes or consumer sentiment. For example, a new competitor entering the market might affect demand for your products, or a change in government policy might influence consumer buying behavior.

2. Implement your chosen forecasting methods

Once you have the data, you must analyze it to draw conclusions. You can do this manually or with the help of automation. Let’s explore a few options.

Statistical models

Statistical techniques like time series analysis and regression analysis are useful for creating forecasting models. 

Time series analysis looks at patterns in historical data over time, such as increases or decreases in sales during certain months. 

Regression analysis identifies relationships between variables. It considers how factors like marketing spend, promotions, and economic conditions have impacted sales.

Conducting an in-depth analysis of large data sets manually can be challenging. However, machine learning algorithms make this process more efficient and can help identify complex patterns, resulting in more accurate predictions.

Forecasting software

As with many business processes, software can make forecasting much smoother. If you choose the right model, it can help to automate data collection and analysis and generate reports for you.

But it’s crucial to choose the right solution for your business needs. You should also understand how that solution creates the forecasts so you can make better decisions. 

Remember that your existing software such as your ERP system may have built-in forecasting capabilities. Or you may need a customized program for your specific industry. 

Collaborative forecasting

Technology isn’t always the answer. Bring together different departments to share insights and perspectives to help shape your forecast. 

For example, a software company launching call scri pt software might get input from their sales team on customer demand and predicted sales. The marketing team would provide campaign insights, while the finance department could offer financial projections.

3. Segment your market

Market segmentation can refine your sales forecast by accounting for demand drivers and behavior variations across different segments. 

After segmenting your audience or products, you can develop separate forecasts for each category. This allows you to account for demand drivers and behavior variations across different segments. 

Here are two ways you might segment your market.

Customer segmentation

Narrow your wider target market into smaller groups based on different characteristics that influence purchasing patterns. This could be:

• Demographics: Age, gender, income
• Psychographics Lifestyle, values, interests
• Geographic location
• Buying behavior

Product segmentation

Categorize your products based on their attributes, such as price, functionality, and lifecycle stage. This helps you tailor your forecasting approach to the different characteristics of each product category.

You might forecast higher-priced products differently from budget items or adjust forecasts based on a product’s lifecycle (e.g., introduction, growth, maturity, decline).

4. Monitor sales performance and make adjustments

Tracking sales performance is crucial to improving the accuracy of your forecast. This allows you to make changes when needed and stay responsive to changing market dynamics.

Keep an eye on key performance indicators (KPIs), sales metrics, and market trends. How do they compare with your forecasted values? If your actual sales drop below what you forecasted, it could be a sign that you need to adjust your strategy or allocate resources differently to adapt to changing market conditions.

Remember that while it’s great to have a demand forecast in place, there are some things you can’t predict. So, it’s essential to remain agile in response to new information or unexpected events that may impact demand. 

It’s likely that you will need to revise forecasts, reallocate resources, or adjust marketing strategies along the way. For example, a competitor launching a similar product could unexpectedly reduce your demand, meaning you need to consider scaling back production.

As part of this step, establish a feedback mechanism. Gather regular insights from frontline employees, customers, and partners about their experiences and perceptions. Their feedback can provide valuable information about changing customer preferences, market trends, or other factors that may influence demand.

5. Review and repeat

After making forecasts, it’s essential to compare them with actual sales data to identify discrepancies and understand their root causes. You may need to change your data collection tactics or forecasting methods in the future.

Forecasting isn’t a job you can do at the start of the financial year and forget about. It’s an ongoing process that needs continuous refinement. Regularly review and refine your forecasting models based on stakeholder feedback, performance metrics, and learnings from past forecasting experiences.

Consider building a scenario analysis into your forecasting process, too. This involves preparing for the potential impact of various scenarios or events on your sales forecast. For example, you might consider what would happen if there’s a recession, if you launch a new product, or if a competitor starts a price war. 

Imagining these scenarios and their potential effects on sales helps you better prepare and make plans to respond effectively.

Demand forecasting: Unlock powerful insights to drive sales

While we can’t see into the future, demand forecasting could be as close to a crystal ball as it gets. 

Accurate sales forecasts help businesses make more informed decisions and plan strategically. The ability to anticipate future demand means you can make the right adjustments to everything from stock levels and manpower to meet customer needs. 

This not only contributes to a more efficient business model but also reduces inefficiencies and reduces costs, leading to a more profitable business and satisfied customers.

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The 10 steps of demand forecasting for new products

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Follow these best practices for more accurate demand forecasting and more cost-efficient product launches.

Demand forecasting for new variants of existing products is difficult enough. But forecasting for radically innovative products in emerging new categories is an entirely different ball game. There are no past trends to reassuringly extrapolate into the future, just a ton of uncertainty about whether the latent demand that marketing suggested to secure the R&D funding is real or not.

And after so much investment, the board is convinced this is the product that is going to become the next cash cow. Sure, you could manage their expectations by reminding them that something like 80% of new products fail and name-drop a few of the spectacular flops of Fortune 500 companies. But that would be career limiting. A better alternative is to take control of the situation by following these 10 steps of demand forecasting best practices that have a proven track record of success.

Want to enhance your company’s product demand forecast? Check out this playbook, featuring specific guidance for the life sciences industry.

Step 1: Make it a collaborative effort

Identify a handful of key people from marketing, sales, operations, and relevant technical departments and form a working group. This core team will be responsible for developing and managing the reforecasting process through the launch period until  demand planning  becomes more predictable.

Step 2: Identify and agree upon the assumptions

Collectively review all the available qualitative and quantitative data from market research, market testing, and buyer surveys. Use the data to identify a set of assumptions that can form the basis of a demand forecasting model.

Ideally this will include assumptions about:

• Number of consumers in the target market
• Proportion expected to buy the product
• Anticipated timing of their purchase
• Patterns of repeat purchasing and replacement purchasing

Be prepared to commission additional research or consult external industry experts to fill any important data gaps. And always let the working group use their collective judgment to identify a realistic range of values for each assumption.

Step 3: Build granular models

Not all consumers will purchase a new product at the same rate. Some may be prepared to queue all night around the block to get their hands on it, but others will want to wait for subsequent versions when any unforeseen bugs are fixed and prices are typically lower. Build a sufficiently granular forecasting model reflect how and when different market segments in different geographies might purchase the product and at what price.

Step 4: Use flexible time periods

Sales over the first few days and weeks in the life of any new product need to be carefully monitored as they will quickly show how demand is likely to grow in the future. Although the sales and finance function may only be interested in monthly data, it pays to develop detailed daily forecasts for the first quarter against which to track actual sales.

Step 5: Generate a range of forecasts

Run through a number of iterations, changing various assumptions and probabilities in the model to generate a range of  forecasts . This is easily done if a modelling solution that can be recalculated in real-time is deployed as internal experts and business leaders can generate and test alternative scenarios on the fly.

Step 6: Deliver the outputs that users need quickly

In  new product launch planning , agreements may have been reached with a number of suppliers to deliver rapid replenishment designed to prevent stock outs in the most uncertain period immediately after the launch. However, if reforecasting the exact replenishment needs of every distribution point in the supply chain involves multiple steps, much of that precious time will evaporate.

Building a fully integrated demand forecasting model that compares existing stock levels and automatically generates a detailed replenishment report for every location as soon as any high-level assumptions change precludes such delays and shortens the replenishment cycle.

Step 7: Combine different techniques

Bottom-up modelling based on purchasing intentions is not the only method available for demand forecasting for new products. In some markets, such as technology and consumer electronics, products can go through an entire life cycle in a matter of months. Such narrow windows of opportunity make it vitally important to assess demand as accurately as possible. The most damaging situation is having a stock shortage while the product is still hot, leading disappointed consumers to purchase a competitor’s product.

These sectors make use of sophisticated modelling techniques developed by academics that use substitution and diffusion rates to forecast how rapidly new technologies replace older ones. Such methodologies might not be appropriate to many businesses, but the message is the same: combining different forecasting techniques gives more accurate results.

Step 8: Reality check the forecast

Whenever reliable data exists, always check the forecast against the sales evolution of comparable products to see if it is realistic. Similarly, you should also estimate how your market share might evolve as new competitors came into this emerging category and how the total market might grow. Unless this macro-overview is credible, be prepared to rework the assumptions behind the model.

Step 9: Reforecast, reforecast, and reforecast some more

Diligently monitor sales and qualitative feedback such as product reviews, media mentions, and customer feedback, and agree with the members of the working group how the assumptions in the model might need to change. If it’s appropriate, reforecast daily.

Step 10: Be prepared to cut your losses

Finally, always have a contingency plan. A high proportion of new products fail, and it is better to pull the plug on an ailing new product that is unlikely to achieve a viable level of profitability at the earliest opportunity. So, quantify and agree what level of sales penetration constitutes failure well before the product launch. That way, the decision will be swift, and the existing stock can be quickly and cost-efficiently depleted.

Demand forecasting for new products is not an exact science and relies on judgement rather than statistical techniques. Key to success is collaboration, using all the quantitative and qualitative data that is available and having a modelling solution that can quickly and easily be updated to generate detailed forecasts for all users across the business. The benefits can be impressive both in terms of reduced inventory costs and improved customer satisfaction, something that is vital for a new product to flourish.

Watch our demo to see how Anaplan helps with demand forecasting by enabling advanced decision-making in every part of your business

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Run » finance, how to create a financial forecast for a startup business plan.

Financial forecasting allows you to measure the progress of your new business by benchmarking performance against anticipated sales and costs.

When starting a new business, a financial forecast is an important tool for recruiting investors as well as for budgeting for your first months of operating. A financial forecast is used to predict the cash flow necessary to operate the company day-to-day and cover financial liabilities.

Many lenders and investors ask for a financial forecast as part of a business plan; however, with no sales under your belt, it can be tricky to estimate how much money you will need to cover your expenses. Here’s how to begin creating a financial forecast for a new business.

[Read more: Startup 2021: Business Plan Financials ]

Start with a sales forecast

A sales forecast attempts to predict what your monthly sales will be for up to 18 months after launching your business. Creating a sales forecast without any past results is a little difficult. In this case, many entrepreneurs make their predictions using industry trends, market analysis demonstrating the population of potential customers and consumer trends. A sales forecast shows investors and lenders that you have a solid understanding of your target market and a clear vision of who will buy your product or service.

A sales forecast typically breaks down monthly sales by unit and price point. Beyond year two of being in business, the sales forecast can be shown quarterly, instead of monthly. Most financial lenders and investors like to see a three-year sales forecast as part of your startup business plan.

Lower fixed costs mean less risk, which might be theoretical in business schools but are very concrete when you have rent and payroll checks to sign.

Tim Berry, president and founder of Palo Alto Software

Create an expenses budget

An expenses budget forecasts how much you anticipate spending during the first years of operating. This includes both your overhead costs and operating expenses — any financial spending that you anticipate during the course of running your business.

Most experts recommend breaking down your expenses forecast by fixed and variable costs. Fixed costs are things such as rent and payroll, while variable costs change depending on demand and sales — advertising and promotional expenses, for instance. Breaking down costs into these two categories can help you better budget and improve your profitability.

"Lower fixed costs mean less risk, which might be theoretical in business schools but are very concrete when you have rent and payroll checks to sign," Tim Berry, president and founder of Palo Alto Software, told Inc . "Most of your variable costs are in those direct costs that belong in your sales forecast, but there are also some variable expenses, like ads and rebates and such."

Project your break-even point

Together, your expenses budget and sales forecast paints a picture of your profitability. Your break-even projection is the date at which you believe your business will become profitable — when more money is earned than spent. Very few businesses are profitable overnight or even in their first year. Most businesses take two to three years to be profitable, but others take far longer: Tesla , for instance, took 18 years to see its first full-year profit.

Lenders and investors will be interested in your break-even point as a projection of when they can begin to recoup their investment. Likewise, your CFO or operations manager can make better decisions after measuring the company’s results against its forecasts.

[Read more: ​​ Startup 2021: Writing a Business Plan? Here’s How to Do It, Step by Step ]

Develop a cash flow projection

A cash flow statement (or projection, for a new business) shows the flow of dollars moving in and out of the business. This is based on the sales forecast, your balance sheet and other assumptions you’ve used to create your expenses projection.

“If you are starting a new business and do not have these historical financial statements, you start by projecting a cash-flow statement broken down into 12 months,” wrote Inc . The cash flow statement will include projected cash flows from operating, investing and financing your business activities.

Keep in mind that most business plans involve developing specific financial documents: income statements, pro formas and a balance sheet, for instance. These documents may be required by investors or lenders; financial projections can help inform the development of those statements and guide your business as it grows.

CO— aims to bring you inspiration from leading respected experts. However, before making any business decision, you should consult a professional who can advise you based on your individual situation.

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7 Financial Forecasting Methods to Predict Business Performance

• 21 Jun 2022

Much of accounting involves evaluating past performance. Financial results demonstrate business success to both shareholders and the public. Planning and preparing for the future, however, is just as important.

Shareholders must be reassured that a business has been, and will continue to be, successful. This requires financial forecasting.

Here's an overview of how to use pro forma statements to conduct financial forecasting, along with seven methods you can leverage to predict a business's future performance.

Access your free e-book today.

What Is Financial Forecasting?

Financial forecasting is predicting a company’s financial future by examining historical performance data, such as revenue, cash flow, expenses, or sales. This involves guesswork and assumptions, as many unforeseen factors can influence business performance.

Financial forecasting is important because it informs business decision-making regarding hiring, budgeting, predicting revenue, and strategic planning . It also helps you maintain a forward-focused mindset.

Each financial forecast plays a major role in determining how much attention is given to individual expense items. For example, if you forecast high-level trends for general planning purposes, you can rely more on broad assumptions than specific details. However, if your forecast is concerned with a business’s future, such as a pending merger or acquisition, it's important to be thorough and detailed.

Forecasting with Pro Forma Statements

A common type of forecasting in financial accounting involves using pro forma statements . Pro forma statements focus on a business's future reports, which are highly dependent on assumptions made during preparation⁠, such as expected market conditions.

Because the term "pro forma" refers to projections or forecasts, pro forma statements apply to any financial document, including:

• Income statements
• Balance sheets
• Cash flow statements

These statements serve both internal and external purposes. Internally, you can use them for strategic planning. Identifying future revenues and expenses can greatly impact business decisions related to hiring and budgeting. Pro forma statements can also inform endeavors by creating multiple statements and interchanging variables to conduct side-by-side comparisons of potential outcomes.

Externally, pro forma statements can demonstrate the risk of investing in a business. While this is an effective form of forecasting, investors should know that pro forma statements don't typically comply with generally accepted accounting principles (GAAP) . This is because pro forma statements don't include one-time expenses—such as equipment purchases or company relocations—which allows for greater accuracy because those expenses don't reflect a company’s ongoing operations.

7 Financial Forecasting Methods

Pro forma statements are incredibly valuable when forecasting revenue, expenses, and sales. These findings are often further supported by one of seven financial forecasting methods that determine future income and growth rates.

There are two primary categories of forecasting: quantitative and qualitative.

Quantitative Methods

When producing accurate forecasts, business leaders typically turn to quantitative forecasts , or assumptions about the future based on historical data.

1. Percent of Sales

Internal pro forma statements are often created using percent of sales forecasting . This method calculates future metrics of financial line items as a percentage of sales. For example, the cost of goods sold is likely to increase proportionally with sales; therefore, it’s logical to apply the same growth rate estimate to each.

To forecast the percent of sales, examine the percentage of each account’s historical profits related to sales. To calculate this, divide each account by its sales, assuming the numbers will remain steady. For example, if the cost of goods sold has historically been 30 percent of sales, assume that trend will continue.

2. Straight Line

The straight-line method assumes a company's historical growth rate will remain constant. Forecasting future revenue involves multiplying a company’s previous year's revenue by its growth rate. For example, if the previous year's growth rate was 12 percent, straight-line forecasting assumes it'll continue to grow by 12 percent next year.

Although straight-line forecasting is an excellent starting point, it doesn't account for market fluctuations or supply chain issues.

3. Moving Average

Moving average involves taking the average—or weighted average—of previous periods⁠ to forecast the future. This method involves more closely examining a business’s high or low demands, so it’s often beneficial for short-term forecasting. For example, you can use it to forecast next month’s sales by averaging the previous quarter.

Moving average forecasting can help estimate several metrics. While it’s most commonly applied to future stock prices, it’s also used to estimate future revenue.

To calculate a moving average, use the following formula:

A1 + A2 + A3 … / N

Formula breakdown:

A = Average for a period

N = Total number of periods

Using weighted averages to emphasize recent periods can increase the accuracy of moving average forecasts.

4. Simple Linear Regression

Simple linear regression forecasts metrics based on a relationship between two variables⁠: dependent and independent. The dependent variable represents the forecasted amount, while the independent variable is the factor that influences the dependent variable.

The equation for simple linear regression is:

Y ⁠ = Dependent variable⁠ (the forecasted number)

B = Regression line's slope

X = Independent variable

A = Y-intercept

5. Multiple Linear Regression

If two or more variables directly impact a company's performance, business leaders might turn to multiple linear regression . This allows for a more accurate forecast, as it accounts for several variables that ultimately influence performance.

To forecast using multiple linear regression, a linear relationship must exist between the dependent and independent variables. Additionally, the independent variables can’t be so closely correlated that it’s impossible to tell which impacts the dependent variable.

Qualitative Methods

When it comes to forecasting, numbers don't always tell the whole story. There are additional factors that influence performance and can't be quantified. Qualitative forecasting relies on experts’ knowledge and experience to predict performance rather than historical numerical data.

These forecasting methods are often called into question, as they're more subjective than quantitative methods. Yet, they can provide valuable insight into forecasts and account for factors that can’t be predicted using historical data.

6. Delphi Method

The Delphi method of forecasting involves consulting experts who analyze market conditions to predict a company's performance.

A facilitator reaches out to those experts with questionnaires, requesting forecasts of business performance based on their experience and knowledge. The facilitator then compiles their analyses and sends them to other experts for comments. The goal is to continue circulating them until a consensus is reached.

7. Market Research

Market research is essential for organizational planning. It helps business leaders obtain a holistic market view based on competition, fluctuating conditions, and consumer patterns. It’s also critical for startups when historical data isn’t available. New businesses can benefit from financial forecasting because it’s essential for recruiting investors and budgeting during the first few months of operation.

When conducting market research, begin with a hypothesis and determine what methods are needed. Sending out consumer surveys is an excellent way to better understand consumer behavior when you don’t have numerical data to inform decisions.

Improve Your Forecasting Skills

Financial forecasting is never a guarantee, but it’s critical for decision-making. Regardless of your business’s industry or stage, it’s important to maintain a forward-thinking mindset—learning from past patterns is an excellent way to plan for the future.

If you’re interested in further exploring financial forecasting and its role in business, consider taking an online course, such as Financial Accounting , to discover how to use it alongside other financial tools to shape your business.

Do you want to take your financial accounting skills to the next level? Consider enrolling in Financial Accounting —one of three courses comprising our Credential of Readiness (CORe) program —to learn how to use financial principles to inform business decisions. Not sure which course is right for you? Download our free flowchart .

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What are the key elements to include in a business development plan PowerPoint presentation?

June 4, 2024 /

The key elements to include in a business development plan PowerPoint presentation are:

• A clear and concise executive summary
• An overview of your company’s mission and goals
• A thorough market analysis
• A detailed description of your products or services
• A comprehensive competitive analysis
• A strategic marketing plan
• A financial forecast
• A compelling conclusion

By incorporating these elements into your presentation, you can effectively communicate your business development plan to potential investors, partners, or stakeholders.

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Amazon just gave a bleak sign about the economy

• Amazon says that deal-seeking shoppers dented its sales.
• Next quarter might be rough, too. The Olympics and the US election might distract people, it says.
• Amazon is presenting a bleak picture of the economy as rising prices batter American wallets.

Amazon said deal-hungry shoppers dented sales in the second quarter, presenting a bleak picture of the economy as prices continue to batter American wallets.

Amazon missed sales estimates Thursday, and the retail giant said it anticipated softening consumer demand in the third quarter — which sent shares falling in after-hours trading.

On a call with reporters, Amazon CFO Brian Olsavsky said shoppers were "cautious" and "looking for deals" — trading down to lower-priced items whenever possible.

That helped boost Amazon's lower-priced Everyday Essentials category, which includes non-perishable foods, health, and personal care items. But those lower-priced items weighed on sales.

And while Amazon CEO Andy Jassy said that "more discretionary, higher-ticket items," like computers and other electronics, were "growing fast" for the company, he still sounded a note of caution.

Those categories are growing "more slowly than we see in a more robust economy," he warned.

Distractions like the Olympics and the US elections could also weigh

Looking ahead, Olsavsky said the third quarter would be difficult to accurately forecast because shoppers are likely to be preoccupied by major world events like the US presidential campaign and the Olympics.

"We do see different traffic patterns during those events," Olsavsky said.

At the same time, he noted that Prime Day in July — Amazon's 10th — was its "largest ever."

Prime Day deals could present some headwinds to operating profits, he said. And cautious consumers could dent sales, the company said.

Related stories

Amazon isn't alone in flagging shopper fatigue with rising prices.

Shoppers are showing elsewhere that they're sick of price increases — leading retailers to say that they're offering deals to try to entice people back .

American pocketbooks have been battered by rising prices , with certain items getting even more expensive even as inflation gradually cools.

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