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What Is Sales Forecasting: Definition, Methods and Examples

Written by:

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

Edited by:

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

What Is Sales Forecasting: Definition, Methods and Examples

What Is Sales Forecasting: Definition, Methods and Examples

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

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

Key Takeaways

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

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

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

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

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

Definition and Benefits of Sales Forecasting

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

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

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

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

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

1. Resource Management

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

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

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

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

2. Financial Planning

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

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

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

3. Communicate With Investors

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

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

4. Optimize Prospecting

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

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

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

Sales Forecasting Methods

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

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

1. Bottom-Up Sales Forecasting

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

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

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

2. Top-Down Sales Forecasting

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

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

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

Length of Cycle Sales Forecasting

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

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

Historical Forecasting

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

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

Opportunity Stage Forecasting

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

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

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

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


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

3. Multivariable Forecasting

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

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

7 Steps of the Sales Forecasting Process

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

1. Standardize Your Sales Process

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

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

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

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

2. Set Sales Targets

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

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

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

3. Select a Forecasting Method

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

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

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

4. Analyze Your Current Sales Pipeline

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

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

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

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

5. Adjust For Internal Factors

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

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

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

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

6. Adjust for External Factors

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

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

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

7. Share With Team Members

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

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

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

Common Sales Forecasting Challenges

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

1. Data Accuracy

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

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

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

2. Unpredictable Disasters

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

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

3. Seasonality

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

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

4. Not Enough Forecasts

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

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


What are some software tools that can help me with sales forecasting?

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

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

What are some best practices for better sales forecasting?

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

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

What do I need for accurate sales forecasting?

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

Who uses sales forecasting?

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