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

Alicia Raeburn contributor headshotAlicia Raeburn
January 2nd, 2024
12 min read
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Summary

A sales forecast predicts future sales revenue using past business data. You can use sales forecasting to assess your financial projections and change your business plan if necessary. Learn how a sales forecast template can help you set goals, budget, and refine your sales cycle.

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.

A sales forecast projects future business revenue based on historical data. You can use sales forecasting to preview your financial projections. Based on how promising those projections are, you can make tweaks and adjustments to your business plan if necessary. In this article, we cover how to create a sales forecast template, which you can use to improve future performance.

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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.

[inline illustration] the importance of sales forecasting (infographic)

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.

  • Aligns merchandising efforts: Sales forecasting can help you adjust your retail merchandising strategy by anticipating demand and ensuring the right products are featured at the right time.

  • 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. Leveraging inventory management software can help you implement these adjustments more effectively by providing up-to-date data on stock levels and supply chain performance.

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:

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.

Free sales pipeline template

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. 

[inline illustration] 5 steps to make a sales forecast template (infographic)

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.

Read: Sales and operations planning (S&OP): A project manager’s guide

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.

Free sales pipeline template

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.

Free sales pipeline template

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.

[inline illustration] 6 month sales forecast (example)

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 retail management 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.  

Free sales pipeline template

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