The Ultimate Guide to Sales Forecasting (+ Free Templates)

Sales forecasting provides an estimate of the revenue and number of customers your business expects to generate during a specific time period. These estimates enable you to better plan for budgetary needs and business growth, and there is more than one way to produce them. In this article, we explore the purpose, benefits, methods, and the process for calculating potential revenues and offer free sales forecast templates to customize for your business.

Free Sales Forecast Templates

While many customer relationship management (CRM) software products offer built-in forecasting tools, your CRM might not, or your business may not yet be using formal CRM software. In either case, here are two free sales forecast templates you can download to create a one-year or multi-year report:

Download Our One-Year Sales Forecast Template: PDF | Excel

Download Our Multi-Year Sales Forecast Template: PDF | Excel

What Sales Forecasting Is & What It’s Used For

Sales forecasting estimates future revenue based on past performance, sales trends, sales opportunities, pipeline conversions, and upcoming marketing campaigns. It is primarily used by business owners, executives, and those in sales management to determine how much the business will grow or how much spending capacity will be available.

For example, let’s say a business wants to know how much available capital they will have to invest in expansion by adding a new location. To do this, they would factor in their current spending capabilities plus expected cash obtained through revenue generation. This is known as the cash flow by revenue number, and is calculated by doing a sales forecast.

The Benefits of Doing a Forecast

Estimated revenue predictions are important to incorporate in your sales plan for your business to grow. The insights sales forecasting provides offer tremendous value in budgeting, offering employee incentives, and scaling a business. Some of the main benefits of calculating future sales include:

• Helps in commercial lending underwriting, such as when you apply for a business loan
• Tells you if you have the capability to grow, hire more personnel, or add more locations
• Provides a framework for compensating and rewarding sales staff with bonuses and promotions
• Establishes total spending or investment capabilities over a set period of time
• Gives you the ability to view potential performance outcomes from marketing campaigns

Developing a sales forecast also allows you to establish attainable goals for your business. These goals heavily influence the scope of a business’ sales operations in terms of how they effectively generate leads, manage customer relationships, and close sales deals.

Sales Forecasting Methods

Forecasting entails inputting factors into an equation to output a sales estimate. Depending on which sales forecasting method you use, internal factors such as past sales, current opportunities, and marketing campaigns influence the estimates produced. There are also external factors to consider, like the economic climate, market competition, and seasonality.

The main types of sales forecasting methods:

Historical Trends

This sales forecasting method takes data from previous time periods, accounts for new factors such as growth or increased demand, and calculates projected sales revenue. While this method is ideal for businesses at least a few years old, new businesses could also use historical trends by evaluating information from other businesses similar to their own. Let’s take a look at an example of using historical trends to make a forecast.

Last year, the ABC Online Store made $100,000 in revenue, had 2,000 customers, and 60,000 website visits. Based on their marketing plan for the new year, they expect to increase web traffic to around 80,000 visits. Assuming each new customer spends the same average amount of $50 per purchase and the conversion rate of 3% remains consistent, ABC Online Store can expect revenue of $120,000.

(80,000 * 0.03) * 50 = 120,000

Let’s switch it up and say the business wants to predict how well they will do in their busy season. In past years, they accumulated 40% of its revenue during the Q4 holiday seasons (October to December). After September, they had sold $80,000 year-to-date. Based on their consistent proportion of revenue generated in Q4, they can expect their total revenue for the year to be $133,333, with $53,333 done in Q4 alone.

1-0.4 = 0.6 → 80,000/0.6 = 133,333 → 133,333 * 0.4 = 53,333

Now let’s switch the factors of the known historical information. Imagine after five years in business, ABC Online consistently makes 15% more than the previous year. There’s also a demand increase in the total market of 10%. If ABC did $150,000 last year, they can expect an increase of $22,500 (150,000 * 15%) due to standard growth as well as an additional increase of $17,250 due to new demand, for a total of $189,750.

150,000 * 0.15 = 22,500 → 150,000 + 22,500 = 172,500 → 172,500 * 0.1 = 17,250 → 17,250 + 172,500 = 189,750

Pipedrive forecasting reports (Source: Pipedrive)

Conversion-based Forecasting

A sales process that follows conversion rates of a sales pipeline or funnel can use conversion-based forecasting to estimate anticipated revenue. This method is more common in business-to-business (B2B) sales, which are usually finalized in the form of deals.

Business-to-consumer (B2C) organizations can also use this method if they follow a typical sales cycle for closing deals. Ecommerce businesses can use it if they track rates of website traffic, browsing, and purchasing.

Let’s take the example of ABC Management Consulting. They want to estimate revenue based on deals, deal values, and the conversion rates of their sales funnel. Going into the new year, they currently have 200 leads in the funnel and expect to generate 50 new leads throughout next year’s campaigns. There’s a total potential deal value of $6,000,000 and the following conversion rates:

• Aware of the brand to interested in more information → 16%
• Interested in information to interested in receiving an offer → 50%
• Received an offer to considering/negotiating that offer → 60%
• Considered to offer accepted/deal closed →75%

Based on this data, ABC estimates that of the 250 total leads, 40 (16% of them) will be interested in more information. Of those interested, 20 (50%) will want to receive an offer through a proposal, and 12 of them (60%) will strongly consider the offer by negotiating some of the terms. In the end, nine of the leads are expected to become clients of ABC, which translates into a total deal value and sales forecast of $216,000.

Next, let’s look at conversion-based forecasting for a B2C ecommerce company. Using industry averages and their internal marketing knowledge, ABC Online believes their digital campaigns will reach 2,000,000 views (awareness) over the next 12 months and get 10% to click and view the online store (interested). From the website, 30% will likely browse for a solid amount of time (consideration) and 5% of those will actually make a purchase (decision).

Let’s assume each purchase is for one unit of what’s being sold at a price of $100 each. Based on this, 3,000 purchases will be made for a total projected revenue of $300,000.

Zoho CRM pipeline and funnel conversion metrics (Source: Zoho)

Sales Rep Knowledge

This sales forecasting method is the least accurate because it doesn’t rely on actual historical data or conversion rates. Instead, you depend on the performance expectations, market intelligence, and confidence of your sales team to project the number of deals they expect to close or leads they anticipate generating.

Accuracy is always going to be in question for this method as sales reps like to be optimistic about what they expect to close, especially to their managers. Ideally, you will only use this method in conjunction with one of the others or when no other method for projecting revenue is possible.

A simple example of the way this method would be used is if XYZ Company is having a sales meeting with their sales reps. The manager goes through a list of new business opportunities and asks each rep responsible for the specific lead to provide a confidence level of closing the deal and how much they expect the deal to be worth. The following responses are given:

• Opportunities:
  • Deal 1→ 30% chance for $50,000
  • Deal 2→ 50% chance for $20,000
  • Deal 3→ 90% chance for $5,000
  • Deal 4→ 40% chance for $60,000
  • Deal 5→ 30% chance for $40,000
  • Deal 6→ 20% chance for $70,000
• According to these responses, the expected deal values are:
  • Deal 1→ $15,000 (30% of $50,000)
  • Deal 2→ $10,000 (50% of $20,000)
  • Deal 3→ $4,500 (90% of $5,000)
  • Deal 4→ $24,000 (40% of $60,000)
  • Deal 5→ $12,000 (30% of $40,000)
  • Deal 6→ $14,000 (20% of $70,000)

This makes the total sales forecast for new business in this scenario $79,500. It’s the sum total of the expected deal values ($15,000 + $10,000 + $4,500 + $24,000 + $12,000 + $14,000).

This method could also be less probability-based and go exclusively on a “close” or “will not close” basis. For example, rather than asking for confidence levels, a manager could just ask for the estimated value and whether or not the rep thinks it will be closed within the time frame. The benefit of this method is that you can motivate your sales reps to prioritize closing deals, especially ones where they expressed a high confidence level that it would close.

How to Perform a Forecast in Five Easy Steps

Much of the process of estimating future revenue is taking the information you already know (historical sales, typical conversion rates, or expected deal values) and incorporating it into a mathematical formula. Once you have a formula, all you need to do is plug and play with different numeric factors to produce revenue calculations.

Here’s how to perform a sales forecast in five steps:

1. Determine the Best Method

Your sales operation and offerings determine which forecasting method you should use. For instance, if your business is an ecommerce company that sells to consumers, either use historical trends or use the conversion-based method with online metrics that offer conversion rates for potential customers who click and navigate your website.

On the other hand, B2B businesses that treat every lead as an opportunity or deal in the sales pipeline should use conversion-based forecasting or sales rep knowledge to obtain revenue estimates. If you sell B2B services but generate sales through ecommerce, such as downloadable software products, use the online conversion-based method or historical data trends.

2. Collect Information & Data

No matter which method you use, you need to gather and organize the data needed to perform that method. For the historical trend method, you will gather data from previous years for sales revenue, units sold, deals closed, growth percentages, seasonality trends, and historical demand.

For conversion-based forecasting, seek out information based on current opportunities in the pipeline, industry averages, or intelligence from experienced sales staff to estimate pipeline or funnel conversions from stage to stage. For using sales rep knowledge, pull information on current opportunities and find out from your sales team which ones are the most promising.

Salesforce opportunity record with stage and value (Source: Salesforce)

3. Set Up Your Forecast Equation

Once you have the information required, you are ready to create a usable forecasting equation. The layout for each equation will vary depending on the method you’re using and the information you already have. For example, if you’re using historical trends and know the growth rate you expect to see, the equation would be:

Estimated Revenue = Previous Year Revenue * (1 + Estimated Growth Percentage)

For determining the number of deals closed or new customers using conversions, add each of the stages and conversion percentages to an equation as follows:

# Deals Closed = Total Sales Opportunities * (Stage 1 Conversion %) * (Stage 2 Conversion %) * (Stage 3 Conversion %) * … * (Final Stage Conversion %)

If you use the knowledge of your sales reps, you could still set up an equation based on their confidence percentage levels:

Estimated Revenue = (Deal 1 Estimated Value * Confidence %) + (Deal 2 Estimated Value * Confidence %) + (Deal 3 Estimated Value * Confidence %) + …. + (Last Deal Estimated Value * Confidence %)

4. Plug Your Data Into Your Equation

The information you accumulated in step two is what will be added into the formula to give you a sales estimate. Using the sample equations from the Methods section above, this is what the equations look like with sample quantitative information added to them:

• Historical trends: Estimated revenue = $150,000 * (1 + 15% annual historical average growth)
• Conversion-based: Number of Deals Closed = 250 leads introduced * (16% lead qualification rate) * (50% proposal/offer delivery rate) * (60% negotiation rate) * (75% deal won rate)
• Sales rep knowledge: Estimated revenue = ($50,000 * 30% confidence) + ($20,000 * 50% confidence) + ($5,000 * 90% confidence) + ($60,000 * 40% confidence) + ($40,000 * 30% confidence) + ($70,000 * 20% confidence)

Note: Numbers are from the ABC Online and XYZ Company examples above.

5. Calculate Your Sales Forecast

Once the numbers are added to the equation, you’re ready to calculate your estimates. It should be noted that if your equation is used to determine deals closed, customers created, or units sold, an extra step is required to calculate the actual revenue anticipated. This means taking what you calculated and multiplying it by an average value per deal, sales per transaction, or price per unit.

Below are the estimated revenue totals using the equations above:

• Historical trends: $172,500 Estimated Revenue = $150,000 * (1 + 15%)
  • Calculation: 172,500 = 150,000 * 1.15
• Conversion-based: 9 Deals Closed = 250 leads introduced * (16% lead qualification rate) * (50% proposal/offer delivery rate) * (60% negotiation rate) * (75% deal won rate) → 9 Deals Closed * $30,000 Average Deal Size = $270,000 estimated revenue
  • Calculation: 9 = 250 * (0.16) * (0.50) * (0.60) * (0.75) → 9 * 30,000 = 270,000
• Sales rep knowledge: $79,500 Estimated Revenue = ($50,000 * 30% confidence) + ($20,000 * 50% confidence) + ($5,000 * 90% confidence) + ($60,000 * 40% confidence)+ ($40,000 * 30% confidence)+ ($70,000 * 20% confidence)
  • Calculation: 79,500 = (50,000 * 0.30) + (20,000 * 0.50) + (5,000 * 0.90) + (60,000 * 0.40) + (40,000 * 0.30) + (70,000 * 0.20)

Bottom Line

Sales forecasting involves taking data you already possess and calculating a future outcome. These estimates are particularly useful for spending and growth planning. Businesses often use CRM software to make revenue predictions as it’s already storing historical sales data and conversion rates. For those without a CRM, we invite you to use our free templates or step-by-step process to perform your forecast.