What Is Sales Forecasting: Methods & Steps (+ Free Templates)
Jess served on the founding team of a successful B2B startup and has used a wide range of sales and marketing tools over the course of her 15-year career. She uses her industry knowledge to deliver the best answers to your questions about sales tools and sales management.
Jill is a writer at Fit Small Business specializing on Customer Relationship Management (CRM) software.
This article is part of a larger series on Sales Management.
Sales forecasting provides an estimate of the revenue your business expects to generate and the number of customers it will serve during a specific time period. These estimates may come from analyzing historical trends, forecasting opportunity conversions, or relying on your team’s existing sales knowledge. Sales forecasting enables you to better plan for budgetary needs and business growth.
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:
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💡 Quick Tip:
Many customer relationship management (CRM) platforms offer built-in sales forecasting tools that make planning your business goals simple.
Consider a CRM like Pipedrive that takes your previous revenue reports and creates sales growth projections automatically to estimate future revenue.
Thank you for downloading!
💡 Quick Tip:
Many customer relationship management (CRM) platforms offer built-in sales forecasting tools that make planning your business goals simple.
Consider a CRM like Pipedrive that takes your previous revenue reports and creates sales growth projections automatically to estimate future revenue.
Methods of Sales Forecasting
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 primary sales forecasting methods include historical trends analysis, conversion-based forecasting, and sales rep knowledge.
Historical Trends Analysis
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 similar businesses. Let’s take a look at an example of using historical trends to make a forecast.
Last year, the ABC Online Store made $90,000 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 a revenue of $120,000.
(80,000 x 0.03) x 50 = 120,000
Use our calculator below for a quick sales forecast based on historical trends:
Let’s switch it up and say the business wants to predict how well it will do during the busy season. In past years, the Q4 holiday season (October to December) accounted for 40% of its revenue. Through September, it had made $80,000. Based on the consistent proportion of revenue generated in Q4, the business can expect 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 x 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 could expect an increase of $22,500 (150,000 x 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 x 0.15 = 22,500 → 150,000 + 22,500 = 172,500 → 172,500 x 0.10 = 17,250 → 17,250 + 172,500 = 189,750
Pro tip: Many CRMs include forecasts in sales reporting features. Pipedrive, for instance, analyzes revenue reports from past periods and considers growth projections and current open opportunities to estimate future revenue.
Users can simply view past data from previous years to forecast their sales performance. (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 as 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 website traffic, browsing, and purchasing rates.
Let’s take the example of ABC Management Consulting. It wants to estimate revenue based on deals, deal values, and the conversion rates of its sales funnel. Going into the new year, it currently has 200 leads in the funnel and expects to generate 50 new leads throughout next year’s campaigns. There’s a total potential deal value of $6 million 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 its digital campaigns will reach 2 million views (awareness) over the next 12 months. It also anticipates 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 for $100 each. Based on this, 3,000 purchases will be made for a total projected revenue of $300,000.
Pro tip: Use your CRM software to track sales pipeline or funnel stage conversion rates. Zoho CRM, for instance, takes data stored in your CRM system, including the number of leads and stages of each lead, and shows you the conversion rates. The information is presented on Zoho’s dashboard and can be broken down further by the location of a lead, sales stage, and lead source.
Zoho CRM pipeline and funnel conversion metrics (Source: Zoho CRM)
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 your sales team’s performance expectations, market intelligence, and confidence 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. That said, sales rep knowledge is instrumental in interpreting or reviewing sales forecasts generated from historical data or forecasted conversions to see if it’s aligned with your typical business performance.
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 a rep responsible for a 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 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.
While sales rep knowledge is instrumental in interpreting sales forecasts, using software that can accurately predict forecasts is still ideal. In fact, 60% of B2B businesses that base their selling on experience and intuition plan to adopt data-driven selling by 2025, resulting in more accurate forecasts. Software like Salesforce has predictive analytics capabilities through its artificial intelligence (AI) tool, Einstein, which can provide actionable forecasts and recommendations sales reps might miss.
Salesforce’s Einstein AI assistant provides predictive analytics. (Source: Salesforce)
How to Perform a Forecast in 5 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.
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, you can use historical trends to forecast upcoming sales. Alternatively, 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 forecasting method or historical trends analysis.
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. For using sales rep knowledge, pull information on current opportunities and find out from your sales team which ones are the most promising.
Pro tip: CRMs make it easy to store and gather the information needed for sales projections. It allows you to create opportunity profiles to track the stage in the sales process the opportunity is at as well as the potential deal value. This information can be used to create conversion and estimated revenue reports.
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 sales forecast formula would be:
Estimated Revenue = Previous Year Revenue x (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 x (Stage 1 Conversion %) x (Stage 2 Conversion %) x (Stage 3 Conversion %) x … x (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 x Confidence %) + (Deal 2 Estimated Value x Confidence %) + (Deal 3 Estimated Value x Confidence %) + …. + (Last Deal Estimated Value x 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 x (1 + 15% annual historical average growth)
- Conversion-based: Number of deals closed = 250 leads introduced x (16% lead qualification rate) x (50% proposal/offer delivery rate) x (60% negotiation rate) x (75% deals won rate)
- Sales rep knowledge: Estimated revenue = ($50,000 x 30% confidence) + ($20,000 x 50% confidence) + ($5,000 x 90% confidence) + ($60,000 x 40% confidence) + ($40,000 x 30% confidence) + ($70,000 x 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 x (1 + 15%)
- Calculation: 172,500 = 150,000 x 1.15
- Conversion-based: 9 deals closed = 250 leads introduced x (16% lead qualification rate) x (50% proposal/offer delivery rate) x (60% negotiation rate) x (75% deal won rate) → 9 deals closed x $30,000 average deal size = $270,000 estimated revenue
- Calculation: 9 = 250 x (0.16) x (0.50) x (0.60) x (0.75) → 9 x 30,000 = 270,000
- Sales rep knowledge: $79,500 estimated revenue = ($50,000 x 30% confidence) + ($20,000 x 50% confidence) + ($5,000 x 90% confidence) + ($60,000 x 40% confidence)+ ($40,000 x 30% confidence)+ ($70,000 x 20% confidence)
- Calculation: 79,500 = (50,000 x 0.30) + (20,000 x 0.50) + (5,000 x 0.90) + (60,000 x 0.40) + (40,000 x 0.30) + (70,000 x 0.20)
Benefits of Sales Forecasting
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:
- Having accurate data to back hiring requests or expand locations
- Being able to create a realistic framework for salary increase or bonuses
- Attaining a realistic overview of your year-on-year performance
- Being aware if you need to look for more business or clients to hit targets
- Being able to determine a healthy spending capacity
- Having proof for commercial lending underwriting
Developing a sales forecast also allows you to be more realistic with your goals and have visibility if you need to exert more effort in converting leads to sales to reach your revenue targets. In fact, according to popularly reported figures, 97% of companies that implemented sophisticated forecasting processes achieved their quotas; only 55% of companies that didn’t use strong forecasting processes hit their goals. Meanwhile, those that leveraged a structured forecasting process increased their win rates by 25%.
Forecasting in Sales Best Practices
Forecasting sales offers a lot of advantages—especially in providing businesses with accurate visibility of their upcoming business performance. However, it must be done correctly to reap the benefits. Below we share some best practices sales teams should observe when doing sales forecasts.
- Have a proper and consistent forecasting system: Having an established system in place ensures that you process the correct data, while using the same system consistently will help provide more accurate forecasts based.
- Use current and updated sales data: Make sure that you are using only the most updated data. For example, regularly updating your pipeline and opportunities lessens the instances of overestimating your incoming revenues.
- Put proper team collaboration in place: Team collaboration is always ideal when doing forecasts as there are areas that one team member can spot which others may not. Having the sales team manager review forecasts also increases the chances of correctness and accuracy.
- Complement software usage with human knowledge: While forecasting sales lessens instances of inaccuracy, having an actual sales agent review and interpret the data gives businesses a more holistic and realistic view of their sales forecasts.
Bottom Line
Forecasting sales involves taking data you already possess and calculating a future outcome. These estimates are particularly useful for spending and growth planning. Businesses often use a CRM system to make revenue predictions as it’s already storing historical sales data and conversion rates. For those without a CRM, download and use our free templates or step-by-step process to perform your forecast.
