5 Sales Forecasting Methods You Should Know

“The goal of forecasting is not to just predict the future but to tell you what you need to know to take meaningful action in the present.” – Paul Safflo

Sales is the lifeline of every business. You’ll find that you ponder over questions like:

How many leads do we need in this quarter to reach our revenue target?

What will the revenue target be next year?

Do we need to increase our sales team size to reach our sales goals?

The key to these questions is hidden in Sales Forecasting.

Sales forecasting isn’t about going head-on crunching those numbers on Excel, you need to have a much more careful analysis for forecasting accurately.

According to a report, approximately 25% of sales managers^[i] are unhappy with the accuracy of their sales forecast. And according to research, companies that have accurate sales forecasts are 13% more likely to increase their revenue year-over-year^[ii].

Sales forecasting is no rocket science, you don’t have to be a mathematical geek or have a Ph.D. in Excel. Let’s understand all about sales forecasting and how you can use it accurately to drive business growth.

What is Sales Forecasting?

Sales forecasting is the process that estimates potential sales and what will happen, regardless of your goal. A sales forecast is dependent on historical data, industry trends, and the current sales pipeline.

The Importance of Sales Forecasting

Sales forecasting is really important as it allows you to find potential trends, events, or competitors so that you can mitigate any risks that may be related to them.

Sales forecasting is tied to many business decisions like:

• Financial planning
• Marketing budget
• Stock value
• Investment portfolios
• Operations department

It matters because it helps with:

• Better decision-making
• Budgeting and risk management
• Efficiently managing cash flow
• Improving sales processes
• Setting sales goals

5 Methods for Sales Forecasting

Forecasting sales can feel a bit intimidating but there are some methods you can use to accurately see it through. Let’s understand those.

1. Opportunity Stages Forecasting

In this forecasting method, your sales staff breaks down your sales pipeline into different stages. Usually, most businesses break their sales pipeline down into stages like:

• Prospecting
• Qualified
• Won or lost

The farther along a deal goes in this chain of stages, the better chance it has of converting to “Won.” Here, you multiply a deal’s potential by its win likelihood (usually, this can be easily determined in most CRMs).

For instance, you have a $2000 deal opportunity with a 10% likelihood to be won. Your opportunity forecast would, therefore, be $200. Now, do this for each deal in your pipeline and then add the overall forecast amount. This method allows you to quickly estimate its calculations but doesn’t consider the size or age of each opportunity.

2. Length Of Sales Cycle

This is a quantitative forecasting method to predict when a deal is most likely to close rather than solely depending on your overall success rate.

For this, your sales team should know how long your average sales cycle is. The basic formula for the average sales cycle is:

Total No. of Days to Close Deals / No. of Closed Deals

With this method, you can learn about different types of deals in your pipeline. Let’s say, you recently closed five deals. Now, calculate the number of days it took to close each one:

• Deal 1: 65 days
• Deal 2: 60 days
• Deal 3: 62 days
• Deal 4: 55 days
• Deal 5: 58 days

Total: 300 days

Divide 300 by the number of deals (in this case, 5) and you get your average sales cycle of 60 days or two months. Now that you know your average sales cycle, you can apply it to individual opportunities in your pipeline. With this method, you can integrate lead sources to forecast those opportunities. However, the limitation here is that these calculations work only with accurately tracked data.

3. Regression Analysis

The regression analysis method gives an in-depth quantitative view. However, this method requires a comprehensive understanding of statistics and different variables that can impact sales. You would also need a regression software, such as InsightSquared or MethodData to run an effective analysis.

Some essential steps with a regression analysis include:

• Decide the reasons for forecasting.
• Determine your dependent and independent variables.
• Choose the time period to review
• Choose a regression model and run.
• Understand the correlation between variables.

Regression analysis helps you with an in-depth and accurate understanding of variables that impact sales at any given time. However, this method is incredibly advanced and is not very easy to use.

4. Multivariable Analysis Forecasting

This method uses predictive analytics and leverages the power of several other factors, such as average sales cycle length, probability of closing based on opportunity type, and individual rep performance. This forecasting method tends to be more accurate because it relies on data from multiple sources. However, this method requires an advanced analytics solution and won’t be feasible if you have a small budget. Also, you’ll need clean data to ensure accurate results.

5. Pipeline Forecasting

This sales forecasting method evaluates every opportunity currently in your pipeline and calculates the chances of it closing based on the unique company variables including the sales rep’s win rate and opportunity value. This forecasting method is dependent on the high-quality data that you provide. Ensure that your sales reps regularly enter accurate data into the CRM to get the most from this method because this method is very data-reliant and can be easily skewed.

The method you choose to incorporate for your sales forecasting would depend on various factors such as the market share of the company, the stage of your business, your business model, the size of your sales team, the quality of data, budget, etc.

Here’s a checklist to keep in mind:

• Consider both internal and external factors that can impact your sales.
• Your sales team should create a documented, structured sales process.
• Regularly revisit your sales forecast.
• Ensure that your teams maintain accurate CRM data.
• Look at your historical data to establish a baseline.

With sales forecasting, you’ll be ready to combat any curveballs that may come your way.

Want to be a sales forecasting pro? Talk to us.

Statistics References

^[i] Saleshacker
^[ii] Sage