Sales forecasting offers you a glimpse into the future of your sales revenue. And which company wouldn’t want to get a sneak peek of that? Without a sales forecast you’re left guessing in the dark.
There isn’t one, sure-fire method of predicting sales that will work for all companies. Instead, there are several that may or may not help you make an estimation of your team’s future performance.
Below I’ve described the most popular methods of creating a sales forecast.
Without further ado, let’s dive into the topic of sales forecasting.
What is sales forecasting?
Sales forecasting is an estimation of your future sales for a given period of time. Most often it’s done for a given month, quarter or year.
It goes without saying that sales forecasts should be as accurate as possible. It is, however, impossible to make a 100% correct prediction.
There are several approaches you can take to try to estimate your future sales revenue. Some of them are backed with past sales data, others rely heavily on the sales reps’ experience and intuition.
I go into more detail about sales forecasting methods below. But first, see why sales forecasting is a must-do.
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The importance of sales forecasting
With sales predictions at hand:
- you have a better idea of how to plan ahead for hiring new team members, budgeting and managing resources
Should you hire another sales rep? What should the budget for marketing be right now?
A sales forecast will help you and other decision-makers at your company to better, informed decisions.
- you can spot issues within your sales strategy and get back on the right track before there’s any real harm
- the directors know what they can expect from the sales department
- the CEO knows what to tell the investors
So how can you predict your future sales?
Sales forecasting methods
Here are the most often used sales forecasting methods:
What’s it about? In this method, you assess how likely deals are to close, based on at what stage of the pipeline they are currently.
How does it go? Once you choose the reporting period, determine the potential value of each deal and how likely it is to close, you multiply the probability by the size of an opportunity.
You back this method with data – you use your conversion rates in between deal stages to identify the probability of closing, so this metric has to be reliable. Otherwise, the results will be inaccurate.
What this approach doesn’t take into account, though, is the age of an opportunity. So two opportunities could get the same potential value, even though one’s been sitting in the pipeline for 4 months, and the other for 4 days.
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Past data forecasting
What’s it about? You use historical data to create a prediction for future sales.
How does it go? You take a look at the past sales data for a given time period, e.g. a month or a quarter, and make an estimate. You can add your average growth rate into the equation.
Make sure you’re using comparable time periods. For example, if December always brings you much more sales than other months, don’t make a prediction for July based on it.
Take seasonality and the demand into account.
Think also about any internal factors that might affect the results, e.g. has your team grown recently? Is your biggest competitor running an effective marketing campaign?
Some of these factors might be hard to show in specific numbers, which is a downside of this approach.
You also won’t be able to use it in new businesses, as there’s no past data yet.
The “ask a sales rep” method
What’s it about? The name already gives that away, but let me just say: in this one, you rely on your sales reps’ prediction of closing their deals.
How does it go? As simple as it gets – you ask your sales reps two questions:
- How likely are you to close that deal?
- When are you going to close it?
The team members will base their answers on their experience and expertise, but it’s still a very subjective estimation. Some of them might be more optimistic than realistic about the outcome, or – on the contrary – play it safe and make a more pessimistic guess.
This method is often used by new businesses, though, as they don’t yet have any historical data to back their sales forecasts with.
Sales cycle forecasting
What’s it about? You take a look at how long a deal has been sitting in your pipeline, and compare it with your average sales cycle length.
How does it go? It relies on the basic assumption that the longer a prospect has been in your pipeline, the closer you are to sealing the deal.
With this method, you can get more specific and create a sales estimation based on how a lead has been acquired. For example, if the first touchpoint is a cold email, a prospect will probably need more time to close than someone who reached out to you directly, asking about your product features.
Note: This method needs reliable data on your sales cycle length, which means the sales reps need to keep very good track and log all necessary data into the CRM. A guesstimate won’t do, so this approach won’t really work for new businesses who don’t yet know how long it takes them to close a deal.
Multivariable analysis forecast
What’s it about? Multivariable analysis forecast combines parts of the other methods. It’s the most complex one.
How does it go? It’s based on predictive analytics and uses data like average sales cycle length and opportunity closing rate.
Since it’s based on so much data, this method can potentially bring you the most accurate predictions.
But what it also means is that well-organized and accurate data is an absolute must in this case. It also requires an advanced analytics tool, which makes it better-suited for established companies rather than new ones whose budgets are tighter.
Over to you
Hope this article gave you a pretty good idea of which sales forecasting method would work best for you.
If you found it useful, you might also like these blog posts:
How to Set Achievable Sales Targets for an Outbound Sales Team>>
How to Build a Sales Pipeline to Turn Your Outbound Leads into Customers?>>
How to Effectively Manage a Sales Pipeline to Grow Your Customer Base?>>
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