DROPSY

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Revenue predictability is an essential business exercise. And it is an accurate sales forecast that allows company leaders to make smarter decisions regarding target setting, budget allocation, discounts, hiring, commissions and other actions that deeply affect cash flow. On the other hand, an inaccurate sales forecast results in an environment where managers are anxiously trying to guess whether they will actually meet the targets set for that month, leading to a general lack of bulk lead in business decision-making. As a result, these leaders may not be aware of any problems in their operations in time to correct them, which, of course, can hurt sales.



But if you think that forecasting sales is a complex task, try running a business without a forecast (even a simplified one). You will see that it is much more difficult.



So, if you want to build your sales forecast, follow the steps described in this article!



What is a sales forecast?

As we already mentioned, a sales forecast is a prediction of your company's future revenue .



These forecasts are typically based on historical data, industry trends, and an analysis of your current sales pipeline . Businesses use sales forecasts to estimate weekly, monthly, quarterly, and annual sales totals and plan their operations for expected growth. Much like a weather forecast, your team should view your sales forecast as a blueprint to work from, not a 100% accurate prediction.



Sales forecasting is also different from setting sales goals. While a sales goal describes what you want to happen, a sales forecast estimates what will happen regardless of your target. Ideally, you should plan your goals with these growth predictions in mind, but this depends on the level of maturity of your company’s sales data department.



What you need to have an accurate sales forecast
Newly launched companies that don’t have much data about their own sales processes need to rely on industry averages or even educated guesses to build a forecast. On the other hand, more established companies can use their historical sales data to model their future performance.



However, clean data is the most important requirement for accurate sales forecasting. This means that obtaining good data is crucial and should be a priority in an operation that seeks this work methodology.



Below is a simple step-by-step guide of what you need to do to get started on this journey as a sales "seer":



1. Document your sales process
Without a clearly documented sales process that outlines the actions and steps required to close a deal, you will have difficulty predicting whether a single deal or more will close.



2. Set your sales goals
While your forecast may differ from your goals, you won’t know if your forecast is worthwhile unless you first have a goal in mind. Therefore, every salesperson needs an individual, realistic goal to work towards, and the goal is to at least meet and ideally exceed that goal.



3. Set a baseline of basic sales metrics
Having easily accessible measurements of basic sales metrics will make your forecast much easier to access. Analyze and record:



the average time it takes for a lead to express interest
the average time it takes for this lead to close a deal
the average price of a sale
conversion rates at each stage of the sales funnel
how many new customers do you gain each year
how many customers do you lose each year
if there are specific months where you acquire or lose more customers than usual


All of this information can be easily recorded and analyzed on sales platforms like Insight Sales.



4. Understand your current sales funnel
Make sure your current sales funnel and CRM are up to date and organized in line with your process. (If you haven’t adopted any tools, forecasting is much harder, but not impossible.)



Sales forecasting methodologies

There are several methods you can use to forecast your sales. Many companies use two or more sales forecasting techniques together to create a set of forecasts. This way, they have a better-case and worse-case view of the future.

To deal with the increasing variety and complexity of management forecasting problems, many forecasting techniques have been developed in recent years.
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