Let’s take a look at what regression analysis means, in layman’s terms, for sales forecasting. That type of explanation isn’t really helpful, though, if you don’t already have a grasp of mathematical processes, which I certainly don’t. There are multiple different types of regression analysis, but the most basic and common form is simple linear regression that uses the following equation: Y = bX + a Results of this analysis demonstrate the strength of the relationship between the two variables and if the dependent variable is significantly impacted by the independent variable. In statistics, regression analysis is a mathematical method used to understand the relationship between a dependent variable and an independent variable.
Thankfully, this piece will give an easy to understand breakdown of regression analysis in sales and guide you through an easy to follow example using Google Sheets. If you’re anything like me and not at all mathematically inclined, conducting this type of forecast may seem daunting. Regression analysis is one of these methods, and it requires in-depth statistical analysis.
Some forecasting methods involve doing basic math, like adding up month to month sales, and others are more in-depth. Forecasting can also help you decide on future business endeavors, like when you’d have the revenue to invest in new products or expand your business. Sales forecasting is important because it can help you identify what is going right, as well as what areas of your current strategy need to be adapted and changed to ensure future success.įor example, if your team is consistently below quotas, sales forecasting can help determine where and why these issues are happening.
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