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How to use regression analysis to predict business performance

How to use regression analysis to predict business performance

Regression analysis is a statistical method that can provide insight into the relationship of two or more variables, and how impactful they are on each other. This information makes regression analysis an effective tool for forecasting and predicting the future movement of variables.

For example, imagine an ice cream truck has gathered data on two variables for the past three months: daily sales and daily temperature. The sales would be the “dependent variable”, and the daily temperature the “independent variable”. After plotting the data on a graph with each of those variables on the axes, the business could generate a line to show the expected daily sales for a given day’s temperature. They would be likely to see that a high daily temperature generally leads to high ice cream sales, and regression analysis can give them a specific prediction.

So regression analysis can be used as a simple means to measure how correlated variables are, and once you know that, you can make predictions about what will happen to part of your business when certain conditions or metrics are met.

Strategic business decision-making

The ice cream truck example is a good, simple way to understand the concept, but for more complicated strategising with more data at your disposal, regression analysis is still extremely valuable. Regression analysis can be performed with more than two variables, and can find the most predictive and most significant indicators of business performance in a list of variables.

In SEO and digital marketing specifically, with the vast number of inputs available from search volume to seasonality to demographic or region breakdowns, regression analysis can be the first stop on your journey to effective predictive analytics as a business. By looking at how each of the variables affect each other and how your business reacts to changes in the data, you have the power to make decisions that are based on evidence rather than pure intuition, and reduce error in your strategy.

Regression analysis can also be effective when looking at competitors. Whether that is to calculate the correlation and impact of their own digital variables on their own business, or to find how their business affects your own, regression analysis is a viable method to get a leg-up on the rest of your market. There is so much guesswork, hypothesising, and bias in thinking about competitors and the market as a whole. Let regression analysis help you to make the right decision.

It’s important to say that regression analysis alone cannot and will not provide all the answers. It’s merely a tool in your toolbox that can guide you to more efficient and more productive business decisions in the future. The phrase “correlation not causation” applies where some regression analysis may suggest an insight, but upon looking further at the situation, you can see that the variables do not directly affect each other.  Regression analysis is an important first step when looking at any data-based business problem, but should be corroborated by other research and analysis.

Summary

While many companies today utilise regression analysis for tasks both simple and complicated, especially in large and competitive markets, there is still room for plenty more to bring it into their decision-making processes. Regression analysis can help you to understand strange spikes or changes in your data, predict movements in the future, or decide between two options for your business. Whether you start your own on Excel, or contact the team at Frankly Analytics, make sure you get regression analysis in your toolbox today.

Published by Alex Jordan