Last week we talked about the difference between attitude and behavior. We also explained why the Theory of Planned Behavior is essential to study consumers’ behavior based on contributing factors such as attitudes, subjective norms, and perceived behavioral control.
So, we already applied the theory of Planned Behavior; now, how we analyze and interpret our finds? There is a quick way to visualize and predict intention to buy. We can perform a Regression Analysis.
What is a Regression in Marketing?
Regression is a type of analysis used to conclude if there is a causal relationship or “correlation” between the independent and dependent variables.
According to Hubspot.com, you can use Regression Analysis for almost everything, “from figuring out whether more rainfall correlates with more crop growth, to how your blog has grown over time.”
The Regression can be easily performed on excel, and it helps to interpret coefficients, averages, and variables like purchase intention. This information is vital because marketers can suggest strategies to modify and increase intention or perceived behavioral control.
It’s like having a fortune teller and a crystal ball but more precise. The results of the Regression explain which of the variables, if modified, may impact behavior or intention.
How Can a Regression Analysis Help You?
The results of the Regression help to formulate strategic recommendations and allows us to know which factors are effective or ineffective before increasing purchase intention in your consumer; you can, as well, discover which factor is linked to another. You can also know if a result is really significant before designing any marketing tactic.
Maybe you have a data analysis team and don’t need to do calculations yourself, but lecturer and marketer Ginny Mineo states that understanding the process of Regression is helpful for everyone because you can notice revealing patterns “like how fast your blog has been growing. Depending on that answer, you can better staff your team, fight for budget, and allocate resources.”
Finally, when analyzing Regression, Harvard Business Review advises: Don’t get confused. Correlation is not causation. “It’s easy to say that there is a correlation between rain and monthly sales. The regression shows that they are indeed related. But it’s an entirely different thing to say that rain caused the sales. Unless you’re selling umbrellas.”
Did you like this post? Please share with me any experience in this matter. I’m here to listen.