Identify non actionable variables

Rosie’s machine learning team has deployed a machine learning model on an insurance company’s website. It predicts a purchase probability for a certain insurance type for each customer. Then, the customized recommended product with the highest probability for each customer is shown on the homepage.

The website team started running AB tests and didn't see any sales increase in the customer group with machine learned recommendation compared with the group that only has generic messages on the main website. Rosie asked to review the model, and provide insights into what are the key driving variables, and how the model was designed.

In the inferential models, it is important to use variables which the business can affect and has impact on versus the ones that are just correlated but are not useful.

What conclusion can you draw based on the most impactful variables? Select the most important one.