A/B tests are performed to test changes on a web page by running experiment where a control group sees the old version while the experiment group sees the new version. Based on a metric, we see how people react to the change. This metric helps measure th level of engagement from users in each group.
This project aims to understand the results of an A/B test run by an e-commerce website. The company has developed a new web page in order to try and increase the number of users who "convert," meaning the number of users who decide to pay for the company's product.
Help the company understand if they should implement this new page, keep the old page, or perhaps run the experiment longer to make their decision.
- After running a one-side test, we fail to reject that the old page lead to more conversions.
- Using a regression approach (a two-side test), we also fail to reject that the old page lead to more conversions.
Based on this statistical results, I think that the company should stick to the old website. However, it will be a good idea to extend the duration of the test to be sure that the results obtained in the course of these tests are not due to change aversion.