Optimizing conversion rate is likely the most common work of a data scientist, and rightfully so. The data revolution has a lot to do with the fact that now we are able to collect all sorts of data about people who buy something on our site as well as people who don’t. This gives us a tremendous opportunity to understand what’s working well (and potentially scale it even further) and what’s not working well (and fix it).
The goal of this challenge is to build a model that predicts conversion rate and, based on the model, come up with ideas to improve revenue.
We have data about users who hit our site: whether they converted or not as well as some of their characteristics such as their country, the marketing channel, their age, whether they are repeat users and the number of pages visited during that session (as a proxy for site activity/time spent on site).
My goal is to:
- Predict conversion rate
- Come up with recommendations for the product team and the marketing team to
improve conversion rate