The world’s second largest manufacturer of home appliances.
Marketing managers are often interested in and challenged with measuring the effectiveness of their website on current and prospective customers.
Does the current version of their website provide a platform necessary for customers to browse all the products offered, compare information about the different products
to then ultimately lead a customer to make a purchase?
From this, can we capture a customer’s behavior on the website that indicates a likelihood or propensity to make a purchase. In other words, can we predict whether or not a customer will make a purchase based on their web browsing history?
- Retrieving the Google Analytics data from the Google API
- Making sense of and preparing the data in a meaningful way to build propensity models
- Building a robust, sound machine learning model that is both accurate and explainable