The goal is to perform funnel analysis for an e-commerce website. Typically, websites have a clear path to conversion: for instance, you land on the home page, then you search, select a product, and buy it. At each of these steps, some users will drop o" and leave the site. The sequence of pages that lead to conversion is called 'funnel'. Data Science can have a tremendous impact on funnel optimization. Funnel analysis allows to understand where/when our users abandon the website. It gives crucial insights on user behavior and on ways to improve the user experience. Also, it often allows to discover bugs.

You are looking at data from an e-commerce website. The site is very simple and has just 4 pages: The first page is the home page. When you come to the site for the first time, you can only land on the home page as a first page. From the home page, the user can perform a search and land on the search page. From the search page, if the user clicks on a product, she will get to the payment page, where she is asked to provide payment information in order to buy that product. If she does decide to buy, she ends up on the confirmation page The company CEO isn't very happy with the ]VS\TL VM sales and, especially, VM sales coming from new users. Therefore, she asked you to investigate whether there is something wrong in the conversion funnel or, in general, if you could suggest how conversion rate can be improved. Specifically, she is interested in : A full picture of funnel conversion rate for both desktop and mobile Some insights on what the product team should focus on in order to improve conversion rate as well as anything you might discover that could help improve

Data is in the data folder. For analysis run Funnel_Analysis.ipynb.