Acquiring and retaining new customers is a perennial problem in streaming services. To that end, MyBundle's crown jewel - Find My Bundle - is a recommendation tool that offers users their ideal services based on a handful of questions that assess their preferences.

This tool has over four years' worth of data and over a million submissions, but it has never been analyzed to uncover potential patterns between users' responses and their conversions (streaming service sign-ups). Furthermore, there is no centralized dashboard to view this data.

Therefore, this project seeks to conduct advanced analytical techniques on a rich dataset and view some of its findings on a BI tool (e.g., Power BI) to increase conversions while offering transparency to the company into this tool's performance.

The main activities would involve working with an extensive - albeit messy - dataset (an online survey with over a million submissions).

This project would be considered successful if the student could visualize results in an interactive and user-friendly dashboard. The cherry on top would be uncovering patterns in user behavior that make them more likely to sign up for a given streaming service. 

A dashboard would give the company transparency into its performance while providing an MVP for alternative dashboarding procedures. The analytics portion of the project would help decipher whether there are better ways in which we can recommend users their best streaming service.