Case Study: Cover achieves scalable analytics and higher conversion with Sisense for Cloud Data Teams

Cover Uses Complex Data Analysis to Empower Customers

Cover is a San Francisco–based startup that lets customers insure items via a simple mobile app. As the company grew it amassed large volumes of raw interaction, event and financial data, but none of it was routed into an analytics stack—engineers were running ad hoc SQL queries and Cover needed a way to consolidate data, avoid building a custom ETL, and enable analysis without pulling engineering resources away from the product.

By adopting Sisense for Cloud Data Teams, Cover linked multiple data sources into a single analytics layer, used SQL Views instead of a bespoke ETL, and built dashboards and automated email reports for the company. The platform’s Python/R integration enabled in-platform A/B testing and a Random Forest model to score and prioritize likely customers, and a single canned query now drives monthly financial reporting—delivering faster, scalable insights, reducing engineering overhead, and empowering nontechnical teams to act on data.

Cover

Chris Stanley

Business Operations