Case Study: Fivetran achieves deeper user behavior insights with Heap

Why Fivetran switched to Heap for detailed analytics

Fivetran, the automated data movement platform, needed a better way to understand user behavior, identify what triggers users to log in, and give Product and Marketing teams more self-serve analytics. Its previous analytics tool lacked the depth and ease of use needed to support those goals, so Fivetran turned to Heap, alongside Chameleon, for deeper insight into how customers interacted with the product.

Heap implemented detailed product analytics, session replay, and integration with Chameleon microsurveys and in-app messaging so Fivetran could connect user feedback to actual behavior. With Heap, Fivetran improved reporting and experimentation, uncovered why users were entering the app, and identified 10–15 bugs before GA release; the company also gained more accountability across teams and expanded self-service insight adoption across Product, Design, Marketing, and Analytics.

Fivetran

Andrew Morse

Product Manager