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Create a Complete View of Your User

Analyzing customers’ behavior starts with knowing who they are. Connect anonymous and cross-platform behavior to a single identity.

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User-centric Schema

Users are more than just a series of events. A user-centric schema ensures every data point ties back to a person.

  • Drill down into one identity to see a user’s complete history of behaviors
  • Easily combine other sources in your data warehouse with predictable join keys
  • Use the standardized data model to accelerate predictive modeling, perform cluster analysis, and identify good and bad actors
Identity Resolution

You can’t compute a conversion funnel between “View Homepage” and “Sign Up” if you can’t connect these events to a single person. Traditional tracking requires you to chose one identity, but that rarely represents user flows in reality. That's why Heap allows you to create Virtual Users using multiple user attributes.

  • Retroactively combine user profiles across different channels, platforms, and devices
  • Map a variety of user attributes such as guest checkout ID, customer email, and customer ID to a single Virtual User
  • Programmatically merge anonymous and identified behavior to understand key behaviors in the pre-purchase journey
One-click Integrations

Configuring datasets with unrelated tables and varying join keys is hard, even when you’re an expert in the underlying data schema. With Heap, you can seamlessly integrate third-party data with Sources.

  • Use custom rules to join Heap and third-party data without APIs
  • Create fully auditable Virtual Users in Heap without manipulating your downstream data model
  • Get a holistic view of your user with data from marketing automation platforms, CRMs, payment processors, and more
User View

Thousands of companies choose Heap for automatic, retroactive insights. Companies like LendingClub, Microsoft, and Harman trust Heap to deliver insights fast.

Learn more about how Microsoft saves hours by using Heap »

“We have been able to save hours and weeks of effort by using Heap instead of designing multiple ETL jobs to combine data from different tools. Everything just works out of the box.”

Abhishek Ratna
Abhishek Ratna, Sr. Marketing Manager

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