Heap SQL: Combining Heap and Revenue Data
One of the most powerful aspects of Heap SQL is the ability to join a complete set of user interactions with additional data sources such as a user's order history. This section will cover topics such as calculating the average revenue per user and lifetime value of a user based on their interactions in your product and attribution channels. You can check out a complete list of all queries in this guide here.
ARPU per UTM Source
This query combines Heap's attribution data with order history data, allowing you to compare how each source is correlated with a user's downstream behavior.
Monthly ARPU per UTM Source
With a slight tweak to your query you can see how the UTM source is correlated with the ARPU on a month to month basis.
ARPU based on User Behavior
You can also combine Heap data with revenue data to determine if certain actions or if the number of times an action is performed is correlated with higher returns. This report segments users into two categories: users who have uploaded files and users who have not uploaded files. It then calculates the ARPU for each segment. We can see here that the ARPU is roughly seven times higher for users who have uploaded files.
Analyzing Churned Customers
Heap SQL allows you to get a better understanding of your churned customers as well. You can answer questions like "Where did they come from?", "What did they do in my product?", and "How much revenue did a customer bring in before churing?". The table below combines Heap session data, server side events, and revenue data to enhance your understanding of churned customers.