From the time it is installed, Heap captures a lot of useful user information,
like browser, landing page and location. But what if you have data about users
from before Heap was installed? This Play guides you through bringing
historical data into Heap so you can understand the customer journey to the
fullest extent.
Step 1: Prepare Data to Bring into Heap
Determine what historical data you need to bring into Heap. Will you be bringing over everything, or just a specific set of user properties? Remember, the more data you have in your account the more robust you can be with the questions you are answering in your account.
Once you determine what data will be brought into Heap, you will then need to enrich your data via API or through one of Heap’s native source integrations.
Hint
Be sure Identity is set up in your account!
Step 2: Make sure your data is correctly firing!
Once you set up your custom APIs and/or Integration(s), you will want to be sure everything is properly firing. The following report will allow you to cross your t’s and dot your i’s and confirm your data is correctly coming into Heap.
| Query #1 | Is my data properly flowing in? |
|---|---|
| Users | – Filter by Identity is Defined or – Filter for yourself using the Heap User ID |
This will confirm any user properties you are sending into Heap are properly firing. Scroll
through the list of identified users, are you seeing those properties you just added? If you
filtered for just yourself, are you seeing the correct information on your user record?
If not, you will need to revisit step #1 of this Play.
Not sure how to find your User ID?
Step 3: Interpret your results and take action
Once these additional properties are being brought into Heap, new doors open up! Understanding historic customer engagement metrics provides you with the opportunity to segment customers based on customer journey and lifecycle properties, analyze the time it takes on average to reach your desired LTV, and improve conversion rate optimization among specific user segments. All of this and more!
Conclusion
Understanding a customer journey is important, and with Heap you can
understand not only the journey – but patterns among customer details. The
more data you have in Heap, the more robust your analysis will be.