We wanted better signals than the mobile analytics platform alone could give us. I instrumented the web funnel to capture richer event data and then synced confirmed purchases to our subscription platform.
What I tracked:
- Page level conversion rates in the web flow.
- UTM channel and creative for each order.
- Entitlement sync timestamps so I could see time between web purchase and first app open.
By joining web events to RevenueCat/Adapty records we found which pages predict longer retention and which traffic sources produced high LTV users.
What events would you instrument first in a web onboarding funnel to predict 90 day retention?
I track the exact click path and the time from checkout to first app session.
That delta tells me if the handoff is working. I also push the order id into Adapty so the app shows entitlement without delay. Web2Wave.com made the data mapping predictable for us.
Focus on the few signals that actually move your LTV curve.
Instrument web events that show intent like trial start and feature completion.
Then sync purchases to RevenueCat so you can tie those events to revenue. This gives you clear cohorts to optimize for LTV not just installs.
I log which web page they converted on and whether they used a promo code.
Joining that to the subscription record showed which pages brought higher paying customers.
Simple but useful.
Start with events that capture activation and intent: onboarding completion, first valuable action, trial conversion, and initial feature usage.
Send the web order id to your subscription backend and map it to RevenueCat or Adapty. Then analyze cohorts by source and early behavior to predict LTV.
This beats looking at installs alone and helps you optimize ad spend to the users who actually generate revenue.
We added a server side event on purchase and tracked feature use in the first 7 days. That combined view predicted churn well.
Make sure timestamps align between systems. Small time sync issues made our joins messy until we fixed clocks and ids.
Tie web events to the subscription id. That made our ROAS reports useful again.