With ATT and similar privacy changes, in-app signals got thinner. I started collecting non-invasive context on the web funnel — things like chosen plan, onboarding answers, and voluntary identifiers — then linked them to subscription records.
That richer context helped me build better cohorts and understand why some users churned quickly. I kept the data minimal and asked for consent where needed. The result was clearer product analytics even when platform-level attribution was limited.
How do you balance collecting useful data on web onboarding while staying respectful of privacy and consent rules?
I only collect what directly helps onboarding and billing.
Email or a hashed id plus onboarding choices gives enough signal to run cohorts. I store those server side and tie them to subscription status so the analytics are complete.
If you need a fast setup try a JSON funnel export from Web2Wave to avoid building the plumbing yourself.
Collect voluntary inputs on web and map them to subscription records on the server.
This gave us better retention cohorts without relying on device level identifiers. It also meant we could run targeted winbacks based on real behavior.
Having a platform where web changes reflect in the app instantly was a big help for quick experiments.
I ask for an email and one or two onboarding answers on web.
That small extra info made cohorts meaningful and kept privacy headaches low.
Ask less get more consented data
The trick is to capture signals the user willingly provides and make them actionable. Save plan choice, intent questions, and first actions on the server. Tie those to subscription events and product analytics. Then analyze which onboarding paths lead to higher LTV.
This avoids relying on ATT level identifiers and still gives rich cohorts for retention work.
We hashed emails and used them as a stable cross platform key. You can respect privacy and still sync behavior if you limit storage and document retention.
I only ask one extra question in onboarding. It made segmentation useful and avoided privacy noise.
Hashing identifiers and keeping data minimal solved most compliance questions for us.