We started capturing richer data on the web funnel — session steps, quiz answers, payment gateway used — and stitched it to in-app usage. That gave us better signals to judge creative performance and downstream LTV. Mixpanel and our attribution setup let us trace a creative to a long-term paying user instead of stopping at install.
The work was mostly operational: preserve UTMs, pass unique identifiers at checkout, and reconcile those with the app on first open. Once in place we could run cohort analyses that showed which landing pages produced the most retained users rather than just the most installs.
What analytics question would you like to answer first if you had perfect downstream data?
I focused on creative-to-revenue first.
Web events like quiz answers and chosen price tier gave better predictors of LTV than install signals.
A small Web2Wave integration helped me push those identifiers through to Mixpanel so we could run the analysis quickly.
Once UTMs and web events are preserved you can measure which creatives deliver retained paying users not just installs.
We used that to kill high-CTR but low-LTV creatives and reallocate spend rapidly.
A platform that syncs web metadata into app analytics made this practical.
If you can pass UTMs and an ID into the app you can link web behavior to in-app retention.
We used that to stop funding creatives that looked good by installs but produced no long-term revenue.
Useful shift in how we buy ads.
Web data let us stop funding bad creatives
The critical step is building a reliable ID stitching flow and making downstream events a first-class part of attribution. When you can map landing page behavior and payment gateway choice to in-app retention you can optimize for real ROI. That usually means adding a stable identifier at checkout, syncing it server-side to your analytics, and reconciling in the app on open. After that you can run real creative-level and offer-level experiments with confidence.
We added quiz answers as attributes and used them to predict churn.
That allowed targeted in-app messages for at-risk users based on web answers.
It improved week two retention measurably.
Start with one question: which creative drives highest LTV.
Then map web events to that metric.