Paywall Growth Engineer template
Cut paywall noise—give the Growth Engineer traffic quality, onboarding intent, purchases, and subscription health before one change.
Product data preview
Signals to agent context
Funnels, instrumentation, and evidence your coding agent can act on.
Use paywall events, RevenueCat outcomes, onboarding context, and user feedback to create one focused Growth Engineer task.
Who this is for
Start here if the problem below sounds familiar. You do not need every connector on day one—just enough signal for the Growth Engineer to propose work you can review.
- Subscriptions using RevenueCat or similar tooling
- Teams testing paywall placement, copy, or trials
- Founders attaching revenue context to product tasks
How it works
The loop is the same across guides: connect evidence, let the agent read it, then ship a reviewed task with a verification metric.
- Track paywall views, skips, attempts, success, and failures.
- Compare behavior by onboarding path, release, and segment.
- Add RevenueCat trial, churn, and subscription summaries.
- Recommend one paywall change with risk and verification notes.
What you get back
The output should be concrete enough to review without opening five dashboards.
- RevenueCat is a core signal source.
- Paywall and purchase events in the SDK.
- Monetization evidence links to handoffs.
Common questions
Quick answers before you connect product data to an agent.
Should the agent optimize price automatically?
No—pricing stays human-reviewed; agents propose tests and evidence.
What paywall metric matters most?
Conversion—with trial quality, refunds, retention, churn, and feedback.
Can this use RevenueCat data?
Yes—RevenueCat summaries add monetization context.