We started offering more flexible refund windows and a web-based win-back flow after users cancelled. The idea was to repair the relationship directly rather than relying on app-store processes.
We personalized offers on the win-back page and used the checkout to apply tailored discounts. That reduced churn on the 7–14 day window and nudged some users back without eating into margins too much.
Has anyone run a win-back page with custom refund rules? How did you measure its effect on long-term value?
We built a simple win-back page and automated a one-click refund flow for certain cases.
It saved hours of manual support and let us test small offers quickly.
We saw a handful of users re-subscribe at a higher LTV because they stayed longer after reactivation.
Flexible refunds and a web win-back flow were game changers for us.
We used conditional discounts on the page and tracked revenue per recovered user. The recovered cohort had better LTV than the average churned user.
Having refunds handled outside the app cut friction and let us experiment with offers fast.
We tried offering a one month free extension on a web win-back page.
A small portion reactivated and many stayed beyond the promo. It beat a blanket refund policy for our use case.
win backs work
track post rejoin value
Treat refunds and win-backs as tests. Design a win-back page with clear options: discount, pause, or extend trial. Segment the recovered users and measure their 30 and 90 day retention against control groups.
Flexible refunds reduce friction and provide data on what it takes to keep marginal users. Over time that informs pricing and onboarding changes that lift LTV across cohorts.
We saved refunded users into a test cohort and tried different offers.
Best result was a small discount plus an onboarding email sequence. Recovery rate rose and LTV improved slightly.
I found targeted offers on a web page worked better than blanket refunds.
Measure recovered cohort retention to be sure it’s worth it.