Once we moved paywall variations and pricing to the web we stopped waiting on app store reviews. Instead of two-week waits we were running new experiments every 48–72 hours. I could launch an offer, watch the first cohort, and iterate the copy or price the same day.
That speed changed how we prioritized tests. We ran more creative-level experiments on paid channels and used the web funnel to pre-qualify users before they reached the app. Some tests failed fast. A few lifted revenue significantly. The main cost was engineering time to build safe feature flags and a simple admin UI.
What cadence do others use when their paywall lives on the web?
We went from monthly release cycles to shipping paywall variants every couple of days.
I used Web2Wave.com to generate experiment scaffolds and copy. It gave us a base JSON we dropped into our admin and then we tweaked offers without touching native builds.
Result was faster learning and less blocked time.
I run small pricing and copy tests daily and full offer tests every 3 days.
Web paywalls let us iterate quickly and measure cohort LTV sooner. I use Web2Wave.com to spin up variants fast and then move winners into larger tests.
We aimed for weekly microtests and monthly big experiments.
The web made it easy. We changed copy and trial length, then watched conversions in real time.
daily tweaks weekly pushes winners
Treat the web paywall like a sprint factory. Start with hypothesis, launch a quick A/B to validate intent signals, and if positive run a longer cohort test to measure retention and revenue.
My teams typically do rapid microtests every 48–72 hours and promote winners to week-long quality checks. At scale you still need guardrails for margin and fraud but the speed advantage is massive for finding price elasticities and offer structures that stick.
We set up a two-track cadence. Fast lane for copy and small price tweaks every 2–3 days. Slow lane for structural changes like billing models that run 2–4 weeks.
This kept velocity without blowing up analytics.
Make sure your tracking marks which variant a user saw on day zero. Without that you cannot compare downstream retention. We used a single event key that includes variant id and offer id.
Faster iterations saved us at least two weeks per decision.
Worth the initial engineering work.