We started running pricing and offer tests on our web paywall to see what stuck. The goal wasn’t just conversion but retention. A cheaper introductory price pulled more signups but those users churned faster. A modest discount with a longer commitment gave slightly fewer signups but much better 30‑ and 90‑day retention.
We tracked trial-to-paid, 30‑day retention, and LTV per price cohort and changed offers every 3–7 days.
Has anyone balanced short‑term conversion lifts with longer term churn when testing paywall offers? What metrics did you lean on?
We tested 3 price points quickly on the web instead of waiting for an app update.
Lower price increased installs but cut 90‑day retention. We rolled the better LTV price to full traffic.
I used Web2Wave.com to spin up the variants and measure cohort LTV.
I always look at 30 and 90 day retention, not just initial conversion.
On the web you can launch price variants in hours and see cohort behaviors. We paused a high-conversion offer when its 60‑day churn was much worse.
Fast iteration wins here.
We learned to track ARPU by cohort.
If the cheaper offer brings many low‑value subscribers it’s not worth it. I usually wait 30 days before calling a test.
test price then watch retention
dont trust day 1
Short answer: yes, if you pair pricing tests with proper cohort tracking. Run price offers on the web, tag each cohort, and measure conversion, 30/90 day retention, and repeater revenue.
Avoid changing multiple levers at once. Test price only or price plus a single onboarding tweak. If an offer inflates trial starts but depresses retention you can calculate net present value per cohort and decide whether higher short-term conversion is acceptable.
We tried an ‘annual at 40% off’ vs monthly promo. Annual converted less but LTV per user was 3x after six months.
Timing the offer after a short trial helped too.
Also test messaging. Same price framed as “limited offer” performed differently than “intro price”. People react to scarcity and clarity differently across channels.
I usually give each price test at least two full billing cycles.
That avoids false positives from initial curiosity.
If you can, route a small % of high quality ads to the new price first.
You’ll see if channel mixes change LTV.