A/B testing tactics

A/B tested a priming screen right before the paywall with the mascot bee: 'We want you to try Sunflower for free. We'll remind you before your trial ends,' then shows the paywall. Addresses trial anxiety. Tested a couple of versions of the screen.

A/B test, half of users each: in-app purchase only vs. web checkout only. Iteration 1: paywall button sent users to the web. Iteration 2: in-app paywall with package selection (monthly/annual, via RevenueCat) and a 'Start Today' button; the tap opens Safari to a stripped-down Stripe page showing only the chosen plan, styled like Apple's in-app purchase sheet, then auto-redirects back into the app. No extra discount for paying on the web, to protect LTV. Next ideas: let users choose web or in-app, and route only high-intent placements (e.g. after the welcome class) to web.

A/B tested one extra screen at the end of onboarding where the user commits/signs that they will work out, against control. Tracked in PostHog.

Three tiers (Silver, Gold, Platinum); most users pick Gold and the paywall can't explain everything, so it normally leads with Gold. A machine-learning model using ~900 data points per user (profile, behavior, previous experiment results) predicts propensity to buy Platinum (wider roadside assistance range, identity protection, more services). High-propensity users are shown Platinum instead of Gold. Part of an ML targeting/orchestration layer built in the last year that also targets promotions, feature education, push notifications and in-app messages.

Previously users finished onboarding and entered the app (home screen, pick a scan / swipe on jobs) and were paywalled at the first valuable action. Tested a complete hard paywall straight after onboarding, with no access to the app. Sprout also switched to a hard paywall and saw better conversion.

After iterating one or two onboarding screens at a time (small wins, hard to make big progress), they made one big jump: from ~5 to ~13 screens ending in the paywall. Added screens include login, notification permissions and mostly personalization (what the user is studying). Login was moved to the last screen, after the paywall.

Tested reducing the free trial from two weeks to seven days in several combinations with how many trials a user is eligible for. Beyond conversion, the shorter trial means experiment readouts come in 7 days instead of 14, so losing tests are killed sooner and more tests run per quarter.

Originally the first paywall screen showed yearly and monthly plans side by side. The test moved the monthly plan under a 'view all plans' button so it wasn't visible at first glance, leaving the yearly plan as the default.

Content is organized like Meta ads: campaigns, then 'playbooks' (like ad sets), then posts. Each playbook gets one to three weeks of tweaks to the prompts given to posters. If nothing pops, pause it and slot in a new idea. Example: a playbook with 446 posts in about a week (~200K views) was paused and replaced with 'how are we making money by Christmas'.

Curiosity Quench originally sold confusing 'Quench credits' in a shop that users had to find themselves. Jack first added a RevenueCat paywall, which he found clunky and hard to customize, then moved to Superwall templates (adding his logo, colors and one asset) with a free-trial option. Over 3-4 months he tested headers, copy and which features to gate, looking at dollars per user.

In 2018 Tinder A/B tested a toggle in the app's top navigation bar that let users enter a new subscription tier directly. Treated as a small-to-medium 'throwaway' test on the experiment roadmap; the design team opposed adding the top nav. Result was read off the daily revenue dashboard. Guest's broader advice: audit where users can reach premium features and add more prominent paywall entry points; don't bury them in the nav.

Launched at $6.99/month without much research. As soon as RevenueCat Experiments came out, tested many monthly prices from $4.99 up to $19.99. $12.49 had the highest LTV lift; $14.99 was slightly higher but they chose $12.49 to keep reach broad because parent-to-parent word of mouth matters in kids apps. Ran look-backs over multiple years: some higher prices gave an early LTV boost that did not hold.