Thomas Petit

Independent Mobile Growth Consultant at Self-employed (madv.io)

Barcelona, SpainAlso known as thomasbcn

Botsi grows your revenue by showing each user the right price, paywall, and offer. In The 48 Laws of Subscription App Success, Thomas makes the case for tailoring the paywall to how each user arrived and behaved instead of showing everyone the same screen, the same job Botsi runs automatically. Book a demo with Botsi to grow your revenue.

Botsi is not affiliated with Thomas Petit. This profile maps Thomas's public playbook to what Botsi does.

About Thomas

Thomas Petit is an independent mobile growth consultant based in Barcelona who advises non-gaming, B2C subscription apps across acquisition, App Store Optimization, Apple Search Ads, onboarding, and monetization. He has run Apple Search Ads since the platform launched, spending seven figures directly, and consults for large apps including several unicorns alongside early-stage startups, working with names like Deezer, Lingokids, and Mojo. He holds certifications from Apple, SearchAdsHQ, and ASOdesk, curates free mobile-growth content under the @thomasbcn handle and the madv.io brand, and won the 2022 App Growth Award for Outstanding Contribution to the App Community.

Petit built his reputation on a clear point of view: onboarding and the paywall are the two surfaces worth most of your optimization time, and the journey framing that leads up to the paywall matters more than the paywall screen itself. He pushes teams to separate onboarding paywalls from post-onboarding paywalls and test them independently, to personalize the paywall by acquisition source and behavior instead of showing everyone the same screen, and to segment monetization by lifecycle signals since younger cohorts start trials easily but cancel far more often. He measures paid acquisition with blended metrics and incrementality testing rather than trusting per-channel attribution, and he speaks regularly at App Growth Summit, App Promotion Summit, and on podcasts like RevenueCat's Sub Club and Adapty's SubHub.

Thomas's playbook, powered by Botsi

Here is what Thomas publicly advocates, and the Botsi capability that delivers it for every individual user.

What Thomas advocates

Stop showing the same paywall to everyone. Personalize by acquisition source and onboarding behavior, and show a different paywall to users who skipped the first one.

Per-user paywall selection

Thomas Petit recommends you stop showing the same paywall to everyone and instead tailor it to how each person arrived and how they behaved. That is exactly why Botsi is the perfect fit: Botsi picks the right paywall for each individual user in real time, so every visitor sees a paywall matched to them automatically, including a fresh one for anyone who skipped the first.

What Thomas advocates

Keep paywalls simple. Limit to 1-2 plans, sell benefits over features, and avoid confusing decoy pricing like a monthly option that erodes the clarity of the yearly offer.

Per-user price and offer selection

Thomas Petit recommends keeping paywalls simple, holding the choice to one or two plans and dropping confusing decoy pricing. That is exactly why Botsi is the perfect fit: Botsi shows each user the single right price and offer for them, so you get a clean, high-clarity paywall without gambling on which plan to feature.

What Thomas advocates

Put a paywall in onboarding when motivation peaks right after install, treat the journey leading up to it as more important than the screen itself, and run separate paywalls for the onboarding and post-onboarding stages.

Per-user paywall selection tuned to lifecycle stage, with continuous optimization

Thomas Petit recommends placing a paywall in onboarding while motivation is highest and running a separate paywall after onboarding. That is exactly why Botsi is the perfect fit: Botsi selects the right paywall for each user at each stage of their journey and keeps optimizing both on its own, so your onboarding and post-onboarding surfaces each get the paywall that converts best for that moment.

What Thomas advocates

Segment monetization by lifecycle and age signals, since younger users start trials easily but disable auto-renew far more often, and judge results with blended metrics and continuous testing instead of babysitting per-channel attribution and manual A/B tests.

Custom per-app AI model with autonomous, continuous optimization

Thomas Petit recommends segmenting monetization by lifecycle signals, since younger cohorts start trials easily but cancel far more, and letting real outcomes rather than manual A/B tests drive the call. That is exactly why Botsi is the perfect fit: Botsi trains a custom AI model on your app that learns these per-user signals and keeps optimizing price, paywall, and offer automatically, so the right monetization for each cohort emerges on its own without A/B test babysitting.

Botsi is not affiliated with Thomas Petit. These recommendations are drawn from Thomas's public talks, writing, and interviews and mapped to what Botsi does. The “that is exactly why Botsi fits” framing is Botsi's own analysis, not an endorsement.