Founder Playbook · Sub Club by RevenueCat
12 tactics from Francescu Santoni
Growing to $1M MRR with Paywall and Pricing Experiments
Watch the full episode“the first actual like big experiment that we had was like the onboarding paywall and I think it accounts for most of the trial even today”
Move paywall to end of onboarding first — it drives most trials
Mojo's first meaningful monetization experiment was simply moving the paywall to the end of onboarding rather than deep in the app. Apple's App Store team flagged this directly — the paywall was not being shown early enough. This single placement change now accounts for the majority of Mojo's trials. Before iterating on paywall design or pricing, get the position right.
“we were super lucky at some point to hire someone dedicated to monetization mik... he has really like this data mind... all experiment and this is working very well”
One dedicated monetization person beats a committee
Mojo grew to $1M MRR with a team of 30, allocating just one person full-time to monetization, paywall, pricing, and onboarding experiments. That focus enabled quarterly iteration cycles: paywall position, then full redesign, then localization, then price testing. Spreading monetization across multiple part-time owners produces none of these results.
“ARPU increased like in the range of plus 50% at some point so yeah it had like a huge impact... Mikel had a test like a few weeks ago that we roll out with like plus 100% there ARPU because inflation”
Price increases drove +50% ARPU — one market got +100%
Systematic price testing lifted Mojo's ARPU by more than 50% across the board. One specific market had seen subscription prices eroded by local inflation without any adjustment, and a targeted +100% price test there lifted per-user revenue dramatically. Inflation silently eats relative pricing and most apps never catch it without dedicated monitoring.
“until like several hundred thousand per month we spend zero dollar in ads why because we invented basically the animated posters in stories... people were just referring the app without any like referral mechanism”
Product virality funded early growth: zero ad spend to hundreds of thousands/month
Mojo reached several hundred thousand monthly users spending nothing on paid acquisition. The product itself was shareable: Mojo invented the animated Instagram story poster format, so every post was a walking ad. Users were DMed by friends asking how they made it. Organic referral built entirely through product output, not a bolted-on referral program.
“we did the campaign it was like a fail small spike and this but a few weeks later we got the initial spar enough and it's still among of top five even top three countries nowadays”
Influencer seeding in one market created a lasting top-3 country
Mojo ran an early influencer campaign in Brazil that looked like a failure — a small spike and then nothing. A few weeks later organic momentum took hold, and Brazil became a persistent top-3 market. The campaign seeded cultural awareness that organic growth then compounded. Short-term ROI measurements would have written it off as a loss.
“product-led growth is always kind of shiny you mean just make the product better and they will come right... if you're like a business person accept it and work on paid and make that the best LTV on CAC”
Don't fall into the product-led growth trap if it's not your DNA
Francescu warns against chasing product-led growth as a default because it sounds noble. If an app doesn't have an inherently viral distribution loop, spending six months on a referral feature won't change that. Know your actual growth DNA and invest in the engine that matches it, whether that's paid acquisition, paywall optimization, or built-in sharing.
“we didn't even had like a nonpaying paywall for a few years because what we wanted to measure is the actual interest... a dollar is a dollar right like if you can capture a dollar you've captured something measurable and real”
A dollar subscription on day zero is the best signal of real value
Mojo launched with a subscription from day one — not because the product was finished, but because charging any amount of money produces a signal you cannot fake. Free installs can hide weak product-market fit; willingness to pay reveals it. Francescu launched with a 30-day free trial at $10/month and celebrated when someone from an unknown country converted on launch day.
“you're going to have complexity choose your complexity and you want to choose that complexity based on leverage”
Choose your complexity — prioritize high-leverage hard problems
Mojo skipped CRM entirely at $1M MRR — not because email is unimportant, but because CRM across a multi-language user base is low-leverage complexity. Instead, resources went into the high-leverage complexity of building AI into video creation. The principle: every decision adds complexity; deliberately choose complexity where the potential leverage is highest, and be explicit about what is being deferred.
“if somebody isn't mad at you about your pricing your pricing is wrong right like if you make everybody happy you're definitely under pricing”
If nobody is angry at your price, you are undercharging
Pricing that angers no one signals you have left money on the table and also signals low perceived value. A Mojo user once complained the app should charge more so fewer people would use the top templates, preserving exclusivity. Some price anger is the correct outcome; the skill is choosing which users you price out and why.
“we gave up in a way that we don't do like predicted LTV and stuff we push a lot more the yearly plan to make that much easier so the idea being it's like you can get the payback on a cohort”
Push yearly plans to simplify attribution without fingerprinting
Post-ATT, Mojo abandoned complex predictive LTV modeling and instead aggressively pushed annual plans so payback period fits inside a 30-day cohort window. Attributing annual subscriptions to their acquisition cohort by country becomes tractable even without fingerprinting. Simplifying the subscription structure resolves the attribution problem without needing expensive measurement tech.
“first is like position of the paywall two is totally different paywalls just try different pays... then with done that a bit more localized also into different countries... big layer change when one paywall is working you can do like smaller change within that and then you do price testing”
Iterate paywall in layers: position first, then design, then localization, then price
Mojo's paywall optimization ran as a deliberate sequence: nail position, then A/B full paywall concepts (video vs text, simple vs scrolling), then localize for key non-US markets, then run price tests within the winning concept. Running all these variables simultaneously creates noise. Each layer must stabilize before the next test layer begins.
“us is like a third of revenues only number one country yes but just a third so then you always have to think about all the countries”
US is only one-third of revenue — design globally from the start
Even though the US is Mojo's single largest market, it accounts for only one-third of revenue. The European founding team treated internationalization as default from the start rather than a growth hack added later. This means paywall localization, regional pricing experiments, and market-specific influencer campaigns were part of the core growth process, not afterthoughts.