Sociaaal · B2C · AI-native app studio
Run the same style of test ads for apps you might build or buy
Strong ad results count as a key data point in buy decisions; no numbers
Unknownvalidationpaid-socialportfolio
What they did
Combine a top-down market view (structure, willingness to pay, growth) with a bottom-up test: run ads for apps that don't exist yet or that are acquisition targets. Ads are highly standardized so results compare against a large internal benchmark. Then check the target's own ARPU, retention and marketing data.
What happened
Used as one strong data point for build/buy decisions.
In their words
The Superwall Podcast · Patrick Stuart-Constant & Pablo Sánchez - $16M AI CEOs: How to Make $1.3M/Month With AI Apps“But we also have a bottom-up approach where we'll run ads for uh apps which don't yet exist or that we're looking at buying. And if the ads perform well, and we've built quite a big benchmark and they're very standardized ads so that the data is as comparable as possible, then that would be another very strong data point.”
Related topics
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More from this episode
- Sociaaal: Buy apps that went viral and are now declining, then grow them againBought 6-year-old Celebs mid-decline; now bigger than ever, ~$300K+/month
- Celebs: Drop the paywall after onboarding; show the lookalike result fast and ask laterMore revenue per user; later paywalls converted the users who used to drop
- Sociaaal: Rerun old A/B tests that lost once the rest of the app has changedOnboarding paywall removal lost several times, then won big
- Sociaaal: Run about 100 A/B tests a month, starting small and scaling the winnersPortfolio ARPU roughly 3x in 18 months, 2x in 12; about 1 in 10 tests wins
- Sociaaal: Write down the reason behind every A/B test so AI agents can learn from it
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