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TL;DR
Steven Cravotta studied 100+ AI apps doing millions/month and found they win on marketing, not product, via one repeatable method: market research → scale with creators → optimize the conversion funnel → scale on paid ads. The companion to the “how they’re printing” study.
The single most important idea
- The more money you make per user, the more you can spend on content and ads. That’s why big apps out-acquire you — they convert better, so they can outspend. Optimize your whole funnel (ad → App Store listing → onboarding → paywall) or you’ll never market like them.
The four-part method
- Market research — Sensor Tower (only learn from apps doing >$50k/mo), then search your niche organically on TikTok/Instagram, plus Viral Ads Library, Facebook Ads Library, TikTok Ads Library. Save everything to a spreadsheet (URL, likes, views, even transcripts).
- Scale with creators — influencers are fast but expensive; better to be scrappy and hire results-only creators on Posted (CPM with deep analytics like first-opens). Build a consistent team; protect ROI with CPM/view-guarantee deals. Repost across every channel.
- Optimize content & profile — pin top-download videos; clean bio → App Store link (Resume $500k/mo, Puff Count). Sneaky CTAs, sell the outcome; engage comments; reply-to-comment videos ride viral traffic (Puff Count’s 8.4M-view video was a reply).
- Scale on paid ads — need ≥20 quality creatives first; optimize for money events (trial starts / subscriptions, not just clicks); keep CAC < LTV (RevenueCat realized-LTV-per-install ≈ $1–$1.50 for Puff Count); test creatives in mass, then rinse and repeat.
Related
- app-market-research · creator-content-engine · paid-ads-scaling
- mobile-app-monetization · studied-100-viral-ai-apps-printing · steven-cravotta