How I Built Multiple $1M+ ARR Product

Dump every idea into a Notion table. Score interest, expertise and opportunity; a formula averages them and you pick the highest. Opportunity gets a point each for: demand, revenue proof, a balanced competition level (too little = no market; only one successful product is a red flag), retention (solves a real problem or truly entertaining) and timing (new platform features, new models, social trends). Expertise scores 1-4 on: can I build it, can I market it, do I understand the product, can I monetize it. Research with Foreplay, AdSpy (competitor Meta ads), Sensor Tower, Appfigures, Google Trends and TikTok view counts for keywords; validation usually takes no more than about a week.

When Apple released home-screen widgets with iOS 14 there was a boom in widget apps; the team executed fast and threw all its marketing expertise at the opportunity. Same pattern: when the ChatGPT API launched there was no official ChatGPT iOS app, so apps ranking for 'ChatGPT' searches made good revenue. BeHard similarly monitors social media for new challenge trends.

Pick the top-scored idea and build it in a week, removing anything that would take too long. BeHard's first version was a bare challenge list (first workout, second workout, 10 pages). Use AI coding agents (carefully with autonomous ones); an 'agent factory' could test many ideas before investing human time.

Challenges were already popular: many people posting on TikTok and searching Google and the App Store. First campaigns aimed to capture a slice of that traffic via organic (ASO, TikTok) plus Apple Ads. Phase two was influencer marketing; phase three paid ads to reach $1M ARR. Guest warns Apple Ads is hard to scale profitably in competitive categories, and ASO alone is rarely viable unless validated before launch.

UA managers ran TikTok influencer campaigns. While daily downloads are small, attribute each video by the traffic peak: note the post day (e.g. Wednesday), then that day's downloads and sales. At high install volume this becomes nearly impossible. Once a creator performs, sign a long-term deal. Discount codes capture only ~10-20% of influenced users; measure the code rate on early campaigns and model future ones from it.

Founder, who built the app for himself after reading David Goggins, posted on TikTok and Instagram about going through the challenges, with little money at the start. Suggests AI-generated talking-head videos of your own face for cheap testing.

Founder made the first screenshots himself in a couple of days. Designers then spent 2-3 weeks on 'perfect' screenshots, and a hired agency produced five variations; both performed worse than the founder's set in store tests.

Treat launch as the first experiment. If it isn't profitable, decide if it's a distribution or product problem (get traffic to the current version before improving the product). Find the bottleneck (CAC too high, low conversion, low LTV, low ad CTR), design an experiment for it, run it, analyze. If profitable, scale until it stops being profitable, then repeat. Start pricing by copying competitors. To force-test a creative Meta/TikTok won't serve, put it alone in its own campaign with a fairly high budget.

App Masters' 'lifetime free' growth hack applied to an AI notetaker app that already had demand, revenue proof, moderate competition and good timing. Host stresses it only took off because those opportunity signals were present; it doesn't work for every app.

Host checks App Store search demand before building, then builds a simple app to match; downloads came immediately, but monetization lagged and had to be tested.

After struggling to monetize the app, tested plan lengths and found weekly plans worked better than yearly.

End-2023 self-challenge: shipped the blandest screenshots (literal screens of the app) and basic features, and only tweaked ASO to fix distribution rather than testing screenshots with no downloads.

Posted many organic social videos for a utility app. Both speakers conclude organic social needs an inherently interesting, shareable product (Cluely, Rizz) and videos about the product itself, not just trends.

Tried long-tail exact-match keywords on his own app; they lacked volume. Instead, raise exact-match bids a lot (aim for ~90% impression share, as John of Momingo did) to see how the core keywords really perform.

Client spending $60K/month on Apple Ads had only two exact-match keywords (and variations) converting well; App Masters moved to what it calls a 'basic-plus' campaign.

Changed the email subject line from 'The benefits of HIIT workouts' to 'Our most popular workouts'. Host suggests the same popularity framing ('Popular tours') for other apps.

Founder Ethan started creating content to validate the idea before building the app.

Rather than month-one ROAS (spent $1,000 this month, made how much this month), evaluate how much a cohort makes within three months against CAC, which allows paying a higher CAC.

For faster Android results than ASO: run Google UAC campaigns targeting a specific market, then use target-ROAS campaigns since Google knows who converts. Pair with keyword-left titles and custom store listings per keyword for Google Play ASO.

A past guest found podcasters in his niche (they understand affiliate deals and want to monetize), built his own tracking down to the sale, and paid them out per sale. App Store Connect offer codes can also be used to track each influencer and give their audience a discount.

Order: paywall -> sign-up -> payment screen. Forcing account creation before the paywall stops most people from paying.