Idea validation tactics

'Proof of pay': ship a real app with a simple onboarding and a hard paywall showing one offer, submit every price you want to test up front, and run Apple Search Ads at the same daily spend (~$1K/day to learn fast; far less works over a longer period). Change only the lifetime price, walking it up: $4.99, $9.99, $29.99, $49.99. Read results directionally (day-one revenue per user), not for statistical significance. If you can't get past ~$4.99, drop or change the concept.

Added a button in the product UI with a rainbow border: 'Book a call with the team if you want 7 days of extra access.' It linked straight to the founders' Calendly. Both co-founders took ~20 calls a week every week since August 2025, interviewing users with a prepared question list, with an AI note-taker on each call.

1) Search the US App Store (on a phone; the web doesn't show long-tail suggestions) for a topic you understand and can build for, e.g. 'calories'. 2) Note autosuggest long-tail terms; ignore new apps' names that appear there briefly. 3) Check whether other apps already own the keyword in title/subtitle, or whether it's a brand term. 4) If US popularity is low (e.g. 5) but Apple suggests it, assume it's searched elsewhere: find the top-ranking app for it and see where it gets its ratings/installs. 5) Deep research with Claude connected to Astro via MCP (his own skill): popularity and difficulty per country, related keywords, competitors per country; ASOMobile shows whether anyone bids on the keyword in Apple Search Ads. Many related keywords with demand is a good sign. Then build, with country-specific titles/subtitles mixing native and English keywords. Example: 'kanji' has popularity 7 in the US but 73 in Japan; 21 of 22 Japanese-learning keywords score better outside the US.

Define a 'commitment metric' for yourself and for users. For yourself: a specific date and a number (customers, clients, etc.) you must hit by then, so validation has a fixed time box. For users: the signal doesn't need to be payment, but must represent real usage; for Once it was event hosts agreeing to use the product at an actual dated event in front of friends and family, treated as nearly a proxy for payment. Their bar: 10 events with a real date and commitment before writing a single line of code.

Used ChatGPT to make a one-page HTML site (runify.xyz) with a one-sentence pitch and rank images. Two options: pay $5 via a Stripe link to become an 'early adopter' (lifetime subscription once live) or join the email waitlist. All Reels traffic pointed there.

After reading reviews where users asked to pay to remove ads, tested a one-time purchase of 30 ad-free days at $3, $5 and $10 instead of a subscription.

Each post centers on a video demo of one feature, wrapped in a problem-solution or story frame: 'me or my friend was facing this problem, so I built this feature to solve it. See, this is how it works. If you want to try, you can try it for 30 days for free. I'm just looking for feedback...'. Show, don't tell; explain the reasoning like talking to adults, no blatant self-promotion. Used to test the new Super Brain feature, whose feedback and feature requests made it the primary feature. Expect hate and bans; keep backup accounts and develop thick skin.

Hook: 'What if you could stop your doomscrolling addiction by doing 20 push-ups?' Make it clear enough for a 5-year-old, with a curiosity gap (what do push-ups have to do with doomscrolling?) and novelty. Show the value, not the build: used an AI push-up detection clip found on YouTube, a shot of placing the phone against the wall, then the scrolling part. End with a strong call to action asking whether they should build it. Make the video good, or you can't tell if the idea or the video failed. Pick ideas with one strongly visual element, explainable in three words, solving a fundamental human desire.

Starts from search terms users type when they have a problem. In Astro, create a temporary app, pick a random category or something he wants to build, add a seed keyword (e.g. 'tree identifier'), pull related apps and their keywords, then filter: popularity at least 20 and difficulty at most ~60-70 (e.g. 'wood identification': decent popularity, very low difficulty). Select the target keywords, then check top competitors' monthly revenue in Sensor Tower, the App Store or similar; skip the market if they make less than $100-200/month.

After mocking up the product, offered 50 lifetime licenses at an 'absurdly low' price. The first 10 were cheapest and the price rose for each following batch of 10 to create FOMO. An offer so good people say yes, even if the first 10 were not profitable. Money-back guarantee: buyers could ask for a refund at any time; product promised within 60 days, then 2 more weeks to try it and request a refund. Treated a sell-out as validation.

Took an unused poster design made for a client, put it on a poster mockup (posters were easy to source fast, which matters with TikTok Shop's two-day delivery), listed it on TikTok Shop and made one video with AI (ElevenLabs voice + Midjourney images). When it got 3 sales, he left a $100 deposit with a local print shop so they would print on each call and bill his card afterwards.

Brain-dump features and competitors into a Google Doc, noting competitors' features, onboarding and UI. Sketch the app with pencil and paper, upload the sketches with the premise and feature list to 99designs, and get 50-70+ UI designs submitted. Hire a developer on Upwork (he recommends only Eastern Europe for quality at a lower price) after a 15-minute call checking vibe, excitement and whether they bring ideas. Pay per completed project, not hourly: paid when the app is live on the store with no bugs. A simple app like Puff Count cost under $5K; a ThemeForest template can get it under $1K. Keep the MVP simple.