Quiz Maker AI

Quiz Maker AI

TrustMRR

Student/teachers tool for creating and learning with quizzes with proven product-market fit. 50+ organic daily downloads, recently optimized paywall showing improved conversions. Student/teacher niche

Student/teachers tool for creating and learning with quizzes with proven product-market fit. 50+ organic daily downloads, recently optimized paywall showing improved conversions. Student/teacher niche = evergreen demand. Includes: Full Flutter source code, Nodejs backend, all assets, Growth opportunities: TikTok marketing, Paid ads, social media marketing, desktop expansion (already seeing Mac users).

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Actual performance

77customers
$465MRR/mo
Did not reach leaderboard

Traction signals

MRR growth 30d+41.7%

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
82%82% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
TrustMRRFits verified-revenue profile · Strong signals: users · Missing: mobile apps, ios, personal
53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: mac, user, code · Missing: agents, macos, agent
31%31% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: growth · Missing: arr, mrr, revenue
25%25% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
21%21% predicted probability of success on Hacker News, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: paid · Missing: web3, chat, crypto
4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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