ClassyAction

TrustMRR

Profitable iOS subscription app that helps users discover and file class action settlement claims they qualify for, many requiring no receipts. Curated database of 160+ active settlements

Visit product View on TrustMRRSep 15, 2025Mobile Apps Mobile App B2C

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Actual performance

129customers

$631MRR/mo

Did not reach leaderboard

Traction signals

Domain Rating1

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting

94%94% 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: ios, users, profitable · Missing: mobile apps, personal, entrepreneurs

73%73% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntOn track for Day 1 leaderboard · Strong signals: user · Missing: mac, agents, macos

53%53% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

44%44% predicted probability of success on BetaList, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: profit, profitable, subscription · Missing: arr, mrr, revenue

40%40% 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

35%35% predicted probability of success on Hacker News, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive

32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Incorrect prediction on native model

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