Sociano

TrustMRR

iOS app that helps people reduce social media use without deleting it. Users can block Reels, Shorts, feeds, or entire apps, set daily limits, schedule focus time, and track screen time while keeping

iOS app that helps people reduce social media use without deleting it. Users can block Reels, Shorts, feeds, or entire apps, set daily limits, schedule focus time, and track screen time while keeping access to messages, search, and posting. Not just an ordinary app blocker.

Visit product View on TrustMRRMay 5, 2026Productivity Mobile App B2C

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Actual performance

17customers

$61MRR/mo

Did not reach leaderboard

Traction signals

MRR growth 30d+357.4%

Launch Intel predictions

Analyze your own launch →

TrustMRRFits verified-revenue profile · Strong signals: ios, apps, users · Missing: mobile apps, personal, entrepreneurs

79%79% 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: apps, user · Missing: mac, agents, macos

76%76% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Strong signals: ios · Missing: supports, reddit linkedin, podcasting

36%36% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

33%33% predicted probability of success on AppSumo, 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

29%29% predicted probability of success on Hacker News, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

26%26% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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