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Quick Cursor: One-Handed Mode for Android Devices

Hacker News

Quick Cursor: One-Handed Mode for Android Devices

I've just released the first public stable version of Quick Cursor. You can find it on Play Store: https://play.google.com/store/apps/details?id=com.quickcursor Some interesting statistics after one year of beta "early access": - 130.938 installs - 12.576 active devices - 4.112 euros sold on Play Store - 3.350 telegram messages - 2.639 euros after taxes - 1.759 pro users - 890 beta reviews - 786 feedback emails - 563 GIT commits - 297 debug screenshots on Telegram - 200 Reddit comments - 118 Tweets - 109 debug screenrecords on Telegram - 105 Telegram channel members - 100 XDA messages - 96 app updates - 92 bugs fixed - 36 testers - 15 Youtube videos presenting the app - 10 languages and translators - 0 ads shown I hope you find it useful and I'm waiting for feedback and questions.

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Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
73%73% 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.
Product HuntOn track for Day 1 leaderboard · Strong signals: cursor, google, apps · Missing: mac, agents, macos
51%51% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: reviews, users · Missing: plus, platform, intuitive
47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: just released, ide, io · Missing: https docs, excited, exist
36%36% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: apps, video, google · Missing: mobile apps, ios, personal
34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · 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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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