Qu
Quit All, an iOS app with an SOS mode for cravings
Hacker NewsQuit All, an iOS app with an SOS mode for cravings
I built Quit All, an iPhone app for breaking bad habits. The main idea is that most habit trackers help after relapse, but cravings happen before that. Quit All has an SOS mode with a timer, GIFs/prompts, streak tracking, relapse logging, savings, milestones, danger-time stats, and iOS widgets. YouTube demo: https://www.youtube.com/watch?v=qwNK4rqOY88 App Store: https://apps.apple.com/us/app/quit-all-break-every-habit/id6760978934 Website: https://quit-all.com
Share cardActual performance
3points
2comments
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting68%68% 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, apps, widgets · Missing: mobile apps, personal, entrepreneurs60%60% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released51%51% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntUnlikely to reach the leaderboard · Strong signals: apple, apps · Missing: mac, agents, macos48%48% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue28%28% 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, crypto2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
Similar products
Bu
Built my first iOS app to quit smoking29%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Built my first iOS app to quit smoking
Hacker News1An
AnimalSoundFun – My first iOS app34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
AnimalSoundFun – My first iOS app
Hacker News1Tr
Trident for GitLab – iOS App29%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Trident for GitLab – iOS App
Hacker News12Da
DataTau iOS App34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
DataTau iOS App
Hacker News6Sw
SwipeVideo, my first iOS App34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
SwipeVideo, my first iOS App
Hacker News15Th
Thinglist, my first iOS app34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Thinglist, my first iOS app
Hacker News2My
My iOS app to cure boredom34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
My iOS app to cure boredom
Hacker News6My
My first iOS app - PostParty34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
My first iOS app - PostParty
Hacker News1Ne
Never-Bored - My first iOS App34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Never-Bored - My first iOS App
Hacker News15Yo
Yourtaximeter iOS App34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Yourtaximeter iOS App
Hacker News4