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Islamic prayer and Quran app for Muslims to track prayer times, qibla, and daily spiritual reminders

Acquire.com

This is a subscription app serving the daily faith routines of the global Muslim community prayer times and Adhan, Qibla finder, full Quran with recitation and translations, lock-screen Quran and Hadith widgets, Dhikr counter, prayer tracker, Islamic calendar and a full suite of Ramadan tools. The app was launched in March 2024 and the owner has been scaling it with Meta ads.

This is a subscription app serving the daily faith routines of the global Muslim community prayer times and Adhan, Qibla finder, full Quran with recitation and translations, lock-screen Quran and Hadith widgets, Dhikr counter, prayer tracker, Islamic calendar and a full suite of Ramadan tools. The app was launched in March 2024 and the owner has been scaling it with Meta ads. The app has a proven ability to scale with paid UA. During a paid acquisition push in early 2026, monthly proceeds...

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Actual performance

Did not reach leaderboard

Traction signals

Asking price$300,000

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
74%74% 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: month, monthly, widgets · Missing: mobile apps, ios, personal
71%71% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: subscription · Missing: arr, mrr, revenue
30%30% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
28%28% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
28%28% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: paid · Missing: web3, chat, crypto
18%18% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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