Francopass

Francopass

TrustMRR

Francopass is a mobile/web app (iOS & Android & Web) that helps immigrants prepare for the French naturalization interview and civic exam. It includes structured revision courses covering French histo

Francopass is a mobile/web app (iOS & Android & Web) that helps immigrants prepare for the French naturalization interview and civic exam. It includes structured revision courses covering French history, institutions, republican values and culture, 200+ interactive quiz questions from real interviews, audio books for on-the-go learning, and the official citizen booklet built in, with thousands of users already prepared and passed.

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Actual performance

124customers
$1,397MRR/mo
Made the leaderboard

Traction signals

Domain Rating1
MRR growth 30d+38.8%

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting
85%85% 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 · Missing: mobile apps, personal, entrepreneurs
67%67% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
51%51% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: user · Missing: mac, agents, macos
43%43% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue
30%30% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: audio · Missing: web3, chat, crypto
4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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