Admesio

Admesio

TrustMRR

Admesio helps app publishers unlock new revenue streams by connecting them directly with advertisers. Discover real partnership opportunities, increase your app’s visibility, and monetize smarter—with

Admesio helps app publishers unlock new revenue streams by connecting them directly with advertisers. Discover real partnership opportunities, increase your app’s visibility, and monetize smarter—without relying on traditional ad networks.

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Actual performance

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
53%53% 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.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
52%52% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: new · Missing: mac, agents, macos
39%39% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
BetaListMay not resonate with beta-testers · Strong signals: smart · Missing: web3, chat, crypto
37%37% predicted probability of success on BetaList, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
27%27% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: revenue · Missing: arr, mrr, profit
20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Correct prediction on native model

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