Content Creators

Content Creators

TrustMRR

We offer a digital educational course focused on creating short-form video content. Students receive lifetime access to training videos, learning modules, and digital materials inside our private onli

We offer a digital educational course focused on creating short-form video content. Students receive lifetime access to training videos, learning modules, and digital materials inside our private online platform.

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Actual performance

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
AppSumoStrong fit for a featured deal · Strong signals: platform, lifetime access · Missing: plus, intuitive, reviews
69%69% predicted probability of success on AppSumo, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
54%54% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: video, education · Missing: mobile apps, ios, personal
48%48% predicted probability of success on TrustMRR, 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: ide, io · Missing: https docs, excited, just released
29%29% 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
21%21% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: training · Missing: arr, mrr, revenue
19%19% 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
11%11% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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