StakeShare

TrustMRR

We believe the most passionate users and advocates should be able to share in the success of the companies they love. Traditional funding models are closed off, and influencer marketing lacks long-term alignment. StakeShare bridges this gap, turning creators from advertisers into true partners. For founders, we provide a powerful new channel for growth, driven by authentic advocates who are invested in your success. For creators, we offer a way to build a portfolio of equity in exciting startups

Visit product View on TrustMRRSep 13, 2025Fintech Consulting stripe

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Actual performance

Did not reach leaderboard

Traction signals

Domain Rating2

Launch Intel predictions

Analyze your own launch →

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

71%71% 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.

Product HuntOn track for Day 1 leaderboard · Strong signals: model, user, new · Missing: mac, agents, macos

66%66% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: users, way · Missing: mobile apps, ios, personal

32%32% 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

32%32% predicted probability of success on Hacker News, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: users · 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: growth · Missing: arr, mrr, revenue

18%18% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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