BuildBid

TrustMRR

BuildBid is a public pay-to-rank leaderboard for startups and agencies. Listings start at $1, and each new top spot costs $1 more than the current highest bid. Visitors can discover ranked products, track live bids, and visit each listing directly. Sponsored placements offer guaranteed visibility.

Visit product View on TrustMRRAug 23, 2026Community Other B2B

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Actual performance

Did not reach leaderboard

Traction signals

Domain Rating2

MRR growth 30d-81.1%

Launch Intel predictions

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

77%77% 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.

BetaListSuited for BetaList early-adopters · Strong signals: discover · Missing: web3, just like, small businesses

70%70% predicted probability of success on BetaList, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: new · Missing: mac, agents, macos

38%38% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Missing: https docs, just released, open source

28%28% predicted probability of success on Hacker News, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: reviews, intuitive, videos

15%15% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: agencies · Missing: api, 000, profitable

11%11% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Correct prediction on native model

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