Taap.bio

TrustMRR

taap.bio is a web-based link-in-bio platform. Users create a customizable public page that hosts all their links, social profiles and content, and share it from their social media bios. Access is sold as a self-serve subscription billed monthly or annually, which unlocks premium features such as advanced analytics, custom domains and additional design options. The free plan remains available with limited features. Customers are mainly individual creators, freelancers and small businesses worldwi

View on TrustMRRAug 10, 2026Analytics Software B2C

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Actual performance

14customers

$266MRR/mo

Did not reach leaderboard

Launch Intel predictions

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AppSumoStrong fit for a featured deal · Strong signals: platform, host, users · Missing: plus, intuitive, reviews

75%75% 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 · Strong signals: ios · Missing: supports, reddit linkedin, podcasting

68%68% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: ios, month, monthly · Missing: mobile apps, personal, entrepreneurs

56%56% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

37%37% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

25%25% predicted probability of success on Hacker News, based on ML models trained on real launch data.

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

23%23% 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

6%6% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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