Griddd – Create a digital presence in minutes

Hacker News

I built griddd as an alternative to platforms like Linktree, Bento.me. It helps professionals and creatives showcase their work and personality through a single, elegant link. We'd love your feedback on the user experience and what features you think we should add next. Give it a try and let us know what you think! URL: https://griddd.co Early bird offer: The first 100 users get lifetime access to our Pro plan (exclusive early access to new features).

Visit product View on Hacker NewsJul 31, 2024

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Actual performance

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

82%82% 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: user, new, single · Missing: mac, agents, macos

72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: platform, exclusive, lifetime access · Missing: plus, intuitive, reviews

64%64% predicted probability of success on AppSumo, 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

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

nativeThis product was originally launched on this platform.

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

31%31% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

14%14% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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