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BestPick – Free AI selector for your best profile photo for social

Hacker News

BestPick – Free AI selector for your best profile photo for social

Hi HN, I’m Saad and I built BestPick.online. We made this because your profile picture is often your first impression — whether you're on a dating app, LinkedIn, Instagram or building a personal brand. :contentReference[oaicite:1]{index=1} Here’s what it does: - Upload 2-3 photos of yourself. :contentReference[oaicite:2]{index=2} - Choose the goal (dating app, professional, social, etc.). :contentReference[oaicite:3]{index=3} - The AI instantly rates them and shows which one works best for that goal. :contentReference[oaicite:4]{index=4} We believe: - Different platforms need different kinds of photos (approachability on Tinder vs authority on LinkedIn). :contentReference[oaicite:5]{index=5} - Everyone should be able to make a data-driven decision rather than just guess. If you have a moment, I’d love your feedback: • Did the recommended photo feel right to you? • What additional goals or platforms should we support next? • Any biases or surprising results you found? Thanks for your time — happy to share more about how the AI works if you're curious. Saad

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
86%86% 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.
TrustMRRFits verified-revenue profile · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs
58%58% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
43%43% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
33%33% 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
26%26% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · 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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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