Shop Clothes with Models That Match Your Body Shape

Hacker News

This is one of those fix a problem you can’t ignore projects. Like most online shoppers, I often found myself frustrated: clothes look great on models but disappoint when I try them on. It’s not the clothes, it’s the body shape mismatch. So, I spent the last few months building TheBodyMatch, a platform where clothes are showcased on models who share your body shape. You get a more relatable and confident shopping experience because seeing is believing, especially when the model reflects you. It’s still early days. Think of this as a beta where feedback is gold. I’d love for you to try it out here: www.thebodymatch.com and share your thoughts. Is this the future of online fashion? I hope so.

Visit product View on Hacker NewsDec 15, 2024

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

57%57% 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.

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

53%53% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

50%50% predicted probability of success on Hacker News, 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: model, models · Missing: mac, agents, macos

45%45% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

23%23% 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

13%13% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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