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Forest Market – buy and sell goods with crypto

Hacker News

Forest Market – buy and sell goods with crypto

Hi everyone! I began my crypto journey in 2020. Over the past four years, I've often wondered: why can't we buy goods with crypto as easily as we shop on eBay? Isn't crypto supposed to function as a medium of exchange? After seeing multiple forum posts echoing my thoughts, I decided to take action. As a developer, I've built a marketplace with one clear goal: to provide a reliable platform where users can buy and sell goods with crypto. I believe that when you make something truly for yourself, you're likely creating something valuable for others too. As of today, you can: 1. buy anything in the marketplace with crypto 2. sell any legal item and get paid in crypto 3. return products if you're unsatisfied and receive a full refund in crypto We're still actively developing the platform, so we'd greatly appreciate any feedback and support.

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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
91%91% 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.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, users · Missing: plus, intuitive, reviews
45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: lua, ide, io · Missing: https docs, excited, just released
44%44% 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: user · Missing: mac, agents, macos
40%40% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal
39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue
17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: crypto, paid · Missing: web3, chat, cryptocurrency
5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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