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SolveMyPainPoint – A single place to post and discover real problems

Hacker News

SolveMyPainPoint – A single place to post and discover real problems

It’s obviously easier to start a venture when you already have a clear idea in mind. But in reality, a lot of people that want to be founders are the opposite: they’re eager to start something new, and only then go looking for a real problem to solve. I’ve been asked many times by friends: “I want to build a startup, but I don’t know what problem to solve.” Yes, there are ideas and complaints scattered across Reddit, Twitter, forums, etc., but there doesn’t seem to be one focused place where pain points and solutions directly meet. So I built a small MVP: https://www.solvemypainpoint.com/ SolveMyPainPoint lets you: • Submit a pain point in a structured way (what’s the problem, how painful, which category). • See if others share the same issue and how they experience it. • Add or discover existing solutions/products when they exist. • Spot unsolved problems that might be worth building for. It’s a scrappy side project (white-coat MVP, far from perfect), but I’d love feedback from both people with real frustrations and builders looking for something useful to work on. If you have a pain point you keep ranting about, please try submitting it. And if you’re a builder, I’d really appreciate thoughts on what would make this genuinely valuable for you (better discovery, tags, subscriptions to topics, etc.). Happy to answer any questions and very open to criticism and feature suggestions. Many thanks!

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Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, single, open · Missing: mac, agents, macos
80%80% predicted probability of success on Product Hunt, 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 · Missing: supports, reddit linkedin, podcasting
73%73% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: builder · Missing: plus, platform, intuitive
44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: exist, lua, existing · Missing: https docs, excited, just released
34%34% 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: way · Missing: mobile apps, ios, personal
26%26% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: subscription · Missing: arr, mrr, revenue
15%15% 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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