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Valideate – validate your ideas before spending more time and money

Hacker News

Valideate – validate your ideas before spending more time and money

Hi Hacker News! My name is Marcel, and I created Valideate.com Valideate is a quick way to validate your ideas so you can determine whether or not they are worth pursuing further. How does it work? 1. You can post your rough idea on Valideate for free, but it costs 1 point. 2. To earn 1 point, you have to vote on 5 other ideas. 3. That's it! Right now, anyone who registers will instantly earn 5 points, so you can validate 5 ideas immediately. I created this because I wanted a quick way to pulse check my own ideas, and I hope it solves your problem too. If you have questions or feedback, I'll happily answer them below! Alternatively, you can also contact me at marcelc6363@gmail.com or DM me on twitter @marcelc63 P.S. Registering is frictionless, just need username and password, email is optional, no email validation required. Please try it out!

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Actual performance

7points
4comments
Made the leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting
59%59% 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 HuntUnlikely to reach the leaderboard · Strong signals: user, new, email · Missing: mac, agents, macos
45%45% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
29%29% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: hacker news, ide, 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
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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