Problemize

Problemize

Indie Hackers

Discover validated problems worth solving

I built Problemize to never again run the risk of building something people won't buy. With Problemize I can validate my ideas against what people are already spending money for or get inspired to build new products.

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Actual performance

6followers
$490MRR/mo
Made the leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
58%58% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Hacker NewsStrong engagement from HN community · Strong signals: ide · Missing: https docs, excited, just released
55%55% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: new · Missing: mac, agents, macos
54%54% 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
34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
32%32% 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
21%21% 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
3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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