I made a tool to help you find your next profitable idea

Hacker News

I'm an indie hacker. I've found that one of the best ways to come up with project ideas is to find apps that are popular, but aren't loved by their users. I typically spend hours searching the depths of the App Store and Google Play Store top charts, looking for apps with a high number of reviews, but a sub-3.9 rating (and ideally ones that haven't been updated by their developers in >6 months). I look for opportunities to add AI, refresh the UI, fix user complaints, etc., and build a better version of the app. I know there's a market need, and I know exactly what my users want. I realized I was spending too much time on the idea discovery process, and would love a way to do it passively over the course of a few months (even while I'm building other projects). Several friends also expressed the same need, and this post by Greg Isenberg ( https://x.com/gregisenberg/status/1868673184213467576 ) validated the method. So, I automated the process and created BuildList - a weekly email newsletter with insights on neglected but popular apps that are ready for disruption. Let me know what you think!

Visit product View on Hacker NewsJan 16, 2025

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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 · Strong signals: created · Missing: supports, reddit linkedin, podcasting

86%86% 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 HuntOn track for Day 1 leaderboard · Strong signals: google, apps, user · Missing: mac, agents, macos

68%68% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: apps, month, google · Missing: mobile apps, ios, personal

51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: reviews, users · Missing: plus, platform, intuitive

42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

39%39% 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 · Strong signals: profit, profitable · Missing: arr, mrr, revenue

16%16% 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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