I made a free app to help you organize your job applications

Hacker News

I was scrolling instagram the other day and I saw a lot of people who are applying for 100s of jobs track all their applications on a Google Sheet. While Google sheets gets to job done, its still not user friendly. People spend a lot of time optimizing and organizing their excel sheets. So I thought it would be a cool weekend project to built an android app that helps you organize 100s of your job applications for free! Link: https://play.google.com/store/apps/details?id=com.applicatio... This is my first project as an Indie hacker so please let me know the reviews and what can I do better for my next project. I am totally okay with harsh criticizm and take all the tips shared by you to make my next product better than this one!

Visit product View on Hacker NewsJun 30, 2024

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2points

1comments

Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

79%79% 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.

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

43%43% 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: google, apps, user · Missing: mac, agents, macos

43%43% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: apps, google · Missing: mobile apps, ios, personal

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

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

40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

20%20% 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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