Jo

Job Seeker Companion

Hacker News

Job Seeker Companion

Hey all, I built a job seeker companion [app]( https://apply-nexus.com ) that I have been using for months to add clarity to my job search. What does it do? - You can track your jobs using its Autofill feature - no need to manually entry each job’s details - You can set daily and weekly goals for yourself to keep yourself motivated - You can see advanced analytics to see what job board works out for you, weekly trends, and many more analytics - [Soon] Interview mode: Keep track of your upcoming interviews and be prepared in an hour or less - [Soon] Email me when I miss a weekly goal or a daily goal for 3 days - and so much more It has been really helpful for me and provided me a lot of insights regarding my job search journey and I hope it will be as helpful for you. I am open to any feedback on this app and there’s a dedicated section for it [here]( https://insigh.to/b/applynexus )

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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 · Missing: supports, reddit linkedin, podcasting
70%70% 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.
TrustMRRFits verified-revenue profile · Strong signals: month · Missing: mobile apps, ios, personal
63%63% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: soon · Missing: plus, platform, intuitive
46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: email, using, open · Missing: mac, agents, macos
38%38% predicted probability of success on Product Hunt, 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
35%35% 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
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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