I built a Chrome extension to save job postings to Google Sheets

Hacker News

Hey HN - I built a Chrome extension that adds a button to LinkedIn, Indeed, and Lever to autosave the job's title, company, and link in a Google Sheet so you can organize all your job applications in one location. I used to open a bunch of tabs to apply for jobs that I never ended up applying to bc I was either lazy or it got too messy to keep track of. AKA I never went back to that tab again The extension has really helped me navigate my own job search and I wanted to share it with anyone looking for a simple and beneficial tool. What's great about this extension: - It's free forever - just trying to help people find a job - No sign up needed - works with your Google account - Saves job postings directly to Google Sheets - You can customize and edit the spreadsheet however you want - Integrates with LinkedIn, Indeed and Lever - Adds a button on the website - no more switching between tabs or copy/paste I hope this helps at least a few people with their job search :) If you do try it, I'd love to hear your thoughts on how it can be improved!

Visit product View on Hacker NewsJul 14, 2022

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Product HuntOn track for Day 1 leaderboard · Strong signals: google, open · Missing: mac, agents, macos

85%85% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

69%69% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

32%32% 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

17%17% 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.

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