Building GhostJob — a Chrome extension to detect ghost job postings (Day 19, 23 MAU, $0 MRR)
Where I'm at
- 23 MAU
- $0 MRR (paid tier shipped 2 weeks ago, no conversions yet)
- 0 reviews on the Chrome Web Store
- Started after I realized I'd been applying to a "Posted 4 days ago" Senior PM role for 11 weeks straight
Goal: $350 MRR in 6 months (50 users × $7/month). Long path. Posting here partly to build the public record, partly because I want feedback before I sink more time into the v2 roadmap below.
The market in 1 paragraph
Resume Builder's 2024 hiring-manager survey (covered widely in WSJ / NYT / BBC) found nearly 4 in 10 hiring managers admit their company has posted jobs with no real plan to fill — market research, résumé collection, ATS auto-reposts of filled roles. The closest direct competitor — HideJobs — sits at ~3K CWS users on $4.99/month. That's roughly $15K MRR from a single-feature extension, which tells me the willingness-to-pay floor is real. Demand isn't my problem. Differentiation is.
What I built
A 0–100 "Ghost Score" overlay on Indeed / LinkedIn / Glassdoor postings (Likely Real / Caution / Likely Ghost). Signals: posting age, repost frequency, industry baseline, NLP keyword density. All client-side, MV3, no data leaves the browser. Free tier is 10 checks/day with score breakdown + recent history. Pro is $6/month or $59 lifetime — unlimited checks, salary insights from the US BLS public API, and priority support.
CWS: https://chromewebstore.google.com/detail/ghostjob/mdjchaohgneaiflafheajamfomeccach
Differentiation bet
HideJobs hides postings outright. I think that's wrong — a 65/100 posting at a company you really want is still maybe worth applying to. You just want to know what you're walking into. So GhostJob exposes the signal instead of removing the listing. Different design philosophy, same underlying problem.
Whether that's the right call is the question I haven't proven yet.
v2 roadmap (next 5 weeks)
- v2.0 (5/29) — English UI + LinkedIn EN parser. Currently JP-only, which is the single largest reason I'm at 23 MAU
- v2.1 (6/5) — Levenshtein-based "same description, new job ID" detection (the trick recruiters use to reset the "Posted today" clock)
- v2.2 (6/12) — Salary-range-required-by-law warning badge for the 7 US disclosure states
- v2.3 (6/26) — Company-level ghost rate (your last 6 months of postings per company)
Each release is a single CWS submission. Marketing is paired: Reddit post the day v2.1 ships, Dev.to writeup the week of v2.0.
What I'm asking
- If you've been mass-applying lately — what would make a "ghost detector" worth $6/month to you?
- Is 60+ days posted my strongest red-flag signal, or am I over-indexing on age vs. repost frequency?
- Anyone with a public CWS-based product crossed the "$300 MRR / 50 paid users" line on a niche extension? I'd love the post-mortem on what actually moved the needle.
I'll repost at 100 MAU, first paid conversion, and first review. Open to a wrong-answers-only roast on the v2 sequencing too.
This is a sharper problem than most job tools because the pain is not “finding more jobs.” It is avoiding wasted applications when the listing itself may not be real. That is a trust layer, not just a Chrome extension feature.
The strongest positioning is probably not “ghost job detector.” That explains the function, but it also keeps the product feeling like a small browser add-on. The bigger wedge is job-market signal intelligence: which postings are real, which companies repeatedly recycle roles, which listings are worth your time, and where applicants are being pulled into fake demand.
That is also where the name becomes a real issue. GhostJob is clear, but it may box you into one narrow trick before you prove the broader value. If this becomes a paid intelligence layer for job seekers, Beryxa.com would carry the product with more trust and room to grow than a literal extension name.