Job seekers waste months applying to and interviewing for positions that don't actually exist — posted for internal compliance, investor optics, or to keep HR busy
Analyze job postings using signals like repost frequency, time-open, company hiring velocity, Glassdoor/layoff data, and crowdsourced interview outcomes to give each listing a 'realness score'
Freemium — free basic scores, paid tier for detailed analytics, alerts on verified-real openings, and interview outcome tracking
This is a top-3 frustration for job seekers. Months of wasted effort applying to fake postings causes real financial and emotional damage. The HN thread sentiment is strong and matches broader social media rage. However, it's acute (during job search) not chronic, which limits lifetime value per user.
~10M active tech job seekers globally at any time, cycling through 3-6 month searches. TAM for a tool like this is likely $200-500M if you capture adjacent use cases (recruiter vetting, company intelligence). SAM for tech job seekers willing to pay is smaller — maybe $50-100M. EU/EMEA focus narrows this further but also reduces competition.
This is the weakest link. Job seekers are notoriously price-sensitive — they're often unemployed or anxious about finances. Free alternatives (manually checking LinkedIn signals, reading Blind) exist even if inferior. The paid tier needs to deliver undeniable ROI, like 'this tool saved me 2 months of searching.' Conversion rates for job seeker tools are typically 2-5%. B2B pivot (selling to recruiters or career coaches) could unlock higher WTP.
Browser extension scraping job boards is straightforward. The hard part is the scoring model — you need multi-source data aggregation (repost frequency, company headcount changes, Glassdoor sentiment, layoff data, crowdsourced outcomes). APIs for some signals exist; others require scraping that may violate ToS. Crowdsourced data creates a cold-start problem. A solo dev can build a credible MVP in 6-8 weeks with a simplified heuristic model, but the real moat (accuracy) takes longer.
No one is doing this directly. LinkedIn won't (misaligned incentives). Glassdoor could but hasn't. Job tracker tools focus on workflow, not intelligence. The insight layer — synthesizing multiple signals into a per-listing realness score — is genuinely unoccupied. First mover who nails accuracy could own this category.
Job searching is episodic, not continuous. Average tech job search is 3-6 months. Users churn hard once employed. Subscription LTV is likely 3-5 months. To improve: add 'passive market monitoring' for employed users, career intelligence alerts, or pivot to B2B (staffing firms, outplacement services) where the buyer is always in-market.
- +Genuine unmet need with strong emotional resonance — job seekers are angry and vocal about ghost jobs
- +No direct competitor occupies this exact niche despite the pain being widely acknowledged
- +Browser extension distribution model is low-friction and viral (shareable scores)
- +Crowdsourced data creates a defensible moat over time — more users = better accuracy
- +Strong media/PR potential — 'ghost jobs' is already a trending topic that journalists love covering
- !Cold start problem: scoring accuracy depends on data you don't have yet. Bad early scores kill trust permanently
- !Job board ToS violations — LinkedIn, Indeed, etc. aggressively block scrapers and could shut down the extension
- !Low willingness to pay from unemployed job seekers combined with high churn once employed creates tough unit economics
- !Accuracy liability — flagging a real job as fake (false positive) could cause a user to miss their dream job, creating PR and trust crises
- !Episodic use pattern makes subscription revenue unreliable without a B2B or 'always-on' career intelligence pivot
Job board with company reviews, salary data, and interview experiences. Users can see if companies are actively hiring or have patterns of reposting.
Shows applicant counts, company growth signals, recruiter activity, and how long a job has been posted.
Job application tracking and resume optimization tools. Help job seekers organize their pipeline and optimize for ATS systems.
Track tech layoffs and hiring freezes. TrueUp aggregates startup jobs and funding data.
Anonymous professional social network where employees share insider info about hiring, layoffs, and internal practices.
Chrome extension that overlays a simple red/yellow/green 'realness badge' on LinkedIn and Indeed job listings. V1 scoring uses only publicly available signals: days posted, repost count, company headcount trend (from LinkedIn), recent layoff mentions (from news APIs), and ratio of open roles to company size. Add a single crowdsource button: 'I applied — did I hear back?' to start building the feedback loop. Skip the paid tier entirely for launch — focus on accuracy and data collection for the first 3 months.
Free extension with basic scores (months 1-6, focus on user growth and data collection) → Freemium with detailed breakdowns, company hiring health reports, and 'verified real' job alerts at $9/month (months 6-12) → B2B tier for career coaches, outplacement firms, and recruiting agencies at $49-99/month (month 12+) → Data licensing to job boards who want to differentiate on quality (year 2+)
3-6 months to first dollar. First 2-3 months should be free-only to build data moat and prove accuracy. Paid tier introduction around month 4-6 once you have enough crowdsourced data to offer meaningfully differentiated insights. Expect slow initial conversion (2-3%) from a price-sensitive audience. B2B revenue could start month 8-12 if you actively pursue career coaching partnerships.
- “most of them have just dummy openings for internal procedures/investor reports”
- “No companies are hiring and all jobs are fake”
- “Agencies simply collect data and will consume your time with intake interviews”
- “HR wants you to think so, otherwise even they are not safe”