JobAlert.world
MRRdeals Score · 47/100Your secret weapon in job hunting! We monitor all major job platforms 24/7 and ping you the moment a matching job appears. Think of us as your personal job-finding assistant who never sleeps.
What this SaaS is
Monitors job platforms and alerts users to new job postings.
- Job monitoring
- Real-time alerts
- User-friendly interface
- Non-recurring revenue— No active subscriptions. The cash isn't contractually guaranteed to repeat.
- No active customers— Zero customers reported. Hard to model retention or growth.
- Founded <12mo ago— Less than 12 months of operating history. Retention is unproven.
Numbers that matter
Score breakdown
How the composite score above splits across seven independent signals. Each axis is graded 0-100. Hover for details.
Payback period, asking price vs category median multiple, and 30-day profit margin.
30-day MRR delta, with a small bonus when historical snapshots confirm a sustained climb.
Revenue per visitor, customer count, plus live-site UX signals (pricing reachability, core pages, copyright freshness).
AI-disruption risk, presence on review platforms (G2, ProductHunt, AppSumo…), penalty when built on no-code rails.
Diversity of marketing channels, Merchant-of-Record status, cofounder count. Solo founders and no-code stacks get docked.
Listing freshness, payment provider trust, business age, customer concentration. Higher score = less risky.
Structured market read across TAM, saturation, 3-year trend, and hype cycle, blended with our category momentum signal.
Market read
- TAMmid
The job alert market serves a broad audience but is not expansive enough to be considered large.
- Saturationmature
Numerous competitors exist, indicating a mature market with established players.
- 3y trendgrowing
Increased job-seeking activity and digital transformation have led to growth in this niche.
- AI disruptionwrapper killable
The core functionality can be easily replicated by solo developers, posing a significant risk.
- Hype cyclemainstream
Job alert services are widely adopted, indicating they are in the mainstream phase.
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