Job Market Trend Analyzer

How the agent runs it

Agent scrapes 50K+ job postings weekly, extracts required skills, salary ranges, and demand trends by role and geography. Produces dashboards and weekly PDF reports for subscribers.

Who this is for

This business is ideal for data engineers, Python developers, or former HR professionals who understand recruitment workflows and want to build a scalable SaaS product with minimal ongoing maintenance. If you've already worked with web scraping, APIs, or job market data—or you have relationships with recruiters and career coaches—you have a significant head start. This model rewards technical depth and domain knowledge without requiring constant client hand-holding or service delivery.

Market opportunity

The recruitment tech market is valued at $8B+ globally and growing 8–10% annually, driven by talent shortages and the shift to data-driven hiring. Career coaches and mid-market recruiting agencies increasingly rely on trend insights to position candidates and justify hiring strategies to clients. Real-time job data is highly valuable; firms like Hired and Levels.fyi have built audiences in the millions by offering exactly this transparency.

Tech stack

Monetization

$99/mo career coaches, $499/mo recruiting agencies (multi-client access).

Key risks

• → Job board ToS on scraping
• → Data lags actual market by 2–4 weeks

Getting started

1. 1
   Set up API access and test scraping

   Register for Indeed API and LinkedIn Jobs scraper access, then build a proof-of-concept Python script that pulls 100–500 job postings and extracts skills and salary data. This validates your data pipeline and confirms that the APIs will support your volume needs before you commit further.
2. 2
   Design your weekly report template

   Create a sample PDF and dashboard (using Notion API or a simple web template) showing top hiring trends, emerging skills, and salary bands by role and geography. Share this mockup with 3–5 recruiters and career coaches to confirm they'd pay for it and identify what metrics matter most to them.
3. 3
   Automate the full data pipeline

   Build a Python workflow using Claude API to clean and summarize job data, then use the Notion API to populate a dashboard and generate a styled PDF weekly report. Automate this with a scheduler (e.g., GitHub Actions or AWS Lambda) so it runs without manual intervention.
4. 4
   Create landing page and pricing tiers

   Build a simple one-pager explaining your reports and offering two tiers: $99/mo for individual career coaches (1–3 reports) and $499/mo for agencies (multi-user dashboard, custom geographies). Use Stripe for payments and set up a free trial to reduce friction.
5. 5
   Launch to warm audience and iterate

   Email your initial feedback group, post in LinkedIn recruiting communities, and reach out directly to 20–30 mid-market recruiting agencies with a free trial offer. Use early subscriber feedback to refine metrics, add missing data points, and refine your positioning before scaling marketing efforts.

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