Scrape Indeed, LinkedIn & Glassdoor in One Run (2026)

No single job board sees the whole market

Indeed dominates volume. LinkedIn skews professional. Glassdoor adds employer ratings. ZipRecruiter is strong in North America, Bayt covers the Middle East. Query only one of them and your “market analysis” has a structural blind spot; query all five separately and you’re maintaining five scrapers, five schemas, and a pile of duplicate listings.

The cross-platform approach fixes the structure of the problem, not just the volume: one input, five sources, one deduplicated dataset.

What you can extract

Per listing, normalized across platforms:

• Job title and full description
• Source platform
• Company metadata and ratings
• Location and remote flags
• Salary range and period, converted to one currency
• Skills and experience level
• Apply links and posting dates
• Contact emails, phones and social links when available

The technical challenge

Multiply everything by five. Each platform has its own pagination, markup, anti-bot system and quirks — Indeed’s TLS fingerprinting, LinkedIn’s aggressive rate limits, Glassdoor’s overlays. On top of that, cross-platform work adds two hard problems of its own:

• Deduplication — the same opening posted on three boards must count once, which means fuzzy matching on title + company.
• Normalization — salaries arrive in different currencies and periods (hourly, monthly, yearly) and need converting to compare anything. For the toughest platforms, a headless browser is still the fallback layer.

DIY or a ready-made Actor?

Building and maintaining five scrapers plus a dedup layer is a project. Our All Jobs Scraper on Apify queries Indeed, LinkedIn, Glassdoor, ZipRecruiter and Bayt in a single run across 70+ countries, deduplicates by title and company, and converts salaries to your target currency using live ECB rates. Pay-per-result from about $0.0023 per job — one of the lowest rates on the market.

A practical workflow

1. One search definition — terms, country, location, platforms to include, freshness window (24h to 30 days).
2. Schedule it — daily runs with a 24h window give you an incremental, always-fresh dataset.
3. Post-process — the dedup is done; add your own enrichment such as company matching or LLM-based classification of roles into your taxonomy.
4. Deliver — job board feed, BI dashboard, or lead list with the extracted contact details.

Use cases that pay off

• True market coverage — measure total demand for a role without platform bias.
• Aggregation at low cost — one run replaces five integrations, at a per-result price built for daily use.
• Salary comparison — same role, five platforms, one currency: real spread, not anecdotes.
• Lead generation — hiring companies are spending companies; contacts included when available.

The legal boundaries

• Public data only — listings are public; keep it that way and respect each platform’s pace.
• Terms of service — automated access is restricted on most boards; analysis of public data is the defensible use, mass republishing is not.
• Personal data — extracted emails and phones fall under GDPR/CCPA; store only what you’ll actually use.

Getting started

Run the All Jobs Scraper on one search and compare what each platform returns — the coverage gaps between boards are usually the first insight. If you need depth on one source instead, our dedicated LinkedIn Jobs, Indeed Jobs and ZipRecruiter scrapers go further per platform. And for wiring the feed into your product or warehouse, that’s what we build at SilentFlow.