Indeed Salary Scraper — Pay by Job Title, Company & City

What does Indeed Salary Scraper do?

Indeed Salary Scraper extracts structured pay data from indeed.com salary pages — median, minimum and maximum pay for any job title across five pay periods (hourly, daily, weekly, monthly, yearly), plus the top-paying companies and top-paid cities for that role. Look titles up nationally or per state and city, across Indeed country markets in local currency. Recurring runs can emit only the records whose estimates moved, so you can monitor salary trends over time.

How to use this actor

• 👉 Register for a free Apify account — no credit card required.
• 🎉 Just click Sign up free on Apify → and complete a quick signup.
• 💰 A free Apify account includes $5 in monthly credits — enough to test this actor.
• ⏳ Scrape during the free trial, with no commitment or upfront payment required.

Key features

• 📤 Export anywhere — Download the dataset as JSON, CSV, or Excel from the Apify Console, or stream live via the Apify API and integrations (Make, Zapier, Google Sheets, n8n, …).
• 🔗 Paste-mode — paste any indeed.com URL straight from your browser — single-job pages, search-results URLs, or category SEO URLs. Build the search you want in the UI, copy the URL, paste it here.
• 🔔 Notifications — Telegram, Slack, Discord, WhatsApp Cloud API, generic webhook — out of the box. Pair with incremental + notifyOnlyChanges for daily "new Indeed jobs" pings to your hiring channel.
• 📦 Compact mode — AI-agent and MCP-friendly compact payloads with core fields only — pipe straight into your ATS, salary-benchmarking tool, or LLM context without parsing extras.
• 🧹 Empty-field stripping — drop null, empty-string, and empty-array fields from each record before push. Smaller payloads for AI agents and dashboards that already handle missing fields gracefully.
• ♻️ Incremental mode — recurring runs emit only NEW / UPDATED / REAPPEARED records — UNCHANGED and EXPIRED are opt-in. First run builds the baseline; subsequent runs emit and charge only for the diff. Pair with notifications for daily "new jobs" alerts to your hiring team. Saves 80–95% on daily monitoring.
• 🔌 MCP connectors — export your results into Notion via Apify's MCP connectors — a clean run-summary page, no glue code. Opt-in via the App connector field; deterministic field-mapping, no AI. Built on Apify's connector framework, so more destinations open up as their catalog grows.

What data can you extract from indeed.com?

Each result includes Core salary fields (recordType, jobTitle, normalizedTitle, displayTitle, location, locationType, countryCode, and currency, and more). In standard mode, all fields are always present — unavailable data points are returned as null, never omitted. In compact mode, only core fields are returned.

Input

The main inputs are an optional location filter. Additional filters and options are available in the input schema.

Key parameters:

• jobTitles — Job titles to get salary data for (e.g. ["software engineer", "registered nurse"]). One aggregate salary record is emitted per title (and per location, when locations are set).
• startUrls — Alias for Job Titles — paste Indeed career salary URLs (indeed.com/career/.../salaries). A pasted URL contributes its title and location. Merged with the Job Titles list.
• locations — Optional states or cities (e.g. ["Texas", "San Jose, CA"]). Each job title is looked up in each location. Leave empty for national data.
• country — Indeed market to query (two-letter code: us, gb, ca, au, de, in, ...). Default us. Salaries are reported in the market's local currency. (default: "us")
• includeCompanies — Also emit one record per top-paying company for each title×location (company name, mean salary, report count, review count). (default: true)
• includeCities — Also emit one record per top-paid city for each title (city, median/min/max salary). (default: true)
• maxCompanies — Maximum top-paying-company records per title×location. Set 0 for all available (Indeed lists up to ~50). (default: 25)
• compact — Output only core fields per record. Ideal for AI agents, MCP workflows, and LLM context windows where token budget matters. (default: false)
• excludeEmptyFields — Drop null, empty-string, and empty-array fields from each record before push. Smaller payloads for AI agents and dashboards. (default: false)
• incrementalMode — Return only salary records that are new or whose estimates changed since the last run for the same query set. Ideal for monitoring salary movements on a schedule. State is keyed automatically; set State Key to isolate universes. (default: false)
• stateKey — Optional stable identifier for the tracked query set. Leave empty to auto-derive from the title/location lists. Use distinct keys for unrelated monitors to keep their state separate.
• telegramToken — Telegram bot token from @BotFather. Required for Telegram notifications.
• ...and 12 more parameters

Input examples

National salary for one job title — Full picture for a single role: aggregate, companies and cities.

→ One salary record with all five pay periods, plus companySalary and citySalary records for the role.

{
  "jobTitles": [
    "software engineer"
  ],
  "includeCompanies": true,
  "includeCities": true,
  "maxCompanies": 25
}

Compare a role across states — Each location gets its own salary record with a national benchmark.

→ One salary record per title×location with nationalMedian for comparison.

{
  "jobTitles": [
    "registered nurse"
  ],
  "locations": [
    "Texas",
    "California",
    "New York State"
  ],
  "includeCompanies": false,
  "includeCities": false
}

Paste an Indeed salary URL — Start URLs work as-is — the title and location are read from the URL.

→ The same salary record as the equivalent title+location input.

{
  "startUrls": [
    "https://www.indeed.com/career/software-engineer/salaries/San-Jose--CA"
  ]
}

Salary change monitor (incremental) — Schedule this and only pay for records whose estimates actually moved.

→ Only new-or-changed salary records on each recurring run.

{
  "jobTitles": [
    "software engineer",
    "data scientist"
  ],
  "includeCompanies": false,
  "includeCities": false,
  "incrementalMode": true
}

Top-paying companies for a role — Who pays the most for this title, with report and review counts.

→ All available companySalary records for the title (maxCompanies 0 = no cap).

{
  "jobTitles": [
    "software engineer"
  ],
  "includeCompanies": true,
  "includeCities": false,
  "maxCompanies": 0
}

Output

Each run produces a dataset of structured salary records. Results can be downloaded as JSON, CSV, or Excel from the Dataset tab in Apify Console.

Example salary record

{
  "recordType": "salary",
  "jobTitle": "software engineer",
  "normalizedTitle": "software engineer",
  "displayTitle": "Software Engineer",
  "location": "United States",
  "locationType": "COUNTRY",
  "countryCode": "US",
  "currency": "USD",
  "displayPeriod": "YEARLY",
  "salaryMedian": 134578.24,
  "salaryMin": 79943.23,
  "salaryMax": 226552.08,
  "salaryMean": 146163.86,
  "dataPoints": 39664,
  "yearly": {
    "median": 134578.24,
    "min": 79943.23,
    "max": 226552.08,
    "mean": 146163.86,
    "stdDev": 61941.04,
    "dataPoints": 39664,
    "lastUpdated": "2026-07-06T08:15:43.000Z"
  },
  "monthly": {
    "median": 9528.36,
    "min": 5660.11,
    "max": 16040.26,
    "mean": 10348.64,
    "stdDev": 4385.53,
    "dataPoints": 0,
    "lastUpdated": "2026-07-06T08:15:43.000Z"
  },
  "weekly": {
    "median": 2462.33,
    "min": 1462.69,
    "max": 4145.15,
    "mean": 2674.31,
    "stdDev": 1133.31,
    "dataPoints": 0,
    "lastUpdated": "2026-07-06T08:15:43.000Z"
  },
  "daily": {
    "median": 598.09,
    "min": 355.28,
    "max": 1006.84,
    "mean": 649.58,
    "stdDev": 275.28,
    "dataPoints": 0,
    "lastUpdated": "2026-07-06T08:15:43.000Z"
  },
  "hourly": {
    "median": 57.79,
    "min": 34.33,
    "max": 97.28,
    "mean": 62.76,
    "stdDev": 26.6,
    "dataPoints": 0,
    "lastUpdated": "2026-07-06T08:15:43.000Z"
  },
  "averageTenureYears": 2,
  "compensations": [
    {
      "compensationType": "CASH_BONUS",
      "salaryType": "YEARLY",
      "mean": 5000
    }
  ],
  "relatedTitles": [
    {
      "title": "entry level software engineer",
      "displayTitle": "Entry Level Software Engineer",
      "salaryType": "YEARLY",
      "salaryMean": 76448.46
    },
    {
      "title": "junior software engineer",
      "displayTitle": "Junior Software Engineer",
      "salaryType": "YEARLY",
      "salaryMean": 85604.95
    },
    {
      "title": "principal software engineer",
      "displayTitle": "Principal Software Engineer",
      "salaryType": "YEARLY",
      "salaryMean": 176735.57
    },
    {
      "title": "senior software engineer",
      "displayTitle": "Senior Software Engineer",
      "salaryType": "YEARLY",
      "salaryMean": 158182.38
    },
    {
      "title": "software engineer intern",
      "displayTitle": "Software Engineer Intern",
      "salaryType": "HOURLY",
      "salaryMean": 35.05
    },
    "... 1 more items"
  ],
  "lastUpdated": "2026-07-06T08:15:43.000Z",
  "sourceUrl": "https://www.indeed.com/career/software-engineer/salaries",
  "scrapedAt": "2026-07-13T21:10:41.899Z"
}

Incremental mode

Indeed re-estimates its salary aggregates continuously, so incremental mode is change-detection: the first run establishes a baseline and subsequent runs emit — and charge for — only salary records that are new or whose pay numbers actually moved (tiny float jitter in the estimates is ignored). State is keyed automatically from the title/location lists; set stateKey to keep unrelated monitors separate. Pair with notifications and notifyOnlyChanges to get alerted only when a salary estimate changes.

How to scrape indeed.com

1. Go to Indeed Salary Scraper in Apify Console.
2. Configure the input and optional location filter.
3. Set maxResults to control how many results you need.
4. Click Start and wait for the run to finish.
5. Export the dataset as JSON, CSV, or Excel.

Use cases

• Compensation benchmarking — pull median/min/max pay for your roles across states and cities to calibrate salary bands against the market.
• Offer negotiation research — check what a title actually pays in a specific metro, including which companies pay the most for it.
• Recruiting intelligence — compare pay across markets before opening a role, and see the salary you are competing against by city.
• Salary trend monitoring — schedule incremental runs and get notified only when Indeed's estimate for a tracked title moves.
• Content & research — feed salary datasets into reports, cost-of-living comparisons, and job-market analyses.

How much does it cost to scrape indeed.com?

Indeed Salary Scraper uses pay-per-event pricing. You pay a small fee when the run starts and then for each result that is actually produced.

• Run start: $0.01 per run
• Per result: $0.0014 per salary record

Example costs:

• 10 results: $0.024
• 25 results: $0.045
• 100 results: $0.15
• 200 results: $0.29
• 500 results: $0.71

Example: recurring monitoring savings

These examples compare full re-scrapes with incremental runs at different churn rates. Churn is the share of records that are new or whose tracked content changed since the previous run. Actual churn depends on your query breadth, source activity, and polling frequency — the scenarios below are examples, not predictions.

Example setup: 250 results per run, daily polling (30 runs/month). Event-pricing examples scale linearly with result count.

Churn rate	Full re-scrape run cost	Incremental run cost	Savings vs full re-scrape	Monthly cost after baseline
5% — stable niche query	$0.36	$0.03	$0.33 (92%)	$0.82
15% — moderate broad query	$0.36	$0.06	$0.30 (83%)	$1.88
30% — high-volume aggregator	$0.36	$0.11	$0.24 (68%)	$3.45

Full re-scrape monthly cost at daily polling: $10.80. First month with incremental costs $1.16 / $2.17 / $3.69 for the 5% / 15% / 30% scenarios because the first run builds baseline state at full cost before incremental savings apply.

Platform usage is included in the per-result fee shown above.

FAQ

How many results can I get from indeed.com?

The number of results depends on the search query and available records on indeed.com. Use the maxResults parameter to control how many results are returned per run.

Does Indeed Salary Scraper support recurring monitoring?

Yes. Enable incremental mode to only receive new or changed records on subsequent runs. This is ideal for scheduled monitoring where you want to track changes over time without re-processing the full dataset.

Can I integrate Indeed Salary Scraper with other apps?

Yes. Indeed Salary Scraper works with Apify's integrations to connect with tools like Zapier, Make, Google Sheets, Slack, and more. You can also use webhooks to trigger actions when a run completes.

Can I use Indeed Salary Scraper with the Apify API?

Yes. You can start runs, manage inputs, and retrieve results programmatically through the Apify API. Client libraries are available for JavaScript, Python, and other languages.

Can I use Indeed Salary Scraper through an MCP Server?

Yes. Apify provides an MCP Server that lets AI assistants and agents call this actor directly. Use compact mode and excludeEmptyFields to keep payloads manageable for LLM context windows.

Is it legal to scrape indeed.com?

This actor extracts publicly available data from indeed.com. Web scraping of public information is generally considered legal, but you should always review the target site's terms of service and ensure your use case complies with applicable laws and regulations, including GDPR where relevant.

Your feedback

If you have questions, need a feature, or found a bug, please open an issue on the actor's page in Apify Console. Your feedback helps us improve.

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