# Google Jobs Market Data - Workforce Trends

**Use case:** 

Collect a 500-row Google Jobs dataset for workforce research. Compare public demand across role groups, employers, locations, and salary text.

## Input

```json
{
  "market": "US-en",
  "queries": [
    "software engineer",
    "data analyst",
    "registered nurse",
    "sales representative",
    "warehouse worker"
  ],
  "location": "",
  "maxItems": 500
}
```

## Output

```json
{
  "title": {
    "label": "Job title",
    "format": "string"
  },
  "companyName": {
    "label": "Company",
    "format": "string"
  },
  "location": {
    "label": "Job location",
    "format": "string"
  },
  "postedAtRaw": {
    "label": "Posted",
    "format": "string"
  },
  "salaryRaw": {
    "label": "Salary",
    "format": "string"
  },
  "via": {
    "label": "Listing source",
    "format": "string"
  },
  "jobUrl": {
    "label": "Google job",
    "format": "string"
  },
  "query": {
    "label": "Search query",
    "format": "string"
  },
  "observedAt": {
    "label": "Observed",
    "format": "string"
  }
}
```

## About this Actor

This example demonstrates how to use [Google Jobs Scraper - Job Search & Apply Links](https://apify.com/chronometrica/google-jobs-scraper) with a specific input configuration. Visit the [Actor detail page](https://apify.com/chronometrica/google-jobs-scraper) to learn more, explore other use cases, and run it yourself.


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This Task's input is already configured above — use it as-is rather than inventing a new one.

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For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/chronometrica/google-jobs-scraper.md

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).