# Google Search Console Query Analysis

**Use case:** 

Unlock detailed insights from Google Search Console queries, focusing on search intent, question detection, and performance opportunities. This task emphasizes data from seafoodtrades.com from June 1 to August 25, 2026, categorizing queries into Transactional, Commercial, and Informational types. Receive a performance-focused report to identify opportunities and optimize click-through rates.

## Input

```json
{
  "serviceAccountKey": "<YOUR_SECRET>",
  "siteUrl": "sc-domain:seafoodtrades.com",
  "startDate": "2026-06-01",
  "endDate": "2026-08-25",
  "rowLimit": 25000,
  "filterOnlyQuestions": false,
  "filterOnlyPrompts": false
}
```

## Output

```json
{
  "query": {
    "label": "Query"
  },
  "intent": {
    "label": "Intent"
  },
  "opportunityType": {
    "label": "Opportunity type"
  },
  "clicks": {
    "label": "Clicks"
  },
  "impressions": {
    "label": "Impressions"
  },
  "ctr": {
    "label": "Ctr"
  },
  "position": {
    "label": "Position"
  },
  "promptCandidate": {
    "label": "Prompt candidate"
  }
}
```

## About this Actor

This example demonstrates how to use [Google Search Console Query & Intent Classifier](https://apify.com/capyduck/gsc-data-mining.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/capyduck/gsc-data-mining.md) to learn more, explore other use cases, and run it yourself.


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For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/capyduck/gsc-data-mining.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).