# Plan Seasonal Content with Google Trends

**Use case:** 

Explore five years of US Google search interest to plan seasonal content. Replace air conditioner with your topic and choose a country. Export the timeline to inspect recurring peaks, then rerun for another topic or planning cycle. Scores are relative interest, not search volumes or forecasts; the current period may be incomplete.

## Input

```json
{
  "keywords": [
    "air conditioner"
  ],
  "queries": [],
  "geo": "US",
  "timeframe": "today 5-y",
  "category": 0,
  "property": "web",
  "dataTypes": [
    "interest_over_time"
  ],
  "mode": "snapshot",
  "outputMode": "all",
  "trendingGeos": [],
  "monitorId": "",
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ],
    "apifyProxyCountry": "US"
  }
}
```

## Output

```json
{
  "timestamp": {
    "label": "Bucket timestamp",
    "format": "string"
  },
  "keyword": {
    "label": "Keyword",
    "format": "string"
  },
  "value": {
    "label": "Relative value",
    "format": "integer"
  },
  "is_partial": {
    "label": "Partial bucket",
    "format": "boolean"
  },
  "has_data": {
    "label": "Has data",
    "format": "boolean"
  },
  "geo": {
    "label": "Location",
    "format": "string"
  },
  "timeframe": {
    "label": "Timeframe",
    "format": "string"
  },
  "source_scaling_context": {
    "label": "Scaling context",
    "format": "object"
  }
}
```

## About this Actor

This example demonstrates how to use [Google Trends Scraper & Breakout Monitor](https://apify.com/automa-flow/google-trends-monitor.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/automa-flow/google-trends-monitor.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

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

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

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

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).