# Compare Brand Search Interest on Google

**Use case:** 

Analyze the search interest for major sports brands in the U.S. This task provides insights into the popularity of Nike, Adidas, Puma, New Balance, and Asics, measured over the past 12 months. Discover which brand trends highest in consumer interest today, backed by real-time Google data.

## Input

```json
{
  "mode": "searchTerms",
  "searchTerms": [
    "Nike",
    "Adidas",
    "Puma",
    "New Balance",
    "Asics"
  ],
  "compareTerms": true,
  "timeRange": "today 12-m",
  "geo": "US",
  "category": "0",
  "searchProperty": "",
  "includeInterestOverTime": true,
  "includeInterestByRegion": true,
  "includeRelatedQueries": true,
  "includeRelatedTopics": false,
  "regionResolution": "AUTO",
  "includeLowVolumeRegions": false,
  "trendingGeos": [
    "US"
  ],
  "language": "en-US",
  "maxConcurrency": 3,
  "maxRetries": 8,
  "requestDelaySecs": 1,
  "proxyConfiguration": {
    "useApifyProxy": true
  },
  "residentialFallback": true
}
```

## Output

```json
{
  "searchTerm": {
    "label": "Search term",
    "format": "string"
  },
  "status": {
    "label": "Status",
    "format": "string"
  },
  "geo": {
    "label": "Location",
    "format": "string"
  },
  "resolvedTimeRange": {
    "label": "Dates",
    "format": "string"
  },
  "averageInterest": {
    "label": "Average",
    "format": "number"
  },
  "peakInterest": {
    "label": "Peak",
    "format": "integer"
  },
  "peakDate": {
    "label": "Peak date",
    "format": "string"
  },
  "latestInterest": {
    "label": "Latest",
    "format": "integer"
  },
  "trendChangePercent": {
    "label": "Trend change %",
    "format": "number"
  },
  "comparedWith": {
    "label": "Compared with",
    "format": "array"
  },
  "exploreUrl": {
    "label": "Google Trends",
    "format": "string"
  },
  "error": {
    "label": "Error",
    "format": "string"
  }
}
```

## How it works

### 1. Sign up on Apify or log in

The Google Trends Scraper Actor is ready to run with the inputs already set for "Compare Brand Search Interest on Google". [Sign up or log in](https://console.apify.com/create-task-from-example/NqLGAwI4WDXzkF97H) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Compare Brand Search Interest on Google" task

The Google Trends Scraper Actor will start running based on the input automatically. You can also change all the input fields, like what to scrape, search terms, and more, to match your specific use case.

### 3. Receive the "Compare Brand Search Interest on Google" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as search term, status, location, and more.

### 4. Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also [run the "Compare Brand Search Interest on Google" task via API](https://apify.com/blueloles/google-trends-scraper.md).

## FAQ

### What brands does this task compare for search interest?

The task compares search interest for Nike, Adidas, Puma, New Balance, and Asics in the U.S.

### What data does this task provide about brand interest?

The task provides average interest, peak interest, peak date, latest interest, and trend change percentage.

### How can I analyze the search interest trends?

The task analyzes search interest data over the past 12 months, enabling insights into brand popularity.

### What does the 'status' output field indicate?

The 'status' field shows if Google returned data: 'ok' means data was found, 'noData' means none was available, and 'failed' indicates the request could not be completed.

### Can I schedule this task to run automatically?

Automatic scheduling is available through the Apify Console for this task.

### Is API access available for this task?

Yes, API access can be used to run this task programmatically.

### What is the output format of the data collected?

The data collected can be output as JSON, CSV, or Excel format.

## About this Actor

This example demonstrates how to use [Google Trends Scraper](https://apify.com/blueloles/google-trends-scraper.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/blueloles/google-trends-scraper.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/blueloles/google-trends-scraper.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`).