> ## Documentation Index
> Fetch the complete documentation index at: https://docs.spidra.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Google Trends

> Get Google Trends interest over time, by region, metro and city, related queries and trending searches as structured data, for 1 credit per link.

Send a Google Trends link to [Scrape](https://docs.spidra.io/scrape.md) or [Batch scrape](https://docs.spidra.io/batch-scrape.md) and you get the data the Trends page shows, as JSON: interest over time for up to 5 terms, interest by region, metro and city, related queries, or what's trending now. Each link costs 1 credit, however many calls it takes, and a term Google has no data for costs nothing.

## Example

Compare coffee and tea in the US over the past 12 months:

```json theme={null}
{ "urls": ["https://trends.google.com/trends/explore?q=coffee,tea&geo=US&date=today%2012-m"], "output": "json", "wait": true }
```

The item's `result`, shortened:

```json theme={null}
{
  "type": "explore",
  "terms": ["coffee", "tea"],
  "geo": "US",
  "timeRange": "today 12-m",
  "resolution": "WEEK",
  "averages": [{ "term": "coffee", "value": 75 }, { "term": "tea", "value": 36 }],
  "summary": [
    {
      "term": "coffee",
      "average": 75,
      "latest": 65,
      "peakValue": 100,
      "peakDate": "2026-04-12",
      "changePercent": 4,
      "direction": "flat",
      "peakMonth": "April",
      "lowMonth": "October",
      "topQuery": "coffee near me",
      "topRisingQuery": "how to remove coffee stain from carpet"
    }
  ],
  "interestOverTime": [
    { "date": "2025-10-19", "formattedTime": "Oct 19 – 25, 2025", "byTerm": { "coffee": 64, "tea": 33 }, "isPartial": false }
  ],
  "interestByRegion": [{ "geoCode": "US-MT", "geoName": "Montana", "byTerm": { "coffee": 74, "tea": 26 } }],
  "relatedQueries": [{ "term": "coffee", "top": [{ "rank": 1, "query": "coffee near me", "value": 100 }], "rising": ["..."] }]
}
```

Values are on Google's 0 to 100 scale. Google samples Trends data, so values for the same request move by 1 to 3 points between runs.

## Links that work

| Link | Example | You get |
| - | - | - |
| Explore | `trends.google.com/trends/explore?q=...&geo=...&date=...&cat=...&gprop=...` | Interest over time, a summary per term, interest by region, and related queries |
| Trending now | `trends.google.com/trending?geo=US&hours=24` (also `category`, `status`, `sort`) | Every trend Google lists for a country or US state in the past 4, 24 or 48 hours or 7 days |
| Trending RSS | `trends.google.com/trending/rss?geo=US` | The 10 most recent trends with approximate traffic and news |
| Autocomplete | `trends.google.com/trends/api/autocomplete/<text>` | Topic ids for a word, to track a topic instead of a search term |

Explore takes up to 5 terms or topic ids (`/m/05p0rrx`), or one term in up to 5 places (`geo=US,GB,CA`).

## Fields

**Explore:** `terms`, `geo`, `timeRange`, `startDate`, `endDate`, `resolution`, `category`, `property`, `averages`, `summary` (average, latest, peak, low, change between the first and last quarter, direction, monthly averages with peak and low month, top and top rising query), `interestOverTime`, `interestByRegion`, and for one term `interestByMetro` (US) and `interestByCity`, `relatedQueries` (top and rising per term), and long-format `timelineRows`, `regionRows` and `relatedRows` ready for a spreadsheet.

**Trending now:** `trendCount` and `trends`, each with `rank`, `query`, `startedAt`, `endedAt`, `active`, `durationHours`, `searchVolume`, `searchVolumeLabel` (such as "500K+"), `increasePercentage`, `categories`, `trendBreakdown` (related searches), `news` (for the first 25 trends) and `exploreUrl`. A 24-hour US list had 641 trends.

## Limits

* Related topics aren't included: Google has returned an empty list for them since about September 2026.
* A term compared across several places has no shared map in Google's answer, so it returns the timeline and related queries only.

## Templates

Ready-made [templates](https://docs.spidra.io/templates.md) for Google Trends: interest over time, trending searches now, rising and top related searches, interest by region and city, keyword trend research in bulk, and a seasonality check.


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