# Google Trends Scraper: Interest, Related Queries, Trending (`arcadium/google-trends`) Actor

Google Trends interest over time, by region, related queries and topics for keywords, links or a country; $2.70 per 1,000 rows. Trending now lists, 12+ keywords on one scale, monitoring mode that returns only changes. Input names of the Apify-made scraper accepted, free error rows.

- **URL**: https://apify.com/arcadium/google-trends.md
- **Developed by:** [Arcadium Data](https://apify.com/arcadium) (community)
- **Categories:** SEO tools, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.27 / 1,000 result rows

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

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 examples already wired to this Actor's own input schema, see the [API](#api) section below.

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`).

# README

## Google Trends Scraper: Interest, Related Queries, Trending

Give it keywords, a Google Trends link or a country and it returns Google Trends data as JSON: one row per keyword with interest over time, interest by region, related queries and related topics, or one row per live "Trending now" search. $2.70 per 1,000 rows on the free plan, less on paid plans. You pay only for rows you get.

**Why this actor**

- Compares 12+ keywords on one scale in one run, not only Google's limit of 5.
- Monitoring mode (`onlyChanges`): after a baseline, a keyword comes back only when a new rising query appears or interest moves; unchanged keywords are free.
- Input names of the Apify-made Trends scraper work as they are (`searchTerms`, `geo`, `timeRange`...). That actor failed 21.5% of its runs over 30 days (Apify Store, 2026-10-28).
- Free error rows with a `code` for every input that fails.

Built by Arcadium Data: public data, dated and agent-ready, never personal data.

### Use with AI agents

Agents can call this actor directly (for example through the Apify MCP server). A minimal input example:

```json
{ "searchTerms": ["electric car"], "geo": "US", "timeRange": "today 3-m", "includeGeo": false }
```

The dataset has one row per keyword. Read `averageInterest` for a quick answer, `interestOverTime_timelineData[].value[0]` for the curve, and `relatedQueries_rising` for what is taking off. To compare brands, use `{"searchTerms":["nike","adidas","puma"],"compareKeywords":true}` and compare `averageInterest` across rows. For a live list of what people are searching right now, use `{"trendingGeos":["US"],"trendingHours":"4"}`. Failures arrive as rows with `rowType: "error"` and a machine-readable `code`; they are free.

Connect it through the Apify MCP server (https://mcp.apify.com, actor `arcadium/google-trends`). Cost: $2.70 per 1,000 rows on the free plan, less on paid plans (see Pricing); error rows are free.

### What you get

Every keyword is one row. The field names follow the well-known `apify/google-trends-scraper`, so a pipeline built for it keeps working (see "Switching from another Google Trends actor").

| Field | What it holds |
| --- | --- |
| `searchTerm`, `inputUrlOrTerm`, `geo`, `timeRange`, `category`, `property` | What was asked: keyword, what you typed, location, period (as Google writes it, for example `today 12-m`), category and search type. |
| `interestOverTime_timelineData` | The timeline: one entry per point with `time` (Unix seconds), `formattedTime`, `value` (0-100), `hasData`, and `isPartial` on the unfinished last point. |
| `averageInterest` | Mean of the timeline values. |
| `interestBy`, `interestBySubregion`, `interestByCity`, `interestByMetro` | Interest by place. Google picks the level: a worldwide search gives countries, a country search gives subregions or cities, a region search can give metro areas. The other lists are empty. |
| `relatedQueries_top`, `relatedQueries_rising` | Related search queries. Rising ones carry a `formattedValue` such as `+250%` or `Breakout`. |
| `relatedTopics_top`, `relatedTopics_rising` | Related topics, with Google's topic id and type. |
| `scale` | How the values are scaled: `single`, `compare` (exact) or `anchor` (approximate), with the keywords, the anchor and the estimated error. |
| `change` | Only in monitoring mode: what changed since the last run. |
| `scrapedAt` | When the row was read. |

"Trending now" rows look different: `keyword`, `geo`, `searchVolume` (lower bound of Google's bracket), `increasePercent`, `startedAt`, `endedAt`, `active`, `relatedKeywords`, `categoryIds`, `articleCount`, `windowHours`.

Output example:

```json
{
  "rowType": "trend",
  "searchTerm": "coffee",
  "geo": "US",
  "timeRange": "today 12-m",
  "averageInterest": 77.7,
  "interestOverTime_timelineData": [
    { "time": "1760832000", "formattedTime": "Oct 19 – 25, 2025", "value": [63], "hasData": [true], "formattedValue": ["63"] }
  ],
  "interestBySubregion": [{ "geoCode": "US-WY", "geoName": "Wyoming", "value": [100] }],
  "relatedQueries_top": [{ "query": "coffee near me", "value": 100, "formattedValue": "100" }],
  "relatedQueries_rising": [{ "query": "best coffee near me", "value": 160, "formattedValue": "+160%" }],
  "scale": { "method": "single", "keywords": ["coffee"] }
}
```

### Input

```json
{
  "searchTerms": ["electric car", "solar panels"],
  "geo": "US",
  "timeRange": "today 3-m"
}
```

| Field | What it does |
| --- | --- |
| `searchTerms` | Keywords, one row each. |
| `startUrls` | Links copied from `trends.google.com/trends/explore`. Keywords, location, period and category come from the link. Several keywords in one link are compared on one scale. |
| `geo` | `US`, `GB`, `DE`, or a region like `US-CA`. Empty is worldwide. |
| `timeRange`, `customTimeRange` | A preset period, or an exact `YYYY-MM-DD YYYY-MM-DD` range. |
| `category`, `property` | Restrict to a Trends category, or measure image, news, YouTube or shopping search. |
| `compareKeywords`, `anchorKeyword` | Put all search terms on one scale (see below). |
| `includeRelatedQueries`, `includeRelatedTopics`, `includeGeo` | Switch sections off to save requests. All on by default. |
| `onlyChanges`, `changeThreshold`, `stateName` | Monitoring mode (see below). |
| `trendingGeos`, `trendingHours` | Add the "Trending now" list for these countries. |
| `spreadsheetId` | Read search terms from the first column of a public Google Sheet. |
| `maxItems` | Stop after this many rows. |
| `includeErrorRows` | Free rows that explain what failed. On by default. |

### More than five keywords on one scale

Google Trends compares at most five keywords at a time and scales each request to its own peak, so numbers from two requests cannot be compared directly. Switch on `compareKeywords` and the actor does this for you:

- Up to 5 keywords: one request, Google's own shared scale. Exact.
- More than 5: the keywords are split into batches of five, and every batch also contains the same anchor keyword (`anchorKeyword`, or the first keyword). The anchor's values in each batch tell how that batch is scaled, so every batch is converted to the first batch's scale, and everything is renormalised so the highest point of all keywords is 100.

How accurate is it? Google rounds every value to a whole number. The actor puts the estimated error of each batch conversion in `scale.factorErrorPct`. We checked it against Google's own exact comparison on live data: for mid-sized keywords the averages matched to within 0.1%, and a keyword that sits at about 2% of the peak was off by about 5%. Keywords that are tiny next to the peak are only indicative. Pick an anchor with steady, medium search volume. If the anchor is very small inside a batch, `scale.lowConfidence` is `true`.

Interest by region is read per batch and is not converted across batches.

### Monitoring mode: only what changed

Set `onlyChanges` and run on a schedule. The first run returns every keyword once as the baseline (`change.status` is `baseline`). After that a keyword is returned only when a new rising query appeared that was not rising last time, or the latest finished point moved by at least `changeThreshold` index points. Unchanged keywords are neither returned nor charged. The state lives in a key-value store named `google-trends-state` in your account; use `stateName` to keep several monitors apart.

### Errors are rows, not silence

When a keyword cannot be delivered you get a free row with a `code` and a `message`:

| Code | Meaning |
| --- | --- |
| `invalid_input` | The link, location, category or date range is not valid. |
| `no_match` | Google reports no data: the keyword has too little search volume here. |
| `blocked` | Google kept answering "too many requests" after all retries. Run again later. |
| `unavailable` | Temporary problem on Google's side or an unexpected answer. |
| `filter_unsupported` | For example, the anchor keyword has no volume in the chosen place. |

### Switching from another Google Trends actor

From the Apify Google Trends Scraper: send the same input. These fields work as they are: `searchTerms`, `startUrls`, `isMultiple`, `geo`, `timeRange`, `customTimeRange`, `category`, `spreadsheetId`, `maxItems`. `viewedFrom` is read as `proxyCountry`, `maxRequestRetries` as `maxRetries`. `maxConcurrency`, `pageLoadTimeoutSecs` and `skipDebugScreen` are accepted and ignored (there is no browser). The actor logs a short notice for each renamed field.

The output uses the same field names (`interestOverTime_timelineData`, `interestBySubregion`, `interestByCity`, `interestBy`, `relatedQueries_top`, `relatedQueries_rising`, `relatedTopics_top`, `relatedTopics_rising`) and one row per keyword.

Differences you should know about:

- `interestOverTime_averages` stays empty, as Google leaves it. Use `averageInterest`.
- `isMultiple` splits a term like `nike, adidas` into compared keywords; each keyword is still its own row, with `value` holding one number (on the shared scale).
- Keywords with no search volume come back as a free `no_match` error row instead of a row full of zeros.
- No browser is used: it is faster and cheaper, and it does not save page snapshots.

Inputs of other popular Trends actors also work: `keyword` or `keywords` become `searchTerms`, `timeframe` becomes `timeRange` (`today 12-m` is the default 12 months), `dataTypes` switches related queries, related topics and interest by region on or off (`trending_searches` with `trendingSearchesGeo` gives a Trending now list), `maxResults` becomes `maxItems`, `property: "web"` is web search and a numeric `category` is read as its id.

### Use it from code

Python:

```python
from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("arcadium/google-trends").call(run_input={
    "searchTerms": ["electric car", "solar panels"],
    "geo": "US",
})
for row in client.dataset(run["defaultDatasetId"]).iterate_items():
    if row["rowType"] == "trend":
        print(row["searchTerm"], row["averageInterest"])
```

JavaScript:

```js
import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' });
const run = await client.actor('arcadium/google-trends').call({
  searchTerms: ['electric car', 'solar panels'],
  geo: 'US',
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items.length, 'rows');
```

### Pricing

You pay per row delivered (one keyword, or one Trending now search), at the price of your Apify plan. Error rows and unchanged keywords in monitoring mode are free.

| Apify plan | Per 1,000 rows |
| --- | --- |
| Free | $2.70 |
| Starter (Bronze) | $0.90 |
| Scale (Silver) | $0.45 |
| Business (Gold) | $0.27 |
| Platinum | $0.15 |
| Diamond | $0.15 |

Plus a one-off $0.00005 per GB of memory when a run starts.

Set a maximum cost per run in the Apify run options and the actor stops before it goes over.

### Related actors and data

- [Google News Scraper: Real Article URLs, Full Text](https://apify.com/arcadium/google-news)
- [YouTube Videos Scraper: Channels, Playlists, Search](https://apify.com/arcadium/youtube-videos)
- [AliExpress Search Scraper: Price, Orders, Rank](https://apify.com/arcadium/aliexpress-search)
- [Arcadium Data MCP Server](https://apify.com/arcadium/arcadium-mcp): AI agents can ask the same questions as tools (`trends`).

### Use cases

- SEO and content: find what is rising for a topic and plan around the season.
- E-commerce: compare product or brand interest across countries and weeks.
- Market research: track many brands on one scale with a scheduled monitor.
- News and social teams: poll "Trending now" every few hours.

### Limitations

- Public Google Trends data only. Nothing behind a login.
- Google shows relative interest (0-100), not search counts. Trending now gives a volume bracket (for example 100,000+), not an exact number.
- Google sometimes answers "too many requests". The actor retries on the same or a fresh connection, repeats the lookup for new tokens, and after a short pause tries the whole keyword again, so a keyword may take a few seconds (rarely a minute) longer; if all retries fail it returns a free `blocked` row.
- If three keywords in a row still end `blocked`, Google is limiting the whole shared connection pool. The actor then pauses for about a minute once and starts the next keywords at most every 5 seconds, so it does not prolong the limit for this run or for other users. After three successful keywords in a row it returns to normal speed. Expect a long list to take a few minutes longer on such a day rather than fail.
- Related topics are empty for many rare keywords; that is Google's answer, not a failure.
- Values for more than 5 compared keywords are approximate (see above).

### Privacy

Only aggregated search-interest data is collected. No user accounts, no personal data.

### FAQ

**Why do two runs of the same keyword differ slightly?**
Google samples its data and updates it continuously, and the last point of a period is still being filled in (`isPartial`).

**What do the codes in `geo` look like?**
Country codes like `US`, regions like `US-CA`, `GB-ENG`. Interest-by-region rows use the same codes.

**Something looks wrong in the output. Who do I tell?**
Open an issue on the actor page with the run link. We read them all.

# Actor input Schema

## `searchTerms` (type: `array`):

Keywords to look up, one result row per keyword. Example: \["electric car", "solar panels"]. Leave empty if you use Trends links, a Google Sheet or Trending now.

## `startUrls` (type: `array`):

Links copied from trends.google.com/trends/explore. Keywords, location, period and category are read from the link and win over the fields below. Several keywords in one link (q=a,b) are compared on one shared scale. Example: https://trends.google.com/trends/explore?q=nike,adidas\&geo=US\&date=today+3-m

## `geo` (type: `string`):

Where to measure interest: a two-letter country code (US, GB, DE) or a region code (US-CA, GB-ENG). Empty means worldwide. Example: US

## `timeRange` (type: `string`):

Period to measure. The default is the past 12 months. Short ranges give finer points: 'now 1-H' gives one point per minute, 'now 7-d' one per hour, 'today 12-m' one per week, 'all' one per month since 2004.

## `customTimeRange` (type: `string`):

Exact period as 'YYYY-MM-DD YYYY-MM-DD' (start, then end). Overrides Time range. Example: 2024-01-01 2024-12-31

## `category` (type: `string`):

Restrict to one Google Trends category, for example Finance or Travel. Empty means all categories.

## `property` (type: `string`):

Which Google search to measure: web search (default), image, news, YouTube or shopping search.

## `language` (type: `string`):

Language of labels such as region names and date text, for example en-US or de-DE. It does not change the numbers.

## `compareKeywords` (type: `boolean`):

Off: every keyword has its own 0-100 scale (like the leader). On: all search terms share one scale, so 50 for one keyword is half as popular as a 100 for another. Up to 5 keywords are exact (one Google request); more than 5 are chained through an anchor keyword (see below).

## `anchorKeyword` (type: `string`):

Only used when comparing more than 5 keywords. This keyword is repeated in every batch of 5 and links the batches to one scale. Pick one with steady, medium search volume that is in your list. Empty means the first keyword. Example: coffee

## `isMultiple` (type: `boolean`):

When on, a search term like 'nike, adidas' is split at commas and the parts are compared on one shared scale.

## `includeRelatedQueries` (type: `boolean`):

Adds the top and rising related search queries of every keyword (one extra request per keyword).

## `includeRelatedTopics` (type: `boolean`):

Adds the top and rising related topics of every keyword (one extra request per keyword). Often empty for rare keywords.

## `includeGeo` (type: `boolean`):

Adds interest by country (worldwide search), by subregion or by city (country search). Turn off to save requests.

## `onlyChanges` (type: `boolean`):

Monitoring mode. The first run returns every keyword once as the baseline. Later runs return only keywords with a new rising query or a move of the latest value by at least the threshold below; unchanged keywords are not returned and not charged. Run it on a schedule.

## `changeThreshold` (type: `integer`):

In only-changes mode: the latest weekly (or daily) value must move by at least this many index points (0-100 scale) since the last run to count as a change.

## `stateName` (type: `string`):

Name of the saved state for only-changes mode. Use different names for different monitors, for example brands-us and brands-de. Letters, digits, - and \_ only.

## `trendingGeos` (type: `array`):

Country codes whose live 'Trending now' list you want, one row per trending search. Example: \["US", "GB"]. Leave empty to skip.

## `trendingHours` (type: `string`):

How far back the Trending now list looks: 4, 24, 48 or 168 hours.

## `spreadsheetId` (type: `string`):

Optional. ID of a public Google Sheet (shared with 'Anyone with the link') whose first column lists search terms; row 1 is a header. Example: 1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgVE2upms

## `maxItems` (type: `integer`):

Stops after this many result rows. 0 means no limit.

## `includeErrorRows` (type: `boolean`):

Adds a free, machine-readable row (code and message) for every keyword or link that could not be read, so a failure is never silent. Codes: invalid_input, no_match, blocked, unavailable, filter_unsupported.

## `maxRetries` (type: `integer`):

How often a request is retried, each time on a fresh connection, after Google answers too many requests. Higher is slower but fails less.

## `proxyCountry` (type: `string`):

Two-letter country of the connection used to ask Google, for example US or DE (default US). 'viewedFrom' is accepted too. The numbers do not depend on it.

## `proxyConfiguration` (type: `object`):

Leave empty. The actor picks the cheapest connection that works. Your own proxy URLs are used if you set them.

## Actor input object example

```json
{
  "searchTerms": [
    "electric car",
    "solar panels"
  ],
  "startUrls": [
    {
      "url": "https://trends.google.com/trends/explore?q=nike,adidas&geo=US&date=today+3-m"
    }
  ],
  "geo": "US",
  "timeRange": "",
  "customTimeRange": "2024-01-01 2024-12-31",
  "category": "",
  "property": "",
  "language": "de-DE",
  "compareKeywords": false,
  "anchorKeyword": "coffee",
  "isMultiple": false,
  "includeRelatedQueries": true,
  "includeRelatedTopics": true,
  "includeGeo": true,
  "onlyChanges": false,
  "changeThreshold": 15,
  "stateName": "brands-us",
  "trendingGeos": [
    "US"
  ],
  "trendingHours": "24",
  "spreadsheetId": "1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgVE2upms",
  "maxItems": 0,
  "includeErrorRows": true,
  "maxRetries": 6,
  "proxyCountry": "US"
}
```

# Actor output Schema

## `results` (type: `string`):

All rows of this run in the default dataset.

## `view_overview` (type: `string`):

One line per keyword: average interest, scale used and, in monitoring mode, what changed.

## `view_timeline` (type: `string`):

The full timeline per keyword; open a row to see every point.

## `view_related` (type: `string`):

No description

## `view_regions` (type: `string`):

No description

## `view_trending` (type: `string`):

No description

## `view_errors` (type: `string`):

Free rows for inputs that could not be read. code is one of invalid_input, no_match, blocked, unavailable, filter_unsupported.

## `record_stats` (type: `string`):

Requests, data volume, retries and cost per result for this run.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "searchTerms": [
        "webscraping"
    ],
    "maxRetries": 6,
    "proxyCountry": "US"
};

// Run the Actor and wait for it to finish
const run = await client.actor("arcadium/google-trends").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "searchTerms": ["webscraping"],
    "maxRetries": 6,
    "proxyCountry": "US",
}

# Run the Actor and wait for it to finish
run = client.actor("arcadium/google-trends").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "searchTerms": [
    "webscraping"
  ],
  "maxRetries": 6,
  "proxyCountry": "US"
}' |
apify call arcadium/google-trends --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,arcadium/google-trends"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/sChC3c8koPyJZCXkS/builds/zCGGTz9SW3h5RqBbI/openapi.json