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

Google Trends data for any keywords: interest over time, interest by country/region/city, related queries and topics (top and rising), comparisons of up to 5 terms and today's Trending now searches by country. Automatic retries, so runs don't fail on Google's rate limits. Pay per term.

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

## Pricing

from $2.00 / 1,000 search term analyzeds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

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

### What does Google Trends Scraper do?

**Google Trends Scraper** gets **Google Trends data for any keywords** through an API: **interest over time**, **interest by country, region, city or US metro area**, **related queries** (top and **rising / breakout**), plus **comparisons of up to 5 terms** on the same 0-100 scale and a **plain-language trend summary** for each term (rising, falling or stable, peak date and % change). It also returns **Trending now**: today's trending searches in any country, with approximate search volume and related news.

Google limits how fast Trends can be queried, which is why many Trends tools fail part of the time. This Actor **retries automatically on fresh sessions and IPs**, so your runs don't fail on those limits, and you **pay only for terms that return data**.

It runs on the Apify platform, so you also get an API, **scheduling** (e.g. weekly trend reports), integrations (Google Sheets, Make, Zapier, n8n, Slack) and access for **AI agents through the [Apify MCP server](https://mcp.apify.com)**.

### Why use it?

- 📈 **Market and product research**: is demand for "air fryer" or "heat pump" growing, and where?
- 🔍 **SEO and content planning**: rising and breakout related queries show new topics before keyword tools do.
- 🆚 **Brand and competitor tracking**: compare up to 5 brands in one query and schedule it weekly.
- 🗺️ **Regional targeting**: find the states, regions or cities where a term is most popular.
- 📰 **Newsjacking and social media**: Trending now lists what people are searching today, with the news behind each trend.
- 🔔 **Weekly alerts**: schedule it with **Monitor new rising searches** and get only the rising searches that appeared since last week.
- 🤖 **AI agents and dashboards**: clean JSON with a ready-made trend summary, one record per query, ready for charts, BI tools and LLMs.

### How to get Google Trends data

1. Click **Try for free**.
2. Enter your **search terms**, one query per line. To compare terms, put up to 5 on one line separated by commas: `chatgpt, gemini, claude`. You can also paste a **Google Trends link** you already use.
3. Choose the **countries** (e.g. `US`, `GB`, or `worldwide`) and the **time range**.
4. Click **Start**. Each query takes a few seconds.
5. Download the results as JSON, CSV or Excel, or open the **Interest over time** view (one row per date) for charts.

### Input

| Field | Description | Default |
|---|---|---|
| `searchTerms` | One query per line; up to 5 comma-separated terms are compared. Google Trends links and topic IDs (`/m/...`) also work | required (or `trendingNow`) |
| `geo` | Country or region codes (`US`, `DE`, `US-CA`) or `worldwide`; each query runs once per geo | worldwide |
| `timeframe` | Past hour, 4 hours, day, 7 days, 30 days, 90 days, 12 months, 5 years, or 2004-present | past 12 months |
| `customTimeRange` | Exact dates, e.g. `2024-01-01 2024-06-30` | - |
| `outputs` | `interestOverTime`, `interestByRegion`, `relatedQueries`, `relatedTopics` (often empty, see FAQ) | first three |
| `searchProperty` | `web`, `images`, `news`, `shopping` (Google Shopping) or `youtube` | web |
| `trendingNow` | Countries for today's trending searches | - |
| `monitorRising` | Scheduled runs: list only rising searches that are new since the previous run | `false` |
| `regionResolution` | `auto`, `COUNTRY`, `REGION`, `CITY` or `DMA` | auto |
| `includeLowVolumeRegions` | Also return low-volume regions and cities (recommended with `CITY`) | `false` |
| `category` | Google Trends category ID (0 = all) | 0 |

```json
{
  "searchTerms": ["solar panels", "chatgpt, gemini, claude"],
  "geo": ["US"],
  "timeframe": "today 12-m",
  "trendingNow": ["US", "GB"]
}
```

### Output

One record per query and geo. You can download the dataset in various formats such as JSON, HTML, CSV, or Excel.

```json
{
  "type": "explore",
  "terms": ["chatgpt", "claude"],
  "geo": "US",
  "timeframe": "today 3-m",
  "status": "ok",
  "averages": { "chatgpt": 64, "claude": 19 },
  "summary": {
    "claude": { "latest": 17, "average": 18.7, "peak": 30, "peakDate": "2026-07-08T00:00:00Z", "changePercent": -27.1, "trend": "falling" }
  },
  "interestOverTime": [
    { "date": "2026-06-26T00:00:00Z", "label": "Jun 26, 2026", "values": { "chatgpt": 62, "claude": 23 } }
  ],
  "interestByRegion": [
    { "geoCode": "US-CA", "geoName": "California", "values": { "chatgpt": 74, "claude": 26 } }
  ],
  "relatedQueries": {
    "claude": {
      "top": [{ "query": "claude ai", "value": 100 }],
      "rising": [{ "query": "kimi k3", "value": 9950, "label": "Breakout", "growthPercent": 9950 }]
    }
  },
  "exploreUrl": "https://trends.google.com/trends/explore?q=chatgpt%2Cclaude&date=today+3-m&hl=en-US&geo=US"
}
```

Trending now rows look like this:

```json
{
  "type": "trending", "geo": "GB", "rank": 1, "query": "nepal vs japan",
  "approxTraffic": "1000+", "approxTrafficNumber": 1000, "published": "2026-09-25T19:20:00-07:00",
  "news": [{ "title": "…", "url": "https://…", "source": "Ratopati" }]
}
```

### Data fields

| Field | Description |
|---|---|
| `interestOverTime` | Interest per date on a 0-100 scale (100 = peak popularity in the period). `isPartial` marks the current, incomplete period |
| `averages` | Average interest of each term over the period |
| `summary` | Per term: `latest`, `average`, `peak`, `peakDate`, `changePercent` (last fifth of the period vs first fifth) and `trend`: `rising` (≥ +20%), `falling` (≤ -20%) or `stable` |
| `newRising` | With `monitorRising`: rising searches not seen in previous runs |
| `interestByRegion` | Interest per country, region, city or DMA (0-100, relative to the top location) |
| `relatedQueries` | `top`: most popular related searches; `rising`: fastest growing, with `growthPercent`; `Breakout` means more than +5000% |
| `exploreUrl` | The same query on trends.google.com |
| `rank`, `query`, `approxTraffic`, `news` | Trending now: position, search, approximate searches and news articles |

### How much does Google Trends scraping cost?

| Event | Price |
|---|---|
| Run start (per GB of memory, default 512 MB) | $0.001 |
| Search term analyzed (one term in one geo, all selected outputs) | **$0.002** |
| Trending now list (one country) | $0.002 |

A comparison of 3 terms in 2 countries is 6 terms: **$0.012**. 1,000 terms cost **$2**. Failed queries are never billed. Set **Max cost per run** and the Actor stops cleanly at that limit.

### Use it with AI agents (MCP)

Add `https://mcp.apify.com?tools=fguiraud/google-trends-scraper` to Claude, Cursor or any MCP client and ask:

- *"Is interest in heat pumps growing in Germany? Show me the last 5 years."*
- *"Compare ChatGPT, Gemini and Claude in the US over the last 90 days and list rising related searches."*
- *"What is trending in the UK today?"*

Smallest useful input for an agent: `{"searchTerms": ["heat pump"], "geo": ["DE"], "outputs": ["interestOverTime"]}`.

### Tips

- **Values are relative, not absolute search counts.** 100 is the peak of the period for the terms compared together, so only compare numbers from the same query.
- Choose only the **outputs** you need: each one is a separate request to Google, so fewer outputs are faster.
- For many terms, keep **Proxy** on and raise **Parallel queries**: each worker uses its own IP.
- Long runs are safe: if the platform restarts the run, finished queries are skipped and never charged twice.
- **Schedule** a weekly run to build your own trend history over time, and turn on **Monitor new rising searches** to be alerted only about what is new.
- The current, incomplete period (`isPartial`) is left out of `summary`, so a half-finished week never looks like a drop.

### Related tools

- Found a rising search and want to know why? [Google News Scraper + Full Article Text](https://apify.com/fguiraud/google-news-scraper) returns the news behind it, with the real article URL and the full text as Markdown, in any country and language.

### FAQ and limitations

- **"Not enough search volume"**: Google returns no data for rare terms in small countries or short periods. The result has `status: "no-data"` and a `note`, and **it is not billed**.
- **Few or no cities?** Google hides low-volume cities. Turn on **Include low search volume regions** for city-level detail.
- **Related topics**: Google currently returns this list empty for most queries, so it is off by default. You can still request it with `relatedTopics`; you are not charged extra for it.
- **Is it legal?** The Actor reads public, aggregated Google Trends data, the same data shown on trends.google.com. It does not collect personal data.
- Found a problem or need a feature? Open an issue on the **Issues** tab. Replies within 48 hours.

# Actor input Schema

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

One query per line. To compare terms on the same scale, put up to 5 on one line separated by commas (e.g. 'python, javascript, rust'). You can also paste a Google Trends link (trends.google.com/trends/explore?...): it keeps its own countries, dates and filters. Google topic IDs such as '/m/0dl567' work too. Each plain line is run for every geo below.

## `geo` (type: `array`):

Where to measure: country codes (US, GB, DE, BR...), regions (US-CA, GB-SCT...) or 'worldwide'. Several values run each query once per geo.

## `timeframe` (type: `string`):

Period to analyze. Hourly data for the last hours or days, daily data up to 9 months, weekly and monthly beyond.

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

Optional exact dates instead of the time range above, as 'YYYY-MM-DD YYYY-MM-DD' (e.g. '2024-01-01 2024-06-30').

## `outputs` (type: `array`):

'interestOverTime': 0-100 interest per date. 'interestByRegion': 0-100 interest per country, region or city. 'relatedQueries': top and rising (breakout) searches related to each term. 'relatedTopics': related topics, only when Google provides them (currently empty for most queries). Fewer outputs make each query faster.

## `searchProperty` (type: `string`):

Which Google search to measure: web search, image search, news, Google Shopping or YouTube.

## `trendingNow` (type: `array`):

Also get today's trending searches for these countries (e.g. US, GB, IN), with approximate search volume and related news articles. Works on its own, without search terms.

## `monitorRising` (type: `boolean`):

For scheduled runs: remember the rising related searches of each query (in a key-value store named 'google-trends-monitor' in your account) and list in 'newRising' only the ones that are new since the previous run. Ideal for weekly content-idea or brand alerts.

## `regionResolution` (type: `string`):

Level of 'Interest by region'. Auto: countries for worldwide queries, regions/states within a country. City and DMA (US metro areas) give more detail.

## `includeLowVolumeRegions` (type: `boolean`):

Also return regions and cities with little search volume (Google's checkbox of the same name). Recommended for city-level detail, where most cities are otherwise hidden.

## `category` (type: `integer`):

Google Trends category to narrow the meaning of a term (0 = all categories). Examples: 5 Computers & Electronics, 7 Finance, 45 Health, 71 Food & Drink, 958 Jobs & Education. The ID is the 'cat=' value in a Google Trends URL.

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

Language for region names, topics and labels, e.g. en-US, es, de, fr, pt-BR.

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

Apify Proxy spreads requests over several IPs so Google's rate limits hit less often. Recommended.

## `maxConcurrency` (type: `integer`):

How many queries run at the same time, each on its own session. More is faster but may meet rate limits sooner.

## `failOnError` (type: `boolean`):

Mark the run as FAILED when any query returns no data after all retries. Useful for monitoring pipelines.

## Actor input object example

```json
{
  "searchTerms": [
    "solar panels",
    "chatgpt, gemini, claude"
  ],
  "geo": [
    "US"
  ],
  "timeframe": "today 12-m",
  "outputs": [
    "interestOverTime",
    "interestByRegion",
    "relatedQueries"
  ],
  "searchProperty": "web",
  "monitorRising": false,
  "regionResolution": "auto",
  "includeLowVolumeRegions": false,
  "category": 0,
  "language": "en-US",
  "proxyConfiguration": {
    "useApifyProxy": true
  },
  "maxConcurrency": 3,
  "failOnError": false
}
```

# Actor output Schema

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

No description

# 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": [
        "solar panels",
        "chatgpt, gemini, claude"
    ],
    "geo": [
        "US"
    ],
    "proxyConfiguration": {
        "useApifyProxy": true
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("fguiraud/google-trends-scraper").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": [
        "solar panels",
        "chatgpt, gemini, claude",
    ],
    "geo": ["US"],
    "proxyConfiguration": { "useApifyProxy": True },
}

# Run the Actor and wait for it to finish
run = client.actor("fguiraud/google-trends-scraper").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": [
    "solar panels",
    "chatgpt, gemini, claude"
  ],
  "geo": [
    "US"
  ],
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}' |
apify call fguiraud/google-trends-scraper --silent --output-dataset

```

## MCP server setup

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

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/Ke5x2n3F4R94SnKM3/builds/CM1wUSdwXdZLEnvAG/openapi.json