# Google Trending Now History (`seodatalab/google-trending-now-history`) Actor

Search every Google Trending Now trend since Nov 2024 across 1,358 countries, regions and US metros: find every time a keyword trended or what was trending on any day, with search volume, duration and related searches. Nov 2024 – May 2026 is free.

- **URL**: https://apify.com/seodatalab/google-trending-now-history.md
- **Developed by:** [Carter Price](https://apify.com/seodatalab) (community)
- **Categories:** SEO tools, News
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.75 / 1,000 trend from the live archives

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 Trending Now History

Search **every trend Google listed on Trending Now since November 2024**, across 1,358 countries, regions and US metro areas. Find every time a keyword trended, see what was trending anywhere on any day, and get search volume, start and end times, duration and related searches.

Google keeps Trending Now for only 7 days, and there is no official way to look further back. This actor gives you the history.

### Why this one

- **18+ months of history.** Over 10 million trends from 28 Nov 2024 onward, and growing every day.
- **Every location Google covers.** 126 countries, about 1,000 regions and 210 US metro areas.
- **Fast.** Searching all of the history for a keyword takes seconds. Nothing is scraped at run time.
- **The academic archive is free.** Rows from Nov 2024 to May 2026 come from a public research dataset and are **never charged** (see Sources). You pay only for rows from our own daily collection.

### Examples

| You want | Input |
|---|---|
| Every time "taylor swift" trended in the US | `{"keywords": ["taylor swift"], "geos": ["US"]}` |
| What the UK searched on Super Bowl Sunday | `{"geos": ["GB"], "dateFrom": "2025-02-09", "dateTo": "2025-02-09", "sortBy": "searchVolume"}` |
| The biggest US sports trends last week | `{"geos": ["US"], "categories": ["Sports"], "sortBy": "searchVolume"}` |
| Where a brand trended worldwide | `{"keywords": ["nintendo switch 2"], "sortBy": "oldest"}` |
| All US states and metros for a topic | `{"keywords": ["hurricane"], "geos": ["US"], "includeSubregions": true}` |

### Input

| Field | Notes |
|---|---|
| `keywords` | Terms to find. They're matched against trend titles and, unless you turn it off, related searches. Leave empty to list everything in the date range. |
| `matchMode` | `contains` (default) or `exact`. |
| `geos` | Country, region or US metro codes. Leave empty for all locations. `includeSubregions` adds the regions and metros of each country. |
| `dateFrom`, `dateTo` | The day a trend started (UTC). The default is all history when you give keywords, otherwise the last 7 days. |
| `categories` | Sports, Politics, Entertainment and so on. Only the live archive has categories. |
| `minSearchVolume`, `sortBy`, `maxResults` | Filter, order and cap the results. |
| `includeAcademicArchive` | Default on. Turn it off to get only the live archive. |

### Output

```json
{
  "title": "super bowl 2025",
  "geo": "US",
  "geoName": "United States",
  "startedAt": "2025-02-09T14:20:00Z",
  "endedAt": null,
  "durationMinutes": null,
  "searchVolume": 10000000,
  "increasePercent": null,
  "bestRank": null,
  "categories": [],
  "relatedSearches": ["2025 halftime show", "kendrick lamar", "super bowl 2024 halftime show", "…1,068 in total"],
  "firstSeen": "2025-02-10T00:00:00Z",
  "lastSeen": "2025-02-10T00:00:00Z",
  "daysObserved": 1,
  "source": "academic-archive",
  "charged": false,
  "attribution": "GoogleTrendArchive by Aleksandra Urman, Anikó Hannák and Joachim Baumann ...",
  "exploreUrl": "https://trends.google.com/trends/explore?q=super%20bowl%202025&geo=US&date=2025-02-09%202025-02-11"
}
```

- **Search volume** is Google's bucket, given as its lower bound (10000000 means "10M+").
- **Live-archive rows** also carry `increasePercent`, `bestRank` (best position on Google's list) and `categories`.
- **`endedAt` is null** when the trend was still active the last time it was collected.
- **Trends seen on several days** appear once, with `firstSeen`, `lastSeen` and `daysObserved`.

### Sources and coverage

| Period | Source | Price |
|---|---|---|
| 28 Nov 2024 – 17 May 2026 | **GoogleTrendArchive** by Aleksandra Urman, Anikó Hannák and Joachim Baumann (University of Zurich / Stanford AI Lab), [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/), [doi:10.57967/hf/7531](https://doi.org/10.57967/hf/7531). We changed the column names and types, split out related searches, and split the data into monthly files. | **Free** |
| 2 Nov 2026 onward | Our own daily collection of every location, updated each morning (UTC) | Charged |

- **There's no data from 18 May to 1 Nov 2026.** The run log warns you when your dates fall in that gap.
- **The academic archive has two short outages:** parts of September 2025 and January 2026.
- If you use academic-archive rows in research, please cite the authors (the `attribution` field gives the citation).

### Pricing

- **$1.00 per 1,000 trends from the live archive**, plus a small start fee per run.
- **Academic-archive rows are free.**
- To keep costs down, use `maxResults`, dates or `minSearchVolume`, or set `includeAcademicArchive` to keep or drop the free rows.

### Use cases

- **Journalism and research:** what a country was searching on any day, and how a story spread between countries.
- **Marketing and SEO:** seasonality of trending topics, and evergreen versus one-off spikes.
- **Brands and agencies:** every time your brand or a competitor trended, where, and how big.
- **Data science:** training and back-testing data for attention and event-detection models.

### Pair it with

- [Google Trending Now Scraper](https://apify.com/seodatalab/google-trending-now): live trends right now, for any location.
- [Google Trends Scraper](https://apify.com/seodatalab/google-trends-scraper): interest over time for any trend title.

# Actor input Schema

## `keywords` (type: `array`):

Find every time these terms trended. Matches trend titles (and related searches, see below), case-insensitive. Leave empty to list everything that trended in the date range.

## `matchMode` (type: `string`):

"contains" finds 'taylor swift tickets' for 'taylor swift'. "exact" finds only 'taylor swift'.

## `searchRelatedSearches` (type: `boolean`):

Also return trends whose related searches contain a keyword (e.g. 'eagles vs chiefs' for 'super bowl').

## `geos` (type: `array`):

Country (US, GB, IN…), region (US-CA, IN-MH…) or US metro codes (501 = New York). Empty = all 1,358 locations.

## `includeSubregions` (type: `boolean`):

US also returns US-CA, US-NY… and US metro areas.

## `dateFrom` (type: `string`):

Trends that started on or after this day (UTC). Default: 2024-11-28 with keywords, otherwise 7 days ago.

## `dateTo` (type: `string`):

Trends that started on or before this day (UTC). Default: today.

## `categories` (type: `array`):

Only trends in these categories. Categories exist only in the live archive (from Nov 2026), so this filter excludes academic-archive rows.

## `minSearchVolume` (type: `integer`):

Skip smaller trends. Volumes are Google's buckets (e.g. 20000 = '20K+').

## `sortBy` (type: `string`):

Order of results.

## `maxResults` (type: `integer`):

Stop after this many trends (up to 100,000 per run; split bigger exports by date).

## `includeAcademicArchive` (type: `boolean`):

Rows from GoogleTrendArchive (Urman, Hannák & Baumann, CC BY 4.0) are free and never charged.

## `maxDataAgeHours` (type: `integer`):

For monitoring: return no results when the newest collected data is older than this many hours.

## Actor input object example

```json
{
  "keywords": [
    "taylor swift"
  ],
  "matchMode": "contains",
  "searchRelatedSearches": true,
  "geos": [
    "US"
  ],
  "includeSubregions": false,
  "minSearchVolume": 0,
  "sortBy": "newest",
  "maxResults": 1000,
  "includeAcademicArchive": true
}
```

# Actor output Schema

## `overview` (type: `string`):

One row per trend per location, with start/end time, search volume and source.

## `stats` (type: `string`):

Matching trends, charged live-archive rows and free academic-archive rows.

# 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 = {
    "keywords": [
        "taylor swift"
    ],
    "geos": [
        "US"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("seodatalab/google-trending-now-history").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 = {
    "keywords": ["taylor swift"],
    "geos": ["US"],
}

# Run the Actor and wait for it to finish
run = client.actor("seodatalab/google-trending-now-history").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 '{
  "keywords": [
    "taylor swift"
  ],
  "geos": [
    "US"
  ]
}' |
apify call seodatalab/google-trending-now-history --silent --output-dataset

```

## MCP server setup

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

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/19Y66qS9G03PWdaEn/builds/yMIcRxrSJgmKlADwe/openapi.json