# What was trending on Google on a past date

**Use case:** 

List what a country searched for on any past day: every Google Trending Now trend that started that day, biggest first, with search volume and related searches. Example: the UK on Super Bowl Sunday 2025.

## Input

```json
{
  "keywords": [
    "taylor swift"
  ],
  "matchMode": "contains",
  "searchRelatedSearches": true,
  "geos": [
    "GB"
  ],
  "includeSubregions": false,
  "dateFrom": "2025-02-09",
  "dateTo": "2025-02-09",
  "minSearchVolume": 0,
  "sortBy": "searchVolume",
  "maxResults": 200,
  "includeAcademicArchive": true
}
```

## Output

```json
{
  "startedAt": {
    "label": "Started at",
    "format": "string"
  },
  "geo": {
    "label": "Geo",
    "format": "string"
  },
  "title": {
    "label": "Title",
    "format": "string"
  },
  "searchVolume": {
    "label": "Search volume",
    "format": "number"
  },
  "durationMinutes": {
    "label": "Duration minutes",
    "format": "integer"
  },
  "categories": {
    "label": "Categories",
    "format": "array"
  },
  "source": {
    "label": "Source",
    "format": "string"
  }
}
```

## How it works

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

The Google Trending Now History Actor is ready to run with the inputs already set for "What was trending on Google on a past date". [Sign up or log in](https://console.apify.com/create-task-from-example/koVZ8GYaFP3JsPUvM) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "What was trending on Google on a past date" task

The Google Trending Now History Actor will start running based on the input automatically. You can also change all the input fields, like keywords, keyword match, and more, to match your specific use case.

### 3. Receive the "What was trending on Google on a past date" 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 started at, geo, title, 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 "What was trending on Google on a past date" task via API](https://apify.com/seodatalab/google-trending-now-history.md).

## FAQ

### Which time zone are dates in?

UTC. A trend belongs to the day it started.

### Is this free?

Days from 28 Nov 2024 to 17 May 2026 come from a free academic archive, so their rows are not charged. You only pay the small start fee.

## About this Actor

This example demonstrates how to use [Google Trending Now History](https://apify.com/seodatalab/google-trending-now-history.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/seodatalab/google-trending-now-history.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/seodatalab/google-trending-now-history.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`).