# Google Trends Keyword Opportunity Finder (`azzarilabs/google-trends-keyword-intelligence`) Actor

Compare keyword demand, discover rising searches and regional opportunities, and prioritize topics with an explainable Trend Opportunity Score.

- **URL**: https://apify.com/azzarilabs/google-trends-keyword-intelligence.md
- **Developed by:** [Azzari Labs](https://apify.com/azzarilabs) (community)
- **Categories:** SEO tools, Marketing
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$0.25 / 1,000 trend results

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

## Google Trends Keyword Opportunity Finder

Decide which topics deserve content, campaign, product, or market attention before investing more time or budget.

Enter up to five keywords and receive Google Trends interest over time, regional demand, related and rising searches, plus an explainable **Trend Opportunity Score**. No Google login or API key is required.

### Quick Start

1. Enter one keyword—or up to five terms you want to compare.
2. Choose a market and analysis period.
3. Click **Start** and review the Dataset, `OUTPUT`, or visual `REPORT.html`.

The prefilled example is ready to run in under 30 seconds.

```json
{
  "keywords": ["ChatGPT", "Claude"],
  "geo": "US",
  "timeRange": "today 3-m",
  "property": "web"
}
```

All other settings are optional. Their defaults include the trend timeline, regional demand, and related queries.

### Input → result → decision

| Input | What you receive | Decision it supports |
|---|---|---|
| Keywords or topics | Relative interest, momentum, volatility, and score | Which topic deserves priority? |
| Market and period | Trend line and regional demand for the selected context | Where and when is interest strongest? |
| Search channel | Web, YouTube, News, Images, or Shopping signals | Which channel fits the opportunity? |
| Optional output controls | Timeline, regions, and related/rising queries | Which evidence should enter your workflow? |

### Three practical use cases

#### 1. Prioritize an SEO or content calendar

Compare candidate topics, inspect momentum and rising queries, then choose the terms with the strongest current evidence.

#### 2. Validate regional demand before a campaign

Measure the same topic in a target country and use the regional rows to decide where localization or media spend deserves a closer look.

#### 3. Monitor products, categories, or competitors

Schedule the same bounded comparison and track changes in relative interest, volatility, breakout queries, and opportunity score over time.

### Example output

This sanitized aggregate comes from the retained successful validation run for the current Actor release:

```json
{
  "status": "SUCCEEDED",
  "records_delivered": 125,
  "keywords_analyzed": 1,
  "time_points": 53,
  "regions": 51,
  "related_queries": 20,
  "warnings": []
}
```

Dataset rows identify their shape with `record_type`:

- `keyword_summary`: current, average, median and peak interest; momentum; volatility; score; level; confidence; reasons.
- `interest_over_time`: date, timestamp, normalized `interest_value`, and partial-period flag.
- `interest_by_region`: region name/code and normalized interest.
- `related_query`: top/rising type, rank, observed value, growth when supplied, and `breakout`.

`OUTPUT` summarizes the run. `REPORT.html` provides a leaderboard, compact trend charts, related queries, regions, warnings, and methodology.

### Pricing

The current price is **USD 0.00025 per valid unique `trend-result` Dataset row delivered**.

| Delivered rows | Price |
|---:|---:|
| 100 | USD 0.025 |
| 1,000 | USD 0.25 |
| 10,000 | USD 2.50 |

The billable unit is a delivered Dataset row, not an input keyword. One keyword can produce a summary plus multiple timeline, regional, and related-query rows. Failed requests, empty results, warnings, duplicates, invalid records, `OUTPUT`, and `REPORT.html` are not billed.

### Verified proof points

- Current production build: 0.1.2.
- Retained Cloud validation: 125 unique records delivered in 11.737 seconds with zero warnings.
- Dataset, `OUTPUT`, `REPORT.html`, deduplication, and delivery-before-charge contracts validated.
- 85 deterministic tests previously passed across input, acquisition, parsing, scoring, partial results, billing, and schemas.
- Values remain traceable to public Google Trends responses; missing data is not invented.

These checks demonstrate the validated contract, not a service-level guarantee or a promise of complete upstream coverage.

### Limitations

- Google Trends values are normalized relative-interest indices from 0–100, not absolute search volume or market share.
- Results depend on the selected terms, market, period, category, and search channel.
- Google can change or rate-limit public endpoints; a valid run can contain warnings or fewer record types.
- Regional and related-query coverage depends on what Google returns for that request.
- The Trend Opportunity Score ranks evidence observed in the current run; it does not predict revenue or financial performance.

### Start now

Use the prefilled keyword, choose your market and period, then click **Start**. Replace the example with your own topic when you are ready.

### Responsible use

Use this Actor in accordance with Google’s terms and applicable law. This independent product is not affiliated with, endorsed by, sponsored by, or officially connected to Google.

# Actor input Schema

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

Enter 1–5 terms. Terms in the same run are measured on the same relative 0–100 Google Trends scale.

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

Where to measure interest. Use a Google Trends code such as US, MX, BR, GT, ES, GB, DE, FR, or CA.

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

Choose the period used for the trend comparison.

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

Measure interest on Web Search, YouTube, News, Images, or Shopping.

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

Use 0 for all categories, or a Google Trends category ID to disambiguate a term.

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

Language used for source labels, for example en-US or es-ES.

## `includeInterestOverTime` (type: `boolean`):

Return normalized interest points over the selected period.

## `includeRegions` (type: `boolean`):

Return interest by region when Google exposes it.

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

Return top and rising searches associated with each keyword.

## `maxRelatedQueries` (type: `integer`):

Maximum top and rising query rows returned per keyword.

## Actor input object example

```json
{
  "keywords": [
    "ChatGPT",
    "Claude"
  ],
  "geo": "US",
  "timeRange": "today 3-m",
  "property": "web",
  "category": 0,
  "language": "en-US",
  "includeInterestOverTime": true,
  "includeRegions": true,
  "includeRelatedQueries": true,
  "maxRelatedQueries": 10
}
```

# Actor output Schema

## `output` (type: `string`):

No description

## `report` (type: `string`):

No description

## `dataset` (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 = {
    "keywords": [
        "ChatGPT"
    ],
    "geo": "US",
    "timeRange": "today 12-m",
    "property": "web"
};

// Run the Actor and wait for it to finish
const run = await client.actor("azzarilabs/google-trends-keyword-intelligence").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": ["ChatGPT"],
    "geo": "US",
    "timeRange": "today 12-m",
    "property": "web",
}

# Run the Actor and wait for it to finish
run = client.actor("azzarilabs/google-trends-keyword-intelligence").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": [
    "ChatGPT"
  ],
  "geo": "US",
  "timeRange": "today 12-m",
  "property": "web"
}' |
apify call azzarilabs/google-trends-keyword-intelligence --silent --output-dataset

```

## MCP server setup

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

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/dt3FLVYspJ0KlU1ii/builds/QkqclSQXL7oMU4NjW/openapi.json