Google Trends Scraper (Interest, Regions & Rising Queries) 📈

Fast, resilient, and enterprise-grade Google Trends scraper. Extract historical search interest, subregional geographic distributions, and breakout rising queries with automated anti-throttling session management.

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🚀 Why Use This Scraper?

Most Google Trends scrapers break or fail unpredictably (often showing a 20%+ failure rate) due to aggressive Google rate-limiting (429 Too Many Requests) and brittle token parsing.

This Actor is engineered specifically for resilience:

• Automated Session Warming: Re-authenticates and manages clean Google session tokens dynamically.
• Jittered Exponential Backoff: Gracefully handles temporary spikes without failing your run.
• Batch Processing: Processes up to 5 comparison terms per query to reduce run time and compute cost.
• Agent & MCP Ready: Delivers clean, structured JSON optimized for LLMs, RAG pipelines, and automated market research.

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🔍 What Data Can You Extract?

1. Interest Over Time: Multi-point timeline index (0–100) across custom time horizons.
2. Regional Breakdown: Geographic interest across US states, DMAs (designated market areas), or global countries.
3. Related & Rising Queries: Uncover emerging keyword opportunities and breakout viral topics before they peak.

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🛠️ Input Parameters

Configure your run via the Apify Console UI or pass the following JSON payload via API:

{
  "searchTerms": ["artificial intelligence", "quantum computing"],
  "timeRange": "today 12-m",
  "geo": "US",
  "property": "web",
  "includeInterestOverTime": true,
  "includeSubregions": true,
  "includeRelatedQueries": true
}

Parameter Reference

Field	Type	Description	Allowed Values / Examples	Default
searchTerms (required)	Array of strings	Keywords or search queries to track.	["tesla", "rivian"]	["artificial intelligence"]
timeRange	String	Time window for historical trend analysis.	now 1-H, now 4-H, now 1-d, now 7-d, today 1-m, today 3-m, today 12-m, today 5-y, all	today 12-m
geo	String	Two-letter ISO country code. Leave blank for worldwide.	US, GB, DE, CA, AU, FR	US
property	String	Search engine vertical.	web, images, news, youtube, froogle (Shopping)	web
category	Integer	Google Trends category ID. 0 for all categories.	0, 396 (Real Estate), 5 (Computers)	0
includeInterestOverTime	Boolean	Include historical timeline index datapoints.	true, false	true
includeSubregions	Boolean	Include breakdown by state/region/country.	true, false	true
includeRelatedQueries	Boolean	Include top and rising / breakout searches.	true, false	true

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📊 Sample Output

Results are pushed directly to your Apify Dataset. You can export to JSON, CSV, Excel, or consume via REST API:

[
  {
    "keyword": "quantum computing",
    "geo": "US",
    "timeRange": "today 12-m",
    "scrapedAt": "2026-11-03T06:12:20.649Z",
    "interestOverTime": [
      {
        "time": "Nov 2 – 8, 2025",
        "value": 14
      },
      {
        "time": "Nov 9 – 15, 2025",
        "value": 16
      },
      {
        "time": "Dec 7 – 13, 2025",
        "value": 27
      }
    ],
    "regionalInterest": [
      {
        "geoCode": "US-MD",
        "geoName": "Maryland",
        "value": 100,
        "formattedValue": "100"
      },
      {
        "geoCode": "US-CO",
        "geoName": "Colorado",
        "value": 96,
        "formattedValue": "96"
      },
      {
        "geoCode": "US-MA",
        "geoName": "Massachusetts",
        "value": 92,
        "formattedValue": "92"
      }
    ],
    "relatedQueries": {
      "top": [
        {
          "query": "what is quantum computing",
          "value": 100,
          "formattedValue": "100"
        },
        {
          "query": "quantum computing stocks",
          "value": 68,
          "formattedValue": "68"
        }
      ],
      "rising": [
        {
          "query": "quantum computing ai breakthrough",
          "value": 1250,
          "formattedValue": "Breakout"
        }
      ]
    }
  }
]

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💻 How to Run Programmatically (Python & JavaScript)

JavaScript / Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });

const run = await client.actor('phoebe-labs/google-trends-scraper').call({
    searchTerms: ['electric vehicles', 'hybrid cars'],
    timeRange: 'today 12-m',
    geo: 'US',
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Python

from apify_client import ApifyClient

client = ApifyClient('YOUR_API_TOKEN')

run = client.actor('phoebe-labs/google-trends-scraper').call(run_input={
    'searchTerms': ['nvidia', 'amd'],
    'timeRange': 'today 3-m',
    'geo': 'US',
})

for item in client.dataset(run['defaultDatasetId']).iterate_items():
    print(item)

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💡 Common Use Cases

• SEO & Content Strategy: Identify rising/breakout topics before competitors catch on.
• Product & E-Commerce Validation: Compare seasonal demand curves across product categories.
• Financial & Market Intelligence: Track brand health, consumer sentiment spikes, and viral momentum.
• AI Agents & Automated Reports: Plug straight into Claude, Cursor, LangChain, or Zapier/Make automations.

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🛡️ Support & Feedback

If you need a custom integration, encounter an edge-case query, or have a feature request, please open an issue in the Issues tab or contact Phoebe Labs.