Google Trends Scraper — Interest, Related & Rising

Google Trends Scraper — Interest Over Time, Related & Rising Queries

Extract Google Trends data at scale — no API key, no login, no fragile Python libraries that break. This high-throughput Google Trends scraper extracts interest over time (the complete 0–100 historical timeline plus latest, average, and peak metrics), top and rising related search queries, regional geographic interest, and real-time trending-now daily searches with traffic estimates, news headlines, and direct publisher citations.

Whether analyzing single keywords or batch-auditing 1,000+ queries across countries and timeframes, everything exports cleanly into JSON, CSV, Excel, or programmatic API.

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⚡ At a glance

Feature	Specification
Target Website	Google Trends (trends.google.com)
Data Scope	Interest timeline, top queries, rising queries, regional breakdown, daily trending
Authentication	Keyless (no Google account or paid API key required)
Search Properties	Web Search, News Search, Image Search, YouTube Search, Google Shopping
Time Horizons	Past day (now 1-d), past 7 days, past month, past 3/12 months, past 5 years, all time (2004–present)
Geographic Scope	Global (worldwide) or any ISO-2 country (US, GB, DE, FR, TR) / sub-region (US-CA)
Concurrency & Scale	1 to 10 parallel workers with sticky IP sessions & automatic 429 backoff
Bulk Capacity	Fully unlocked for 1,000+ keywords per run with zero truncation
Export Formats	Dataset JSON, tabular CSV, spreadsheet Excel, XML, HTML, webhook integrations

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🔎 Why scrape Google Trends?

Google Trends represents the most comprehensive public pulse of global search demand, consumer sentiment, brand awareness, and breaking cultural shifts. Because Google captures over 90% of global search queries, Trends data provides an unparalleled leading indicator for commercial intent, investment themes, and viral trends.

However, extracting Google Trends programmatically comes with steep obstacles:

1. No official public API: Google does not offer a free or commercial public API for Trends.
2. Aggressive 429 rate limits: Unofficial scrapers and legacy Python packages (pytrends) frequently trigger HTTP 429 rate limits and broken cookie sessions.
3. Data normalization complexity: Interest values are dynamically indexed (0–100) relative to peak volume within the selected geography and timeframe.
4. Widget fragmentation: Timeline, related queries, and regional maps are split across separate internal API tokens.

This Google Trends data extractor completely eliminates these headaches. By bundling automated session bootstrapping, isolated proxy cookies, automatic JSON guard stripping, and multi-endpoint aggregation, it delivers structured, analytics-ready records for thousands of keywords reliably.

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⚖️ Feature comparison: Why choose this Actor?

Capability	Google Trends Web UI	Python pytrends	This Apify Actor
Bulk Keywords	Manual 5-term compare	Blocked after ~10 terms	1,000+ keywords automated
Anti-Bot Resilience	Interactive only	Frequent HTTP 429 fails	Sticky residential rotation
Daily Trending Searches	Manual copy-paste	Incomplete / fragile	Automated RSS & news links
Automated Export	Manual CSV download	Python code required	One-click JSON / CSV / Excel
Cloud Scheduling	Not supported	Requires custom server	Native Apify cron scheduler
Webhook Integrations	Not supported	Custom engineering	Direct to Zapier / Make / Slack
Maintenance	N/A	Abandoned / broke	Continuously maintained

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✨ Core capabilities

• 📈 Complete interest timeline: Retrieves the full indexed 0–100 search series for any keyword, calculating the latest value, arithmetic average, peak score, and peak date.
• 🔍 Top related queries: Uncovers the top 25 high-volume search queries frequently searched alongside your primary target.
• 🚀 Rising & breakout queries: Discovers explosive search terms with surging growth rates (including 5,000%+ "Breakout" surges) before competitors notice them.
• 🌍 Geographic & regional breakdown: Maps interest concentration across top countries, provinces, or states with normalized density metrics.
• 📰 Daily trending searches: Scrapes today's viral trending searches including approximate traffic counts, primary news headlines, news source names, and article links.
• 🎯 Multi-surface coverage: Switch effortlessly between Google Web Search, Google News, Google Images, YouTube Search, and Google Shopping (froogle).
• 🛡️ Anti-blocking architecture: Employs per-keyword sticky session cookies and residential IP rotation to prevent rate limiting even on large-scale research batches.
• 📦 Bulk 1,000+ keywords: Optimized queue architecture handles hundreds or thousands of seed keywords with steady throughput and zero dropouts.

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🎯 Use cases & industry applications

1. High-ROI SEO & content marketing

• Content calendar ideation: Uncover surging seasonal topics 4–8 weeks before search interest peaks.
• Breakout keyword discovery: Mine rising queries to write authoritative articles on emergent subtopics before keyword difficulty scores spike.
• Search intent mapping: Identify whether commercial terms perform better on Web Search versus YouTube or Google Shopping.

2. Market research & consumer intelligence

• Brand sentiment & share of search: Compare your company against direct competitors to measure brand salience over 12 months or 5 years.
• Product category validation: Test consumer demand for new product categories or startup concepts before investing engineering capital.
• Geographic expansion: Identify which cities, states, or overseas markets exhibit the highest organic interest for your service.

3. Financial analysis & quantitative trading

• Alternative data signals: Track search volume spikes for public ticker symbols, commodities, cryptocurrencies, or macroeconomic terms.
• Retail demand forecasting: Gauge holiday shopping interest for consumer discretionary brands ahead of quarterly earnings reports.

4. PR, journalism & newsroom monitoring

• Daily news agenda tracking: Automatically monitor Google's daily trending searches to identify breaking viral events and cultural moments.
• Source attribution: Capture the primary news outlets and articles currently ranking for surging stories.

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📥 Input parameters

The actor is designed to run instantly with zero configuration (using built-in popular market terms), while offering granular filters for deep market analysis.

Parameter	Type	Default	Description
keywords	array	["bitcoin", ...]	List of search terms or phrases (one per line). Supports single terms, multi-word queries, and product names.
geo	string	""	ISO-2 country code (US, GB, DE, CA, AU, TR) or sub-region (US-NY). Leave empty for worldwide data.
timeRange	select	"today 12-m"	Historical window: now 1-d (hourly), now 7-d, today 1-m, today 3-m, today 12-m, today 5-y, or all (2004–present).
category	integer	0	Google category ID (e.g., 7 Finance, 5 Computers & Tech, 71 Food & Drink, 20 Sports, 18 Shopping). 0 = all.
searchProperty	select	""	Search property: "" (Web), news (News), images (Images), youtube (YouTube), or froogle (Google Shopping).
includeRelatedQueries	boolean	true	When enabled, pulls top and rising queries for each seed term.
includeRegionalInterest	boolean	false	When enabled, fetches geographic interest distribution across provinces/countries.
includeTimeline	boolean	true	When enabled, serializes the complete date-value time series array as a clean JSON string.
trendingNow	boolean	false	When enabled, fetches daily trending search stories with estimated traffic and news headlines.
maxItems	integer	0	Maximum keywords or trending items to process. 0 = unlimited (processes all input keywords).
maxConcurrency	integer	4	Number of simultaneous keyword sessions (1–10). Recommended 3–5 for steady throughput.
proxyConfiguration	object	RESIDENTIAL	Apify proxy configuration. Residential proxies are enabled by default for maximum reliability.

Sample JSON configuration

{
  "keywords": [
    "artificial intelligence",
    "electric vehicles",
    "renewable energy",
    "quantum computing"
  ],
  "geo": "US",
  "timeRange": "today 12-m",
  "category": 0,
  "searchProperty": "",
  "includeRelatedQueries": true,
  "includeRegionalInterest": true,
  "includeTimeline": true,
  "trendingNow": false,
  "maxItems": 100,
  "maxConcurrency": 4,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"]
  }
}

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📊 Output data fields

Every record pushed to the Apify dataset represents either a comprehensive keyword evaluation or a daily trending search event. All fields use normalized string formats for seamless compatibility with BigQuery, Snowflake, PostgreSQL, and pandas.

🏷️ Keyword trend fields

Field	Coverage	Type	Description
type	🟢 High (100%)	String	Record classification ("keyword" or "trending").
keyword	🟢 High (100%)	String	The exact search term or entity queried.
geo	🟢 High (100%)	String	Geographic territory ("US", "GB", or "worldwide").
timeRange	🟢 High (100%)	String	The evaluated time window ("today 12-m", "all", etc.).
category	🟢 High (100%)	String	Numeric Google category ID ("0" for all).
searchProperty	🟢 High (100%)	String	Search surface queried ("web", "youtube", "news", etc.).
latestValue	🟢 High (98%)	String	The most recent search interest score (0–100).
averageValue	🟢 High (98%)	String	Arithmetic mean interest across the entire timeframe.
peakValue	🟢 High (98%)	String	Maximum relative search interest recorded (usually 100).
peakDate	🟢 High (98%)	String	Formatted date or week when the peak score occurred.
dataPoints	🟢 High (98%)	String	Total count of temporal data observations collected.
relatedTopQueries	🟢 High (95%)	String	Semicolon-separated list of top associated searches.
relatedRisingQueries	🟡 Conditional (75%)	String	Semicolon-separated list of fastest-growing breakout terms.
topRegions	🟡 Conditional (65%)	String	Top sub-regions formatted as GeoName:Score; GeoName:Score.
timeline	🟢 High (98%)	String	Full serialized JSON array of { "t": "Date", "v": Score }.
scrapedAt	🟢 High (100%)	String	ISO 8601 UTC execution timestamp.

📰 Daily trending search fields

Field	Coverage	Type	Description
type	🟢 High (100%)	String	Always "trending" for daily news spikes.
rank	🟢 High (100%)	String	Daily leaderboard position (1, 2, 3...).
keyword	🟢 High (100%)	String	Trending search topic name or celebrity/brand entity.
approxTraffic	🟢 High (95%)	String	Search volume threshold (e.g., "500K+", "100K+", "50K+").
relatedNews	🟢 High (95%)	String	Semicolon-delimited primary headline summaries.
newsSources	🟢 High (95%)	String	Names of reporting publishers (e.g., "The Wall Street Journal; Reuters").
newsUrls	🟢 High (95%)	String	Direct external URLs to ranking news articles.
publishedAt	🟢 High (100%)	String	RFC 822 publication timestamp from Google's trend feed.

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📋 Example JSON outputs

1. Keyword analysis record

{
  "type": "keyword",
  "keyword": "artificial intelligence",
  "geo": "US",
  "timeRange": "today 12-m",
  "category": "0",
  "searchProperty": "web",
  "latestValue": "87",
  "averageValue": "82",
  "peakValue": "100",
  "peakDate": "Feb 18, 2026",
  "dataPoints": "52",
  "relatedTopQueries": "ai; open ai; chat gpt; what is artificial intelligence; ai tools; ai image generator; bing ai",
  "relatedRisingQueries": "deepseek; chat gpt 5; claude 3.7; local llm benchmark; grok 3",
  "topRegions": "California:100; Washington:94; Massachusetts:91; New York:85; Texas:79",
  "timeline": "[{\"t\":\"Nov 12, 2025\",\"v\":74},{\"t\":\"Nov 19, 2025\",\"v\":78},{\"t\":\"Feb 18, 2026\",\"v\":100}]",
  "rank": "",
  "approxTraffic": "",
  "relatedNews": "",
  "newsSources": "",
  "newsUrls": "",
  "publishedAt": "",
  "error": "",
  "scrapedAt": "2026-11-10T14:15:22.184Z"
}

2. Daily trending record

{
  "type": "trending",
  "keyword": "Champions League Draw",
  "geo": "US",
  "timeRange": "now",
  "category": "",
  "searchProperty": "",
  "latestValue": "",
  "averageValue": "",
  "peakValue": "",
  "peakDate": "",
  "dataPoints": "",
  "relatedTopQueries": "",
  "relatedRisingQueries": "",
  "topRegions": "",
  "timeline": "",
  "rank": "1",
  "approxTraffic": "500K+",
  "relatedNews": "Champions League Quarterfinal Matchups Confirmed; Real Madrid Drawn Against Arsenal",
  "newsSources": "ESPN; UEFA Official; BBC Sport",
  "newsUrls": "https://www.espn.com/soccer/story/... | https://www.bbc.com/sport/football/...",
  "publishedAt": "Tue, 10 Nov 2026 12:00:00 GMT",
  "error": "",
  "scrapedAt": "2026-11-10T14:15:24.012Z"
}

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💻 Programmatic usage examples

Integrate Google Trends data directly into your Python scripts or Node.js applications using the official Apify Client SDKs.

Python integration

from apify_client import ApifyClient

# Initialize the ApifyClient with your API token
client = ApifyClient("YOUR_APIFY_TOKEN")

# Prepare actor input
run_input = {
    "keywords": ["openai", "anthropic", "mistral ai"],
    "geo": "US",
    "timeRange": "today 3-m",
    "includeRelatedQueries": True,
    "includeTimeline": True,
    "maxConcurrency": 3
}

# Run the actor and wait for it to finish
run = client.actor("haketa/google-trends-scraper").call(run_input=run_input)

# Fetch and print dataset results
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{item['keyword']} -> Latest: {item['latestValue']}, Peak: {item['peakValue']}")

Node.js integration

import { ApifyClient } from 'apify-client';

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

const input = {
    keywords: ['solana', 'ethereum', 'bitcoin'],
    geo: '',
    timeRange: 'today 12-m',
    includeRegionalInterest: true,
};

const run = await client.actor('haketa/google-trends-scraper').call(input);
const { items } = await client.dataset(run.defaultDatasetId).listItems();

console.log(`Retrieved ${items.length} Google Trends records:`);
items.forEach(item => {
    console.log(`- ${item.keyword}: Avg=${item.averageValue}, Rising: ${item.relatedRisingQueries}`);
});

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🚀 How to use this actor

1. Paste your keywords: In the Apify Console input form, enter one or more keywords into the Keywords field.
2. Select geographic territory: Choose worldwide (leave blank) or select target countries like US, GB, DE, or JP.
3. Choose timeframe & surface: Select your preferred historical range (today 12-m is recommended for annual trends) and search surface.
4. Configure optional enrichment: Enable Include related & rising queries for keyword research and Include regional interest for geographic expansion mapping.
5. Execute & monitor: Hit Start. The actor displays live status updates showing processed keyword counts and queue throughput.
6. Export dataset: Download your clean results immediately as CSV, Excel, or JSON, or stream directly via the Apify REST API.

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💡 Best practices & optimization tips

• Relative vs. absolute metrics: Remember that Google Trends reports relative index values (0–100) indexed to the peak volume within the selected query, region, and timeframe. A score of 100 represents the highest search interest point for that term, not an absolute search volume.
• Maintain residential proxy settings: Google aggressively rate-limits datacenter IP ranges on its exploration endpoints. Keep the default Apify residential proxy enabled for smooth execution across large keyword lists.
• Disambiguate broad nouns with categories: If your query could mean multiple distinct entities (e.g., "Apple" the company vs. apple the fruit), specify the appropriate Google Category ID to isolate commercial search data.
• Inspect rising vs. top queries: Top queries demonstrate steady, high-volume search baseline demand. Rising queries reflect sudden velocity shifts—ideal for trend-jacking and early content publication.
• Automate weekly/monthly monitoring: Set up an Apify schedule (e.g., every Monday at 08:00 UTC) to continuously track brand velocity and log historical trend shifts into your data warehouse.

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❓ Frequently Asked Questions (FAQ)

Do I need a Google Cloud account or API key?

No. This scraper functions completely keyless through Google's public endpoints. No credentials, billing setups, or OAuth authorizations are required.

How many keywords can I scrape in a single run?

There is no hard ceiling. The Actor easily handles batches from 1 to 1,000+ keywords. The built-in worker pool rotates sessions and throttles requests to ensure steady, uninterrupted processing.

Can I scrape YouTube or Google Shopping search interest?

Yes. Simply change the Search property dropdown to youtube or froogle (Google Shopping) to inspect vertical-specific search behavior.

Why do some low-volume terms lack rising queries?

If a search query has low baseline interest or steady historical volume with no sudden acceleration, Google's algorithm does not calculate rising queries. In such cases, top queries and interest timeline remain fully populated.

How do I integrate this Actor with Zapier, Make, or Google Sheets?

You can query the dataset via the Apify API (GET /v2/datasets/{datasetId}/items?format=csv) or configure an Apify Webhook to trigger an external HTTP workflow whenever a run finishes.

What happens if Google triggers a temporary 429 rate limit?

The Actor implements an intelligent exponential backoff and proxy session re-cycling engine. When a rate limit is detected, it automatically instantiates a new session with fresh cookie jars and resumes without losing previously scraped rows.

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🔗 Related scrapers & data tools

Complement your market research stack with these specialized Apify actors:

• Academic Paper & Author Resolver — Resolve DOI, PubMed, and ArXiv papers with full citation metrics.
• Substack Scraper — Extract newsletter posts, subscriber metrics, and author profiles.
• Article Content Extractor — Clean, ad-free article text and metadata extractor.
• Wikidata Entity Resolver — High-speed entity grounding and cross-database linking for AI agents.

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📋 Changelog

Version 1.2 (2026-11)

• Unlocked 1,000+ deep keyword processing: Removed batch size restrictions, enabling seamless execution across 1,000+ search terms with sticky proxy session persistence.
• Added explicit maxItems support: Added configurable item capping with automatic validation and zero-limit bypass.
• Accelerated prefill execution: Streamlined session bootstrapping to complete standard test runs in under 30 seconds.
• Enhanced data normalization: Improved URL delimiter consistency and standardized news source extraction on daily trending feeds.
• Schema & UX compliance: Verified 100% schema alignment with Apify CLI 2026 standards and added comprehensive dataset view components.

Version 1.1 (2026-10)

• Added daily trending RSS parser with news headline, publisher, and external article link extraction.
• Introduced per-keyword isolated cookie jars to prevent session cross-contamination and HTTP 429 errors.
• Enhanced regional geographic mapping with automatic score pairing.

Version 1.0 (2026-10)

• Initial release featuring interest over time, top & rising queries, and multi-surface support.