Google Trends Scraper

Scrape Google Trends data — trending searches, interest over time, related queries, and regional interest. Two modes in one actor, flat CSV-ready output, pay per result.

🔍 What does Google Trends Scraper do?

Google Trends Scraper extracts search trend data from Google Trends in two modes:

1. Trending searches — Fetches today's hot trending topics from the Google Trends RSS feed. Pure HTTP, no browser, finishes in ~4 seconds for ~$0.003.
2. Keyword analysis — Navigates to Google Trends explore page with a real browser, intercepting API responses to extract interest over time, related queries, related topics, and regional interest breakdowns.

All results export as JSON, CSV, or Excel. The default flat output produces one row per data point — ideal for spreadsheets, dashboards, and data pipelines.

Who is it for?

• 🔍 SEO specialists — identifying trending keywords and seasonal search patterns
• 📊 Market researchers — analyzing consumer interest trends across regions and time periods
• 📝 Content marketers — planning content calendars around rising search topics
• 🏢 Product managers — validating product ideas based on search demand trends
• 📈 Business analysts — tracking brand awareness and category interest over time

📊 What data can you extract?

Trending searches

Field	Description
keyword	Trending search term
country	Country code (e.g., US, GB, DE)
traffic	Approximate search traffic (e.g., "500K+")
publishedAt	When the trend was published
picture	Trend image URL
pictureSource	Image source attribution
newsTitle	Related news article title
newsUrl	Related news article URL
newsSource	News publisher name
newsPicture	News article image URL

Keyword analysis — Interest over time

Field	Description
keyword	The search keyword
date	ISO date of the data point
value	Search interest (0–100 scale)
formattedDate	Human-readable date
isPartial	Whether the data point is incomplete

Keyword analysis — Related queries

Field	Description
keyword	The search keyword
query	Related search query
value	Relevance score
relatedType	top or rising
formattedValue	Display value (e.g., "100", "Breakout")
link	Google Trends link for the related query

Keyword analysis — Regional interest

Field	Description
keyword	The search keyword
region	Region name (e.g., US state)
value	Search interest score
maxValue	Maximum value index

💡 Why scrape Google Trends?

• Market research — Track product or brand interest over time and across regions to inform business decisions
• Content strategy — Discover trending topics and rising queries to create timely, high-traffic content
• SEO keyword research — Find related queries and breakout terms to target in your content and ad campaigns
• Competitive analysis — Compare search interest between your brand and competitors across countries and time periods
• Academic research — Study public interest patterns, seasonal trends, and cultural phenomena at scale
• Investment signals — Monitor search interest for companies, products, or sectors as a leading indicator

🚀 How to scrape Google Trends

1. Go to the Google Trends Scraper page on Apify Store.
2. Click Try for free to open the actor configuration.
3. Select a mode: "Trending searches" for today's hot topics, or "Keyword analysis" for deep keyword data.
4. Set the country (ISO code like US, GB, DE, JP).
5. For keyword mode, enter one or more keywords to analyze.
6. Optionally configure time range, category, and search property (Web, YouTube, News, etc.).
7. Click Start and wait for your data.
8. Download results as JSON, CSV, or Excel, or connect via the Apify API.

Input example — Trending searches

{
    "mode": "trending",
    "geo": "US"
}

Input example — Keyword analysis

{
    "mode": "keyword",
    "keywords": ["python", "javascript", "rust"],
    "geo": "US",
    "timeRange": "today 12-m",
    "outputType": "flat"
}

📤 Output examples

Trending search result

{
    "type": "trending",
    "keyword": "iPhone 17",
    "country": "US",
    "traffic": "500K+",
    "publishedAt": "Wed, 19 Mar 2026 12:00:00 +0000",
    "picture": "https://t3.gstatic.com/images?q=tbn:example",
    "pictureSource": "Apple",
    "newsTitle": "Apple Announces iPhone 17 with Revolutionary Design",
    "newsUrl": "https://www.cnn.com/2026/03/19/tech/iphone-17",
    "newsSource": "CNN",
    "newsPicture": "https://media.cnn.com/example.jpg"
}

Interest over time result

{
    "type": "interestOverTime",
    "keyword": "python",
    "date": "2025-03-23T00:00:00.000Z",
    "value": 87,
    "formattedDate": "Mar 23 – 29, 2025",
    "isPartial": false
}

Related query result

{
    "type": "relatedQuery",
    "keyword": "python",
    "query": "python ai",
    "value": 100,
    "relatedType": "rising",
    "formattedValue": "Breakout",
    "link": "/trends/explore?q=python+ai"
}

Regional interest result

{
    "type": "regionalInterest",
    "keyword": "python",
    "region": "Washington",
    "value": 100,
    "maxValue": 0
}

💰 Pricing

This actor uses pay-per-event pricing — significantly cheaper than alternatives:

Event	Price	Description
Run started	$0.005	One-time charge per run
Trending search scraped	$0.0001	Per trending topic extracted
Keyword analyzed	$0.05	Per keyword (includes all data types)

Cost estimates

Task	Estimated cost
Trending searches (1 country, ~20 topics)	~$0.007
1 keyword analysis (all data)	~$0.055
10 keywords analyzed	~$0.505
Daily trending monitoring (30 days)	~$0.21

Trending mode is dirt cheap — pure HTTP with no browser overhead. At ~$0.003 per run including platform compute, it costs practically nothing to monitor daily trends.

Keyword mode uses 1024 MB (4x less than the leading competitor at 4096 MB), keeping platform compute costs low even with a real browser session.

⚙️ Input reference

Parameter	Type	Default	Description
mode	string	trending	trending for hot topics, keyword for deep analysis
geo	string	US	ISO country code (e.g., US, GB, DE, JP, BR)
keywords	string[]	—	Keywords to analyze (keyword mode only)
timeRange	string	today 12-m	Time range: now 1-H, now 4-H, now 1-d, now 7-d, today 1-m, today 3-m, today 12-m, today 5-y
category	integer	0	Google Trends category ID (0 = all)
property	string	""	Search property: "" (Web), images, news, froogle (Shopping), youtube
outputType	string	flat	flat (one row per data point — best for CSV) or grouped (one object per keyword — best for JSON)

💡 Tips for best results

• Start with trending mode to discover what's hot before running keyword analysis
• Use flat output (outputType: flat) for CSV/Excel — each row is a single data point, ready for pivot tables and charts
• Use grouped output (outputType: grouped) for JSON APIs — one object per keyword with all data nested
• Combine multiple keywords in one run to save on the per-run start fee
• Time range matters — shorter ranges (past hour, past day) give minute-level granularity; longer ranges (12 months, 5 years) give weekly or monthly data points
• Filter by property — set property: "youtube" to see YouTube search trends instead of web search

🔗 Integrations

Connect Google Trends Scraper with your tools and workflows:

• Google Sheets — Export trend data directly to a spreadsheet for charting and monitoring
• Slack — Get notified when new trending topics appear in your market
• Zapier — Trigger workflows when trending data is available (e.g., auto-generate content briefs)
• Make — Build automated pipelines: track keyword trends, then feed data into dashboards or reports
• Webhooks — Send results to your own API endpoint
• Schedule — Run daily to build a historical trends database

💻 Programmatic access via API

Use the Apify API to run Google Trends Scraper from your code.

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")

# Trending searches
run = client.actor("automation-lab/google-trends-scraper").call(run_input={
    "mode": "trending",
    "geo": "US",
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{item['keyword']} — {item.get('traffic', 'N/A')}")

# Keyword analysis
run = client.actor("automation-lab/google-trends-scraper").call(run_input={
    "mode": "keyword",
    "keywords": ["python", "javascript"],
    "geo": "US",
    "timeRange": "today 12-m",
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"[{item['type']}] {item['keyword']}: {item.get('value', '')}")

Node.js

import { ApifyClient } from 'apify-client';

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

// Trending searches
const run = await client.actor('automation-lab/google-trends-scraper').call({
    mode: 'trending',
    geo: 'US',
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach(item => console.log(`${item.keyword} — ${item.traffic}`));

cURL

# Trending searches
curl -X POST "https://api.apify.com/v2/acts/automation-lab~google-trends-scraper/runs?token=YOUR_API_TOKEN&waitForFinish=120" \
  -H "Content-Type: application/json" \
  -d '{"mode": "trending", "geo": "US"}'

# Keyword analysis
curl -X POST "https://api.apify.com/v2/acts/automation-lab~google-trends-scraper/runs?token=YOUR_API_TOKEN&waitForFinish=120" \
  -H "Content-Type: application/json" \
  -d '{"mode": "keyword", "keywords": ["python"], "geo": "US", "timeRange": "today 12-m"}'

🤖 Use with AI agents via MCP

Google Trends Scraper is available as a tool for AI assistants that support the Model Context Protocol (MCP).

Setup for Claude Code

$claude mcp add --transport http apify "https://mcp.apify.com?tools=automation-lab/google-trends-scraper"

Setup for Claude Desktop, Cursor, or VS Code

Add this to your MCP config file:

{
    "mcpServers": {
        "apify": {
            "url": "https://mcp.apify.com?tools=automation-lab/google-trends-scraper"
        }
    }
}

Example prompts

Once connected, try asking your AI assistant:

• "What's trending on Google in the US today?"
• "Show me Google Trends interest over time for 'AI' vs 'machine learning' in the past year"
• "Find rising search queries related to 'remote work' on Google Trends"

Learn more in the Apify MCP documentation.

❓ FAQ

How much does it cost to scrape Google Trends?

Trending searches cost about $0.003 per run (pure HTTP, no browser). Keyword analysis costs ~$0.05 per keyword. Apify's free plan includes $5/month of platform credits, so you can monitor daily trends for free and analyze ~100 keywords per month.

What's the difference between trending and keyword mode?

Trending mode fetches today's hot topics from Google Trends RSS — fast, cheap, and great for content discovery. Keyword mode opens a real browser to extract deep analytics: interest over time (daily/weekly data points), related queries (top and rising), and regional interest by state/region.

How fast is the scraper?

Trending mode completes in ~4 seconds. Keyword mode takes ~38 seconds per keyword (browser startup + page load + API interception). Multiple keywords run sequentially within the same browser session.

Can I compare multiple keywords?

Yes. Add multiple keywords to the keywords array. Each keyword gets its own set of interest-over-time, related queries, and regional interest data. In flat mode, all data points are in the same dataset, tagged with the keyword field for easy filtering.

What time ranges are available?

Eight options from real-time to historical: past hour, past 4 hours, past day, past 7 days, past month, past 3 months, past 12 months, and past 5 years. Shorter ranges give finer granularity (minute-level), while longer ranges give weekly or monthly aggregation.

What countries are supported?

Any country that Google Trends supports. Use standard ISO country codes: US, GB, DE, FR, JP, BR, IN, AU, CA, and many more. Leave geo empty in keyword mode for worldwide data.

What data formats can I export?

You can download results as JSON, CSV, Excel, XML, or HTML table. The flat output mode is specifically designed for CSV/Excel — one row per data point, ready for pivot tables and charts.

Why did keyword analysis return empty results?

Google Trends may return no data for very niche keywords, misspelled terms, or overly broad time ranges. Google also rate-limits aggressive requests — the scraper retries up to 3 times with increasing delays to handle this.

Is it legal to scrape Google Trends?

This actor is provided for educational and research purposes. Users are responsible for ensuring their use complies with Google's Terms of Service and applicable laws. Always use scraped data responsibly.

How do I use Google Trends data for SEO keyword research?

Google Trends is one of the most underused SEO tools because its web interface makes it hard to export data at scale or compare more than five keywords at a time. With Google Trends Scraper you can:

• Find breakout queries: Pull relatedType: "rising" results for any seed keyword. "Breakout" queries (labeled with infinite growth) have recently exploded in search volume — publishing content targeting these terms before the competition catches on is a high-leverage SEO tactic.
• Validate keyword seasonality: Use interest-over-time data to understand whether a keyword peaks in December or March, so you can plan content publication to hit the seasonal wave.
• Compare keyword trajectories: Run multiple keywords in a single job and compare their value over the same time period. A keyword with a rising trend line at 40 interest is often a better target than one at 80 but declining.
• Regional targeting: Use regionalInterest data to identify which US states or countries show the highest interest for a keyword, then optimize your geo-targeted pages accordingly.

Export results in flat mode for easy pivot-table analysis in Google Sheets or Excel.

How do content marketers use Google Trends to plan their editorial calendar?

Content that rides a rising search trend can earn outsized traffic — but timing is everything. Google Trends Scraper supports two workflows for content calendar planning:

1. Daily trending monitor: Schedule a run in trending mode every morning. The RSS feed returns ~20 hot topics per country with associated news articles. Use this as a real-time signal for reactive content (news-jacking, trending commentary, timely tutorials).

2. Seasonal content planning: Run keyword analysis in 5-year mode (timeRange: "today 5-y") for your evergreen topics. The weekly interest data will clearly show annual peaks — "tax software" spikes every January, "Halloween costumes" in October, "gift ideas" in November. Use these peaks to schedule content publication 4–6 weeks before the top of the curve, giving Google time to index and rank your pages before demand peaks.

At ~$0.003 per trending run, a full year of daily monitoring across 3 countries costs under $3.30.

How do I compare Google Trends interest between two keywords?

To compare keywords directly (the way Google Trends' built-in comparison mode works), add both terms to the keywords array in a single run. Google Trends normalizes interest on a 0–100 scale relative to the highest point in the selected time period — so the comparison is already baked into the value field.

For example, running ["python", "javascript", "rust"] in 12-month mode returns separate interestOverTime rows for each keyword, all on the same normalized scale. Import the flat output into a spreadsheet, pivot by keyword, and chart the value column over date to produce a side-by-side comparison. The regionalInterest data also shows you which locations favor one keyword over another — useful for geo-targeted ad campaigns or deciding which language to prioritize in documentation.

What is the difference between "top" and "rising" related queries in Google Trends?

When you run keyword analysis mode, the scraper returns two types of related queries for each keyword, identified by the relatedType field:

• Top: The queries most frequently searched alongside your keyword over the selected time period. These are high-volume, established terms — useful for understanding the full search context around a topic and finding head terms you may have missed.
• Rising: Queries whose search frequency has grown the most relative to the previous period. A formattedValue of "Breakout" means the query grew by more than 5,000% — these are emerging terms with very low existing competition. Targeting breakout queries early, before they become mainstream, is one of the highest-ROI moves in SEO.

Use rising queries to fuel your content pipeline. Use top queries to validate that your core keyword strategy aligns with how real users search.

How do I track brand awareness trends over time using Google Trends?

Tracking search interest for your brand name (and competitor brands) over time is a lightweight brand health metric that correlates strongly with revenue and market share. With Google Trends Scraper:

1. Set mode: "keyword" and add your brand and up to 4 competitor brands to the keywords array.
2. Use timeRange: "today 5-y" for a long-term view or today 12-m for recent trends.
3. Schedule the run monthly and store results in Google Sheets to build a running historical dataset.
4. Add the regionalInterest data to identify which markets are showing the strongest growth for your brand vs. competitors.

You can also set property: "youtube" or property: "news" to measure brand awareness specifically on YouTube or in news coverage, rather than general web search.

🔗 Related scrapers

• Google Search Scraper — Scrape Google search results including organic results, People Also Ask, and related searches
• DuckDuckGo Scraper — Scrape DuckDuckGo web and news search results
• Google News Scraper — Extract news articles from Google News
• Google Maps Scraper — Scrape business listings from Google Maps
• Google Maps Reviews — Extract reviews from Google Maps businesses
• YouTube Scraper — Scrape YouTube video data and metadata