Google Trends Scraper

Scrape Google Trends data — the full Trending now list (hundreds of trends per country with search volume, growth %, categories and related searches), plus keyword interest over time, related queries (top and rising) and regional interest for up to 200 keywords per run. 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 now — Reads every trend Google Trends lists for a country or region in the past 4 hours, 24 hours, 48 hours or 7 days (the US often has 400+ a day). Each trend has its search volume ("200K+" and 200000), growth %, start and end time, active status, categories and the related searches Google groups under it. Filter by category (Sports, Politics, Technology …) or active trends only, and set how many you want. Pure HTTP, no browser, a few seconds per run. By default it returns the top 20 trends; raise maxItems for more. At the BRONZE tier, 20 trends cost about $0.025 and 100 trends about $0.105, including the run-start charge.
2. Keyword analysis — Extracts interest over time, related queries (top and rising), related topics when Google provides them, and regional interest. Compare 2–5 keywords on one shared 0–100 scale, or turn off comparison to analyze up to 200 keywords in one run, each on its own scale. Time ranges from the past hour to 2004–present, or exact custom dates. HTTP-first with a browser fallback.

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

Automated market research workflow on Apify

Use this actor as one source in a broader competitor-intelligence and market-research workflow:

1. Monitor ads and messaging with Google Ads Scraper, Google Ads Transparency Center Scraper, and LinkedIn Ad Library Scraper.
2. Track reviews and sentiment with G2 Reviews & Products Scraper, Trustpilot Reviews Scraper, and Amazon Reviews Scraper.
3. Watch demand and category trends with Google Trends Scraper, Google News Scraper, and TikTok Trends Scraper.
4. Benchmark ecommerce pricing and products with Amazon Scraper, Google Shopping Scraper, and Shopify Store Scraper.
5. Map companies to people with LinkedIn Company Employees Scraper when you need account or team context.

Schedule runs, export datasets to CSV/Excel/JSON, or connect the outputs to Google Sheets, webhooks, Make, Zapier, BI tools, and LLM reporting workflows.

📊 What data can you extract?

Trending searches

Field	Description
keyword	Trending search term
country	Country or region code (e.g., US, GB, US-CA)
traffic	Search volume label (e.g., "500K+")
searchVolume	Search volume as a number (e.g., 500000)
increasePercentage	Growth in percent (e.g., 1000 for +1,000%)
startedAt / endedAt	ISO start time; end time, or null while active
isActive	Whether the trend is still active
categories	Google Trends categories, e.g. ["Sports"]
relatedSearches	Queries Google groups under the trend ("Trend breakdown")
newsArticleCount	Number of news articles Google links to the trend
exploreUrl	Google Trends explore link
publishedAt	Start time as a date string (kept for older integrations)
picture, pictureSource	Trend image and credit ¹
newsTitle, newsUrl, newsSource, newsPicture	First news article ¹
news	All news articles ¹

¹ Google publishes article details only in its RSS feed, which covers about 10–20 top trends. Other trends have these fields set to null and news empty; newsArticleCount is filled for every trend.

Keyword analysis — Interest over time

Field	Description
keyword	The search keyword
date	ISO date of the data point
value	Search interest (0–100); shared across all keywords in a multi-keyword comparison
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 1–5 unique keywords. Two or more are compared in one Google-normalized request.
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",
    "trendingHours": "24",
    "trendingCategory": "17",
    "activeOnly": true,
    "maxItems": 100
}

trendingCategory 17 is Sports; 0 (default) is all categories.

Input example — Keyword analysis

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

Input example — Many keywords, each on its own scale

{
    "mode": "keyword",
    "keywords": ["running shoes", "trail shoes", "hiking boots", "sandals", "sneakers", "slippers", "flip flops"],
    "compareKeywords": false,
    "geo": "",
    "customTimeRange": "2024-01-01 2025-12-31"
}

📤 Output examples

Trending search result

{
    "type": "trending",
    "keyword": "pochettino",
    "country": "GB",
    "traffic": "50K+",
    "searchVolume": 50000,
    "increasePercentage": 1000,
    "publishedAt": "Mon, 09 Nov 2026 20:50:00 GMT",
    "startedAt": "2026-11-09T20:50:00.000Z",
    "endedAt": null,
    "isActive": true,
    "categories": ["Sports"],
    "relatedSearches": ["pochettino", "carrick", "mauricio pochettino", "next man utd manager odds"],
    "newsArticleCount": 24,
    "exploreUrl": "https://trends.google.com/trends/explore?q=pochettino&date=now%207-d&geo=GB&hl=en-US",
    "picture": null,
    "pictureSource": null,
    "newsTitle": null,
    "newsUrl": null,
    "newsSource": null,
    "newsPicture": null,
    "news": []
}

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 with tier discounts for Apify subscribers.

Event	FREE	BRONZE	SILVER	GOLD	PLATINUM	DIAMOND
Run started	$0.005	$0.005	$0.005	$0.005	$0.005	$0.005
Trending topic scraped	$0.00115	$0.001	$0.00078	$0.0006	$0.0004	$0.00036
Keyword analyzed	$0.138	$0.12	$0.0936	$0.072	$0.048	$0.0336

The run-start charge is taken together with the first delivered result, so a run with invalid input or no results costs nothing. Keywords for which Google has no data are not charged.

Cost formulas (BRONZE tier)

These are computed examples, not additional Actor charges. Apply the live BRONZE event rates shown above:

Task	Cost formula
Trending now (1 country, 20 trends)	run-start charge + (20 × trending-topic charge)
1 keyword analysis (all data)	run-start charge + (1 × keyword-analysis charge)
5 keywords compared in one run	run-start charge + (5 × keyword-analysis charge)
Daily trending monitoring (30 days)	30 × [run-start charge + (topics returned × trending-topic charge)]

Trending mode is lightweight — pure HTTP with no browser overhead, making it cost-efficient for regular monitoring.

Keyword mode uses 1024 MB (4× 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	Country code (e.g., US, GB, DE, JP, BR) or region (US-CA). Empty = worldwide (keyword mode only)
trendingHours	string	24	Trending window: 4, 24, 48 or 168 hours
trendingCategory	string	0	Trending category ID: 0 all, 1 Autos, 2 Beauty, 3 Business, 4 Entertainment, 5 Food, 6 Games, 7 Health, 8 Hobbies, 9 Jobs & Education, 10 Law & Government, 11 Other, 13 Pets, 14 Politics, 15 Science, 16 Shopping, 17 Sports, 18 Technology, 19 Travel, 20 Climate
activeOnly	boolean	false	Trending: skip trends that have ended
maxItems	integer	20	Trending: how many trends to return (one charge each)
keywords	string[]	—	Keywords to analyze (up to 5 when compared, up to 200 otherwise)
compareKeywords	boolean	true	true: one shared 0–100 scale for up to 5 keywords. false: each keyword analyzed on its own
timeRange	string	today 12-m	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 (2004–present)
customTimeRange	string	—	Exact dates YYYY-MM-DD YYYY-MM-DD (from 2004-01-01); overrides timeRange
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
• Compare 2–5 keywords together to preserve Google's shared normalization and 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

💻 API Usage

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?

At the BRONZE tier, a trending run returning 20 trends (the default) costs about $0.025, while one keyword analysis costs about $0.125; both estimates include the $0.005 run-start charge. Actual totals depend on the number of topics or keywords returned and your Apify pricing tier. Apify's Free plan includes monthly platform credits; check your current plan allowance and the Store Pricing tab before estimating how many runs the credits cover.

What's the difference between trending and keyword mode?

Trending mode reads Google's full "Trending now" list — every trend for the country and window, with volume, growth and categories. Fast, cheap, and great for content discovery. Keyword mode extracts deep analytics over HTTP, with a browser fallback: 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 typically completes in a few seconds. Keyword mode uses one HTTP-first request per comparison (or per keyword when comparison is off), with a browser fallback only when needed; runtime varies with Google and proxy conditions.

Can I compare multiple keywords?

Yes. Add 2–5 unique keywords to the keywords array. They are sent to Google together, so interest-over-time and regional values share Google's comparison-wide 0–100 normalization instead of each series being independently scaled to 100. Related results remain attributed to their source keyword. In flat mode, rows are tagged with keyword; grouped mode returns one object per keyword. Google compares at most five keywords at once. For more, set compareKeywords to false: up to 200 keywords per run, each scaled 0–100 on its own, like typing it alone into Google Trends.

What time ranges are available?

Nine options from real-time to historical: past hour, past 4 hours, past day, past 7 days, past month, past 3 months, past 12 months, past 5 years, and 2004–present (all). Or set exact dates with customTimeRange. 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 returns no data for very niche or misspelled keywords. Such keywords are listed in the run's status message and are not charged. If Google does not answer at all, the scraper retries with a browser and fails the run with a clear message instead of returning an empty success. Related topics are often empty because Google itself returns none for many keywords; related queries are not affected.

Error reporting

When a run fails, the Actor sends sanitized diagnostic input, the exception and the Actor, build and run IDs to our private GlitchTip service so we can repair it. Secret fields and URL query strings are removed, and reports are kept for 30 days.

Legality

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.

Google Trends data is aggregated and anonymized by Google; this Actor collects only what Google Trends shows publicly. This Actor is not affiliated with, endorsed by or sponsored by Google. Google and Google Trends are trademarks of Google LLC.

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 exports cumbersome and limits a directly comparable set to five keywords. Google Trends Scraper preserves that five-keyword comparison limit so values remain mathematically comparable. 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 2–5 keywords in one job and compare their value over the same period on Google's shared scale. A keyword with a rising trend line at 40 interest can be 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 the BRONZE tier, daily monitoring across 3 countries for a full year costs about $27.38 when each run returns ~20 topics ($0.005 start + 20 × $0.001 per country-run). Actual totals vary with topic counts and your Apify pricing tier.

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