Google Trends Scraper: interest over time, by region, related queries

Get Google Trends data as JSON, CSV or Excel in seconds: interest over time, interest by region, and top and rising related queries, for up to 5 compared terms, any country, time range, category, or YouTube/Shopping/News search. No browser and no Google account. Each query takes about 3 seconds.

Built for SEO and content teams, e-commerce and product researchers, marketers, analysts and AI agents who need Trends data on a schedule or at scale, without copying charts by hand.

What you get

Panel	What it contains
Interest over time	Google's 0-100 interest index for every period (minutes, hours, days, weeks or months depending on the range), per keyword
Interest by region	Index per country, state/region, US metro area (DMA) or city, per keyword
Related queries	Top and rising related searches with their score or % growth, including "Breakout" flags
Related topics	Returned when Google provides them. Google currently returns this panel empty for most queries, so don't rely on it

Filters:

• Location: worldwide, any country (US, DE) or region (US-CA)
• Time range: past hour up to 2004 to today, or a custom date range
• Category: any Google Trends category ID
• Google property: web, Image, News, Shopping or YouTube search

How to use it

1. Add search terms, one query per line. To compare terms on the same scale, put up to 5 on one line separated by commas: iphone, samsung galaxy, pixel.
2. Optionally set location, time range, property and category.
3. Click Start. Download results from the Output tab as JSON, CSV, Excel or HTML, or fetch them through the API.

Input example

{
    "searchTerms": ["taylor swift, beyonce", "air fryer"],
    "geo": "",
    "timeRange": "today 3-m",
    "searchProperty": "youtube",
    "dataTypes": ["interestOverTime", "interestByRegion", "relatedQueries"]
}

Output

One item per search term (default)

Each query returns one item with every panel nested inside. The field names match the popular apify/google-trends-scraper, so if you're switching, your integration keeps working. Real output, with lists shortened to 2 entries:

{
    "searchTerm": "taylor swift, beyonce",
    "keywords": ["taylor swift", "beyonce"],
    "geo": "",
    "timeRange": "today 3-m",
    "category": 0,
    "searchProperty": "youtube",
    "interestOverTime_timelineData": [
        { "time": "2026-07-24T00:00:00.000Z", "formattedTime": "Jul 24, 2026", "value": [20, 10], "hasData": [true, true], "isPartial": false },
        { "time": "2026-07-25T00:00:00.000Z", "formattedTime": "Jul 25, 2026", "value": [20, 10], "hasData": [true, true], "isPartial": false }
    ],
    "interestBy": [
        { "geoCode": "PH", "geoName": "Philippines", "value": [90, 10], "hasData": [true, true] },
        { "geoCode": "GG", "geoName": "Guernsey", "value": [0, 0], "hasData": [false, false] }
    ],
    "relatedQueries_top": [
        { "keyword": "taylor swift", "query": "patient zero", "value": 100, "formattedValue": "100", "link": "https://trends.google.com/trends/explore?q=patient+zero&date=today+3-m" }
    ],
    "relatedQueries_rising": [
        { "keyword": "taylor swift", "query": "patient zero", "value": 774800, "formattedValue": "Breakout", "link": "https://trends.google.com/trends/explore?q=patient+zero&date=today+3-m" }
    ],
    "relatedTopics_top": [],
    "relatedTopics_rising": [],
    "sourceUrl": "https://trends.google.com/trends/explore?date=today+3-m&q=taylor+swift%2Cbeyonce&hl=en-US&gprop=youtube",
    "scrapedAt": "2026-10-24T21:10:00.700Z"
}

In comparisons, value[0] belongs to the first keyword, value[1] to the second, and so on.

Rows (one per data point)

Set Output format to Rows to get a flat table that drops straight into Excel, Google Sheets, SQL or a BI tool. Each row has a dataType column, and the Output tab has a separate view for each panel.

{ "dataType": "interestOverTime", "query": "coffee", "keyword": "coffee", "date": "2025-10-19T00:00:00.000Z", "dateLabel": "Oct 19 – 25, 2025", "value": 65, "hasData": true, "isPartial": false, "geo": "US", "timeRange": "today 12-m", "category": 0, "searchProperty": "web", "sourceUrl": "https://trends.google.com/trends/explore?date=today+12-m&q=coffee&hl=en-US&geo=US", "scrapedAt": "2026-10-24T21:09:46.956Z" }
{ "dataType": "interestByRegion", "query": "coffee", "keyword": "coffee", "geoCode": "US-WY", "geoName": "Wyoming", "value": 100, "hasData": true, "geo": "US", "timeRange": "today 12-m", "category": 0, "searchProperty": "web", "sourceUrl": "https://trends.google.com/trends/explore?date=today+12-m&q=coffee&hl=en-US&geo=US", "scrapedAt": "2026-10-24T21:09:46.956Z" }
{ "dataType": "relatedQueries", "query": "coffee", "keyword": "coffee", "rankType": "top", "rank": 1, "relatedQuery": "coffee near me", "value": 100, "formattedValue": "100", "isBreakout": false, "link": "https://trends.google.com/trends/explore?q=coffee+near+me&date=today+12-m&geo=US", "geo": "US", "timeRange": "today 12-m", "category": 0, "searchProperty": "web", "sourceUrl": "https://trends.google.com/trends/explore?date=today+12-m&q=coffee&hl=en-US&geo=US", "scrapedAt": "2026-10-24T21:09:46.956Z" }

A single 12-month query usually produces 100-700 rows.

Pricing

You pay per search query: one line of input, with up to 5 compared terms and every panel you selected.

Apify plan	Price per query	1,000 queries
Free	$0.002	$2.00
Starter (Bronze)	$0.0008	$0.80
Scale and above	$0.0005	$0.50

• Rows format: each stored row costs an extra $0.015 per 1,000 rows (about $0.006 for a typical 12-month query). The default nested format stores one item per query, so it adds almost nothing.
• No charge for queries that fail or that Google has no data for.
• No start fee beyond Apify's standard $0.00005 per run.
• Platform usage (compute, proxy) is included.
• Set Max cost per run in the run options, and the scraper stops cleanly when it gets there.

Why use this instead of…

• Copying from trends.google.com: batch hundreds of keywords, schedule daily or weekly runs, and get clean numbers instead of screenshots.
• pytrends or your own script: no rate-limit fights, proxy management or broken scripts when Google changes something. A live test runs against Google every day, so breakages are caught early.
• Browser-based scrapers: this one calls Google's data endpoints directly, so it's faster, cheaper and less likely to fail on slow page loads.

Use with AI agents (MCP)

This Actor works as a tool through the Apify MCP server, so Claude, ChatGPT, Cursor and other MCP clients can call it directly. Every input field has a plain-English description the agent can read. A typical agent call:

{ "searchTerms": ["electric bike, e-scooter"], "geo": "US", "timeRange": "today 5-y", "dataTypes": ["interestOverTime"] }

The default nested output is compact (one item per query), so the results fit comfortably in an agent's context.

You can also call it from code with the Apify API or the apify-client package for JavaScript and Python.

FAQ

What do the numbers mean? Google Trends reports relative interest, not search volume. 100 is the peak in the selected time and place, 50 is half that, and 0 means not enough data. Values are only comparable within one query, so put terms on the same line (comma-separated) to compare them.

Why are values in different queries on different scales? Google normalizes each query on its own. Compare terms on one line.

What does "Breakout" mean? In rising queries, the query grew by more than 5,000%. value holds Google's raw growth figure and isBreakout is true.

Why are related topics empty? Google currently returns the related topics panel empty through its data endpoint for most queries. If Google starts returning them again, they'll show up automatically.

How do I find a category ID? Open trends.google.com, pick a category, and copy the number after cat= in the URL.

Is scraping Google Trends allowed? This Actor collects publicly available, aggregated, anonymized data that anyone can view on trends.google.com. It doesn't log in or collect personal data. You're responsible for using the data in line with applicable laws and Google's terms.

Does the Actor send anything back to the developer? At the end of each run it sends us a small usage record: how many of each billable event the run was charged, the prices it was charged at, your pricing tier, whether your plan is paid, and a one-way hash of your user ID. That's how we see which Actors are worth maintaining, because Apify doesn't share this with developers. Your input, your results and your account details are never sent.

Something broke or looks wrong? Open an issue on the Issues tab. Issues get a response within 48 hours.