Google Trends Scraper: Fast, No Browser

Get Google Trends data as clean rows: interest over time, by region, city and US metro area, related queries (top and rising), and trending searches by country. It talks to Google Trends directly, without a browser, so runs are quick and cheap, and it compares any number of terms on one scale, not just 5.

• Works with your existing input. Apify's Google Trends Scraper input (searchTerms, isMultiple, timeRange, geo, category, startUrls, spreadsheetId, customTimeRange, maxItems) runs unchanged, and results use the same field names.
• Doesn't give up when Google pushes back. Google limits how often one IP address can ask, so every attempt uses a new residential IP address and cookie, included in the price. A refused request is retried on another IP straight away. Failed searches are never charged.
• More than 5 terms on one chart. Turn on Put all search terms on one scale and 8, 50 or 500 terms come back comparable, with 100 as the highest point among all of them.
• A summary for every term: average, peak and when it happened, latest value, change over the period, and whether it is rising, falling or stable. No spreadsheet formulas needed.
• Every Google Trends filter: 9 time ranges or your own dates, 250 countries (and states or provinces through a URL), 1,132 categories, and web, image, news, YouTube or Google Shopping searches.
• Trending now: the searches trending in any country, with their approximate search volume and news articles.

What you can do with it

• Find out whether a product, a brand or a topic is growing or fading before you invest in it.
• Pick blog topics and keywords with rising queries, then track them every week (schedule the Actor).
• Compare 50 competitors or product names on one scale for a market report.
• Find the states, cities or metro areas where interest is highest for local ads.
• Feed a dashboard, a newsletter or an AI agent with what people are searching for today.

Quick start

1. Type your search terms, one per line.
2. Pick the country and time range.
3. Click Start. One row per term appears in the Output tab, with its summary; open a row for the full timeline, regions and related queries.

Input examples

A few terms, United States, past 5 years

{ "searchTerms": ["air fryer", "standing desk"], "geo": "US", "timeRange": "today 5-y" }

Compare terms on one chart, as on Google Trends (up to 5 per line)

{ "searchTerms": ["coffee, tea, matcha"], "isMultiple": true }

Any number of terms on one scale

{ "searchTerms": ["coffee", "tea", "matcha", "espresso", "latte", "chai", "cold brew", "hot chocolate"], "compareAllTerms": true, "geo": "US" }

A Google Trends URL, for example a state and YouTube searches

{ "startUrls": [{ "url": "https://trends.google.com/trends/explore?geo=US-CA&q=pizza&date=today%203-m&gprop=youtube" }] }

Your own dates and a category

{ "searchTerms": ["mortgage rates"], "geo": "GB", "customTimeRange": "2024-01-01 2026-06-30", "category": "7" }

Trending searches in three countries

{ "trendingSearchesCountries": ["US", "GB", "FR"] }

Output

One row per search term (or per comparison):

{
  "type": "searchTerm",
  "searchTerm": "bitcoin",
  "geo": "US",
  "timeRange": "today 12-m",
  "average": 34.9,
  "peak": 100,
  "peakTime": "Feb 1 – 7, 2026",
  "latest": 15,
  "latestTime": "Oct 11 – 17, 2026",
  "changePercent": -48.2,
  "trend": "falling",
  "interestOverTime_timelineData": [
    { "time": "1760832000", "formattedTime": "Oct 19 – 25, 2025", "formattedAxisTime": "Oct 19, 2025", "value": [32], "hasData": [true], "formattedValue": ["32"] }
  ],
  "interestOverTime_averages": [],
  "interestBySubregion": [
    { "geoCode": "US-WY", "geoName": "Wyoming", "value": [100], "formattedValue": ["100"], "maxValueIndex": 0, "hasData": [true] }
  ],
  "interestByCity": [ "… up to 200 cities" ],
  "interestByMetro": [],
  "interestBy": [],
  "relatedQueries_top": [
    { "query": "bitcoin price", "value": 100, "formattedValue": "100", "hasData": true, "link": "/trends/explore?q=bitcoin+price&date=today+12-m&geo=US" }
  ],
  "relatedQueries_rising": [
    { "query": "spcx stock", "value": 14500, "formattedValue": "Breakout", "link": "/trends/explore?q=spcx+stock&date=today+12-m&geo=US" }
  ],
  "relatedTopics_top": [],
  "relatedTopics_rising": [],
  "trendsUrl": "https://trends.google.com/trends/explore?q=bitcoin&geo=US&date=today+12-m&hl=en-US",
  "scrapedAt": "2026-10-23T16:04:58.112Z"
}

• Values are relative, as on Google Trends: 100 is the highest point of the chart, 50 is half as many searches. They are not search counts.
• interestBy is filled for worldwide searches (by country), interestBySubregion inside a country (states, regions), interestByCity everywhere Google has city data, interestByMetro for the United States when you ask for it.
• In a comparison, each term has its own summary in termSummaries, Google's interestOverTime_averages has one average per term, and every related query says which term it belongs to.
• With Put all search terms on one scale, each term gets its own row and "scale": "shared".
• A search that fails gets a row with an error and is not charged.

Trending searches come as rows with "type": "trendingSearch": country, rank, title, approxTraffic (such as "2,000+"), approxTrafficNumber, startedAt, picture and news (title, URL, source).

Coming from Apify's Google Trends Scraper?

Paste your input as it is. The field names of the results are the same, with a summary, the place, the time range, the search type and a link to the chart added to each row. Browser settings such as skipDebugScreen and pageLoadTimeoutSecs are accepted and have no effect, since there is no browser.

How "one scale" works

Google compares at most 5 terms at a time, and scales each comparison so its own highest point is 100. To compare more, the Actor puts terms in groups of 5, compares the most popular term of each group with the other groups' leaders, and rescales each group from there. Values are rounded to one decimal; a term hundreds of times smaller than the most popular one shows values close to 0, as it would on Google Trends itself.

Pricing

Pay per event: you pay for results delivered, nothing for failed searches.

Event	Price
Search term (each term, including each term of a comparison)	$2.50 per 1,000
Trending search (one row of trending searches)	$1.00 per 1,000

Residential proxies are included. Example: 200 terms with timeline, regions, cities and related queries = $0.50.

Good to know

• Related topics: in October 2026 Google returns them empty for most searches, on its own website too, so they are off by default. Related queries are not affected.
• Speed: 10 terms are fetched at a time, each through its own IP address. Google sometimes refuses a request; it is retried on another IP, so a few terms take longer than others.
• Small terms: when too few people search for a term, Google reports no data (hasData: false) and the summary is empty.
• States and provinces: use a Google Trends URL with the place in it, such as geo=US-CA or geo=FR-J.
• Fresh data: the past hour, 4 hours and day are close to real time; weekly points in the past 12 months include the current, partial week, which the summary leaves out.

FAQ

Is this the same data as on trends.google.com? Yes. The Actor asks Google Trends for the same data its website shows, in the same format.

Can it compare more than 5 terms? Yes, turn on Put all search terms on one scale.

Can I run it every week? Yes: save your input as a task and add a schedule in Apify Console.

Is it legal to scrape Google Trends? The Actor collects public, aggregated search interest data. Respect Google's terms of service for how you use and publish it.

Support

Something not working as expected? Open an issue on the Issues tab with your input. Made by WebThreenity.