Google Trends Scraper & API

Get Google Trends data for any number of search terms in one run: interest over time, interest by country, region, city or metro area, related queries, side-by-side comparisons, and Trending Now with search volumes. Rank more than 5 terms on one calibrated scale, and get daily points across multi-year ranges. Clean, typed JSON or flat rows, built for AI agents and data teams, from $1.50 per 1,000 results.

What you can do with it

• Track a keyword portfolio: "Get Google Trends interest for these 50 keywords in the US over the past 12 months."
• Rank many terms against each other: "Which of these 30 product names gets the most searches?" Calibrated comparison puts every term on one 0-100 scale with error bounds, beyond Google's 5-term limit.
• Compare across countries: "How does interest in electric cars compare in the US, UK and Germany?" One run, any number of locations.
• Find rising topics: "What related searches are breaking out around web scraping?" Rising queries are flagged with isBreakout.
• Watch what is trending: "What is trending in the UK in sports right now?" Hundreds of trends with search volume, growth and start time, not just the top 10.
• Monitor on a schedule: monitor mode returns only new trends or new rising queries since the last run.
• Feed an AI agent or dashboard: choose only the fields you need, or get one flat row per data point.

Why this actor

• Reliable and fast. Plain HTTP requests with automatic session rotation and proxy escalation; no browser, no hanging runs. A blocked data type is reported in missingDataTypes instead of failing the run.
• Every data type in one record per term, plus a computed summary: average, peak and date, latest value, change in percent and direction (rising, falling, stable).
• Calibrated comparison of any number of terms with low and high bounds, so you know how precise each value is.
• Daily points for long ranges. Google returns weekly or monthly points beyond about 9 months; turn on dailyResolution for one point per day across years.
• Standard Google Trends field names (interestOverTime_timelineData, interestBySubregion, relatedQueries_rising and so on), so existing pipelines keep working.
• Built for AI agents: typed inputs with defaults and examples, a declared output schema, fields selection, and a RUN_SUMMARY with the outcome of every lookup. Works through Apify's MCP server.

Modes

Mode	What you get	Billed per
explore (default)	One record per term (and per location): interest over time, by region, related queries, optional topic suggestions; with compare, an extra comparison record per group of up to 5 terms	Term record, comparison record
calibrated-comparison	One record per term with its rank, relativeInterest (largest term = 100), low and high bounds, and its time series on the shared scale	Calibrated term
trending	Trending Now for a country: term, search volume, growth percent, start and end time, active flag, categories, related searches	Trending item

Input

Field	Type	What it does
mode	explore, calibrated-comparison, trending	What to get (default explore)
searchTerms	array of strings	Terms to look up, any number
startUrls	array of Google Trends explore URLs	Terms, locations, period, category and search type read from each URL
compare	boolean	Compare terms on one scale in groups of up to 5, with a comparison record
geo	string	US, GB, US-CA, US-CA-807; empty = worldwide
geos	array of strings	Run every term for each location, e.g. ["US", "GB", "DE"]
timeRange	past-hour … all-time	Preset period (default past-12-months)
customTimeRange	string	"2024-01-01 2024-12-31" or hourly "2026-09-01T00 2026-09-03T12"
category	integer	Google Trends category id (0 = all)
property	web, images, news, youtube, shopping	Which Google search to measure
dataTypes	array	interestOverTime, interestByRegion, relatedQueries, relatedTopics, suggestions
regionResolution	auto, country, region, city, metro	Detail of the region breakdown
includeLowVolumeRegions	boolean	Include regions Google hides for low volume
dailyResolution	boolean	Daily points across ranges longer than about 9 months
trendingGeo, trendingHours, trendingCategories, trendingActiveOnly, trendingMaxItems		Trending Now: country, window (4, 24, 48 or 168 hours), categories, active only, how many
monitorMode, monitorName	boolean, string	Only new trends or new rising queries since the last run
outputFormat	nested, flat	One record per term, or one row per data point
fields	array of strings	Return only these fields (dotted paths allowed)
maxItems	integer	Stop after this many billed results
language, timezone	string, integer	Labels language (en-US) and offset in minutes for hourly data

Example input

{
  "searchTerms": ["web scraping", "data extraction"],
  "compare": true,
  "geos": ["US", "GB"],
  "timeRange": "past-12-months",
  "dataTypes": ["interestOverTime", "interestByRegion", "relatedQueries"]
}

Output

Term record (explore mode, shortened)

{
  "type": "term",
  "searchTerm": "web scraping",
  "geo": "US",
  "timeRange": "past-12-months",
  "summary": {
    "average": 67.8,
    "peak": 100,
    "peakDate": "2026-06-07T00:00:00.000Z",
    "latest": 24,
    "latestDate": "2026-09-27T00:00:00.000Z",
    "changePercent": -44,
    "direction": "falling"
  },
  "interestOverTime_timelineData": [
    {
      "date": "2026-09-27T00:00:00.000Z",
      "formattedTime": "Sep 27 – Oct 3, 2026",
      "value": [24],
      "hasData": [true],
      "isPartial": false
    }
  ],
  "interestOverTime_averages": [68],
  "interestBySubregion": [{ "geoCode": "US-MD", "geoName": "Maryland", "value": [100] }],
  "relatedQueries_top": [{ "query": "ai web scraping", "value": 100, "isBreakout": false }],
  "relatedQueries_rising": [
    {
      "query": "best noise cancelling headphones",
      "value": 12150,
      "formattedValue": "Breakout",
      "isBreakout": true
    }
  ],
  "missingDataTypes": [],
  "trendsUrl": "https://trends.google.com/trends/explore?q=web%20scraping&geo=US&date=today%2012-m"
}

Calibrated term

Each calibrated record also carries timeline: the term's series rescaled onto the shared scale.

{
  "type": "calibrated-term",
  "rank": 4,
  "searchTerm": "selenium",
  "relativeInterest": 0.2263,
  "low": 0.1683,
  "high": 0.2937,
  "belowRange": false,
  "bridge": "python",
  "comparedTerms": 12
}

Trending item

{
  "type": "trending",
  "rank": 1,
  "term": "bahrain grand prix",
  "geo": "GB",
  "searchVolume": 100000,
  "growthPercent": 300,
  "startedAt": "2026-10-04T06:40:00.000Z",
  "isActive": true,
  "categories": [{ "id": 17, "name": "Sports" }],
  "trendBreakdown": ["bahrain grand prix"]
}

Every run also writes RUN_SUMMARY to the key-value store: the outcome (COMPLETE, PARTIAL, NO_NEW_DATA, EMPTY or FAILED), counts, and the reason for any failed lookup.

Pricing

Pay only for results delivered. Blocked or failed lookups are never charged.

Result	Free and Bronze	Silver	Gold
Term record (all requested data types for one term and location)	$1.50	$1.30	$1.10
Comparison record	$1.50	$1.30	$1.10
Calibrated term	$10.00	$9.00	$8.00
Trending item	$1.00	$0.90	$0.80

Prices are per 1,000 results; your tier depends on your Apify plan. Each run also has a $0.00005 start fee.

Flat mode is billed per term record, not per row.

How calibrated comparison works

Google compares at most 5 terms at a time, each group on its own 0-100 scale rounded to whole numbers. The actor first sizes every term against one anchor, then chains groups from the most popular term down, each group sharing a "bridge" term with the previous one and holding only terms of similar size, so no value is lost to rounding. Bounds carry Google's rounding through the chain: a niche term 30,000 times smaller than the top one still comes back with a value and a range.

Limits

• Related topics are returned only when Google provides them to logged-out visitors, which is often not the case. When they are missing, the record says so in missingDataTypes.
• Google Trends values are relative (0-100), not absolute search counts. Trending Now volumes are Google's own approximate figures.
• Calibrated values are only as precise as their bounds; terms far apart in popularity have wider bounds.
• Memory: explore runs fit in 512 MB at any size tested (2,000 terms); calibrated comparisons of up to about 500 terms fit in 512 MB (5 years of daily points), larger ones need the default 4,096 MB.
• Nothing found: terms with no interest data, or input naming nothing to look up, are not a failure: the run still succeeds, with one free recordType: "unreadable" row giving the reason; nothing is charged. A run near its time limit stops starting lookups, delivers what it read and lists the rest in RUN_SUMMARY.

Changelog

• 0.1.x, reliability (2026-10-24): runs that find nothing (terms without data, input naming nothing to look up) end SUCCEEDED with a free unreadable row saying why, instead of FAILED; custom time ranges and Trends URLs are checked in the input form; a run stops starting lookups before its time limit, never TIMED-OUT. A run whose every lookup Google blocked still fails. Prices and events unchanged.
• 0.1 (October 2026): explore, comparison, multiple locations, calibrated comparison of any number of terms, daily points for long ranges, Trending Now, monitor mode, flat output and field selection.