Google Trends Scraper – Fast, Reliable API Alternative

Get Google Trends data without failed runs: interest over time, interest by region, city and metro area, related queries and related topics (top and rising), plus today's Trending now searches with search volume. No browser, no login, no API key.

Already using the official Google Trends Scraper? This Actor accepts the same input fields and returns the same output fields (interestOverTime_timelineData, interestBySubregion, relatedQueries_top…). In most cases you only change the Actor ID in your code or integration.

Why this one

	This Actor	Typical browser-based scraper
How it works	Google Trends' own data endpoints	Opens Google Trends in a headless browser
Time per search term	~5–25 s	60–180 s
Refused requests	Retried automatically with a new IP address and cookie	Run often fails or loops
Never hangs	Every search has a time limit; partial data is kept and labelled	Can run until timeout
Compared terms	Related queries for each term	Often only one term
Long keyword lists on one scale	✅ Anchor term	❌
Trend metrics (growth, peak, direction)	✅	❌
Trending now with search volume	✅	❌
Price	$1.50 per 1,000 searches	$3+ per 1,000

Benchmark (20 Oct 2026, 5 keywords, US, past 12 months): this Actor returned complete data for 5/5 keywords in 100 s — time series, 51 states, cities, 210 metro areas and 50 related queries each. Other Google Trends Actors tested the same day returned partial data (time series only), ignored the keyword, or cost about $0.05 per keyword.

What you get

Keywords mode — one item per search term (or per group of up to 5 compared terms):

• interestOverTime_timelineData — the chart, point by point (weekly for 12 months, daily for 90 days, hourly for 7 days…)
• interestOverTime_averages — average per compared term
• interestBySubregion — by state / region (by country when Worldwide)
• interestByCity — by city (single term, inside a country; tick Include low search volume regions for many more cities)
• interestByMetro — by US metro area (DMA)
• relatedQueries_top, relatedQueries_rising — with "Breakout" and +% growth
• relatedTopics_top, relatedTopics_rising
• trendSummary — computed for you: average, peak and peak date, latest value, change in % (last quarter of the period vs first quarter), direction (rising / stable / falling), low-volume flag
• exploreUrl — open the same chart in Google Trends

Trending now mode — what people search today, per country:

• search term, search volume (e.g. 200,000+), increase %, start time, still trending or not
• related search terms, categories (Sports, Politics, Entertainment…), news articles for the top trends

Input examples

Simple:

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

Compare up to 5 terms on the same scale:

{ "searchTerms": ["tea,coffee,matcha"], "isMultiple": true, "geo": "GB", "timeRange": "today 3-m" }

Compare hundreds of terms on one scale with an anchor term:

{ "searchTerms": ["netflix", "hulu", "peacock", "paramount plus", "..."], "anchorTerm": "disney plus", "geo": "US" }

Each term is measured together with the anchor; trendSummary[].averageVsAnchor gives its popularity with the anchor = 100. Pick an anchor of similar popularity for the best precision.

Trending now:

{ "mode": "trending", "trendingGeos": ["US", "GB", "IN"], "trendingHours": "24", "trendingMinVolume": 10000 }

You can also paste Google Trends links (https://trends.google.com/trends/explore?q=bitcoin&geo=US&date=today%205-y) — their region, dates, category and search type (web, YouTube, news, images, shopping) are used.

Output example (classic format)

{
  "searchTerm": "coffee",
  "geo": "US",
  "timeRange": "today 12-m",
  "interestOverTime_timelineData": [
    { "time": "1760832000", "formattedTime": "Oct 19 – 25, 2025", "value": [64], "hasData": [true], "formattedValue": ["64"] }
  ],
  "interestBySubregion": [{ "geoCode": "US-WY", "geoName": "Wyoming", "value": [100] }],
  "relatedQueries_top": [{ "query": "coffee near me", "value": 100, "formattedValue": "100" }],
  "relatedQueries_rising": [{ "query": "how to brew pour over coffee", "value": 3300, "formattedValue": "+3,300%" }],
  "trendSummary": [{ "term": "coffee", "average": 76.2, "peak": 100, "peakDate": "2026-04-12", "latest": 66, "changePercent": 6, "direction": "stable" }],
  "exploreUrl": "https://trends.google.com/trends/explore?q=coffee&date=today+12-m&geo=US"
}

Prefer spreadsheets? Set Output format = Flat: one row per date and term, per related query and per region — ready for Excel, Google Sheets or a BI tool.

Use cases

• SEO and content: find rising queries and seasonal peaks before writing.
• E-commerce and product research: compare products, brands and categories over 5 years.
• Market research and investing: track interest in companies, assets and topics.
• Newsrooms and social media: monitor what is trending now in each country.
• AI agents and dashboards: schedule daily runs and feed the JSON into your pipeline.

Pricing

• $1.50 per 1,000 searches (one search = one term or one group of compared terms, with all its data). Searches with no data are not charged.
• $0.50 per 1,000 trending searches in Trending now mode.

Cheaper on paid Apify plans.

Good to know

• Values are Google's relative interest index (0–100), exactly as shown on Google Trends — not absolute search counts. Trending now gives Google's approximate search volume.
• Google sometimes shows unusual "rising" queries; they are returned as Google publishes them.
• Very rare terms get a low-volume warning: Google then shows data on only a few dates.
• Google Sheets import (spreadsheetId) is not supported; the field is accepted and ignored with a warning.
• Only public Google Trends data is collected.

Related scrapers

Other ready-to-use Actors by RT Solutions:

• Google News Scraper
• Google Ads Transparency Scraper
• App Store Reviews Scraper with AI