Google Trends Scraper API

Reliable Google Trends data in one normalized dataset — every surface Google Trends exposes:

• Interest over time — search-interest values (0–100) per keyword, over your chosen timeframe and geo.
• Related & rising queries — the top and breakout queries associated with each keyword.
• Related topics — the top and rising topics (entities) associated with each keyword.
• Interest by region — which countries / regions / cities / metros search most for each keyword.
• Trending now — the currently trending searches for a country, with approximate traffic and related news.

Built for reliability. Google Trends has no official public API and aggressively rate-limits its internal endpoints — which is why many scrapers fail intermittently. This actor routes through residential proxy, bootstraps Google's consent cookie before every session, and retries with exponential backoff, so runs complete instead of silently returning nothing.

Why this one

• One normalized schema for all three data types (discriminated by a dataType field) — load it straight into a spreadsheet or pipeline.
• Residential-proxy routed + retry-hardened against the 429 rate limits that break naive scrapers.
• No login, no personal data — public aggregate trend data only.

Input

Field	Description
searchTerms	Up to 5 keywords (Google compares max 5). Required for all data types except trending_now.
dataTypes	Any of interest_over_time, related_queries, related_topics, interest_by_region, trending_now.
regionResolution	For interest_by_region: COUNTRY, REGION, CITY, or DMA.
geo	Two-letter country code (e.g. US, GB, FI); empty = worldwide.
timeframe	e.g. today 12-m, today 5-y, now 7-d, or YYYY-MM-DD YYYY-MM-DD.
category	Google Trends category ID (0 = all).
language	Interface language, e.g. en-US, fi-FI.
trendingGeo	Country for the trending-now feed.
proxyConfiguration	Proxy routing. Residential Apify Proxy is strongly recommended — Google rate-limits datacenter IPs hard.

How to find IDs

• Timeframe and category mirror the options on trends.google.com.
• Geo is the standard ISO two-letter country code.

Example output

Interest over time:

{
  "dataType": "interest_over_time",
  "keyword": "bitcoin",
  "geo": "US",
  "timeframe": "today 12-m",
  "date": "Jul 8 2026",
  "value": 72,
  "isPartial": false
}

Trending now:

{
  "dataType": "trending_now",
  "geo": "US",
  "rank": 1,
  "query": "example topic",
  "approxTraffic": "50000+",
  "relatedNews": ["Headline one", "Headline two"]
}

Reliability by data type

Google defends its Trends endpoints unevenly, so this actor is honest about it:

• Interest over time and Trending now are reliable — these are the default, and they complete consistently (interest-over-time via residential-IP rotation, trending via Google's stable RSS feed).
• Related queries, related topics, and interest by region are best-effort. They use Google's most heavily rate-limited endpoints; the actor rotates through a pool of residential IPs and retries, but under load Google may still block them, in which case that data type returns nothing (the run still succeeds and you're only charged for rows delivered). For best results, request these one at a time.

Notes & limits

• Residential proxy is important. Google rate-limits these endpoints heavily on datacenter/unproxied IPs; the actor routes through a pool of residential IPs and rotates to a fresh IP on every retry, which is what keeps the reliable data types completing.
• trending_now uses Google's trending RSS feed — the most stable Trends surface — and needs no keywords.
• Google Trends values are relative (0–100, scaled to the peak within your query), not absolute search counts — this is how Google Trends works, not a limitation of the scraper.

Common uses

• Track demand/seasonality for products, tickers, or topics.
• Find breakout ("rising") queries for content and SEO.
• Monitor what's trending in a country for newsroom/marketing workflows.