Google Trends Scraper — Interest Over Time, Related Queries & Trending Now

Extract Google Trends data for any keyword: interest over time, interest by region, related queries, related topics, and real-time trending searches. Built API-first (no slow browser automation), so runs finish in seconds and cost less.

What data does it extract?

Data type	What you get
Interest over time	0–100 search-interest index per date for your timeframe
Interest by region	Interest by country, state/region, city, or US metro area
Related queries	Top & rising queries with values and growth ("Breakout")
Related topics	Top & rising topics with type (e.g. Cryptocurrency, Company)
Trending now	Current trending searches with approximate traffic, start time, and related queries — 300+ entries per region

Any timeframe Google Trends supports: now 1-H … today 5-y, all, or explicit date ranges. Any country or region. Category filtering supported.

Why this scraper?

• ⚡ API-first, not browser-based — most Google Trends actors drive a headless Chrome through the Trends UI; this one talks to Trends data endpoints directly. Faster runs, lower compute, fewer flaky failures.
• 📊 All five datasets in one actor — no need for separate actors for trending searches.
• 💰 $1.50 per 1,000 rows — pay only for delivered results.
• 🔁 Automatic session rotation — rate limits are handled with retries, backoff, and fresh sessions.

Pricing

Event	Price	When charged
Actor start	$0.02	Once per run
Data row	$0.0015	Per result row ($1.50 / 1,000)

Example: 12 months of weekly interest + 51 US states + related queries & topics for one keyword ≈ 230 rows ≈ $0.37.

Input

{
    "queries": ["bitcoin", "ethereum"],
    "dataTypes": ["interestOverTime", "interestByRegion", "relatedQueries", "relatedTopics"],
    "timeframe": "today 12-m",
    "geo": "US",
    "regionResolution": "REGION",
    "includeTrendingNow": true,
    "trendingHours": 24
}

Leave queries empty and enable includeTrendingNow to get only trending searches.

Output examples

{ "type": "interestOverTime", "keyword": "bitcoin", "geo": "US", "date": "2026-04-17T00:00:00.000Z", "value": 86, "isPartial": false }
{ "type": "interestByRegion", "keyword": "bitcoin", "geoCode": "US-WY", "geoName": "Wyoming", "value": 100 }
{ "type": "relatedQueries", "keyword": "bitcoin", "rankType": "RISING", "query": "bitcoin etf", "formattedValue": "+250%" }
{ "type": "trendingNow", "geo": "US", "keyword": "taylor farms", "approxTraffic": 200000, "startedAt": "2026-07-16T21:20:00.000Z", "relatedQueries": ["taylor farms lettuce"] }

Download as JSON, CSV, Excel, or fetch via API.

Use from code or AI agents

• API / SDKs: run and fetch results with the Apify API.
• MCP: works out of the box with the Apify MCP server — Claude, Cursor, and other AI agents can call it as a tool.
• Scheduling: run it daily/hourly with Apify Schedules for keyword monitoring.

Common use cases

• SEO & content planning — find rising queries before they peak
• Market research — compare brand interest across regions and time
• Trend monitoring — feed trending-now data into news/content pipelines
• Trading signals — track search interest for tickers and products
• Ad timing — schedule campaigns around seasonal interest curves

Notes & troubleshooting

• Values are Google's relative 0–100 index per query context, not absolute volumes.
• Residential proxy (the default) is strongly recommended; Google rate-limits datacenter IPs.
• A query returning no rows usually means Google has no data for that keyword/region/timeframe combination.
• Issues or feature requests (multi-keyword comparison, categories list, hourly granularity)? Open an issue in the Issues tab — answered within 24 hours.