Google Trends Scraper

Reliable Google Trends data — interest over time, interest by region, and rising related queries — for any keywords, any country, up to 5 years back. No API key.

Google aggressively rate-limits Trends (HTTP 429), and most scrapers built on top of it just fall over. Their issue trackers say it out loud: "Runs with infinite loop and no result", "Too much time and no output", "It never worked." You start a run, wait, pay for compute, and get an empty dataset with no explanation. The official Apify Google Trends actor sits at 3.1 stars for exactly this reason.

This scraper is built around that failure mode instead of ignoring it. The full API dance — cookies, explore, widget data — rides a single sticky residential-proxy session. The moment Google returns a 429, the session is thrown away and the batch restarts on a fresh IP, with bounded retries and backoff. The run either delivers real data or fails fast and loud with a clear message. It never hangs, and it never quietly charges you for an empty result.

You give it	You get back
Keywords (up to 5 on a shared 0–100 scale)	Interest-over-time timeline per keyword
A country or region (or worldwide)	Interest-by-region breakdown with geo codes
A time range (7 days → 5 years)	Top and rising related queries and topics
Toggles for each data type	Clean, long-format rows ready for CSV, Sheets, or an LLM

What does the Google Trends Scraper do?

It pulls the same numbers you see on trends.google.com — normalized 0–100 search interest — straight from Google Trends' own internal API, and returns them as flat dataset rows you can sort, filter, and export.

For each keyword you can collect four data types, each an opt-in toggle so you only pay for the rows you actually want:

• Interest over time — the search-interest timeline (0–100) for every keyword across your chosen window.
• Interest by region — how interest breaks down by country or subregion, with geo codes.
• Related queries — the top and rising searches people run alongside your keyword.
• Related topics — the top and rising topics associated with your keyword.

Up to 5 keywords are compared per batch on one shared 0–100 scale. Larger keyword lists are processed in additional batches automatically.

Who is it for?

Audience	What they pull
SEO specialists	Rising related queries to target topics before they get competitive
Content marketers	Interest-over-time curves to time articles, videos, and campaigns
Product teams	Demand trajectory for a niche before committing to build it
Market researchers	Interest-by-region maps to size and compare geographic demand
AI / trend pipelines	Clean typed rows feeding dashboards, alerts, and LLM analysis

Why use this scraper?

• Reliability over empty datasets. Sticky sessions and residential proxies beat the 429 wall that makes other Trends scrapers hang or return nothing.
• Rising related queries = the best early-trend signal Google gives away. Every rising query comes flagged with its growth percentage.
• Up to 5 keywords on a shared 0–100 scale. Directly comparable numbers, so you can rank demand head-to-head.
• Any country or region. Worldwide, a single country (US, GB, DE), or a subregion (US-CA).
• Up to 5 years of history. From the past 7 days to the past 5 years, in one toggle.
• No API key, no login, no quota. Just keywords in, rows out.

What data do you get?

Every row is long-format and carries a type field so you can split the dataset by data type. Here are real samples of each row.

Interest over time

{
  "type": "interestOverTime",
  "date": "Jul 22, 2026",
  "timestamp": 1753142400,
  "keyword": "ai agents",
  "value": 14,
  "isPartial": false
}

Interest by region

{
  "type": "interestByRegion",
  "region": "California",
  "geoCode": "US-CA",
  "keyword": "ai agents",
  "value": 100
}

Related queries (and relatedTopics, same shape)

{
  "type": "relatedQueries",
  "keyword": "ai agents",
  "query": "ai agent frameworks",
  "value": 3600,
  "isRising": true,
  "change": "+3,600%"
}

Rows where isRising is true come with a growth figure in change (for example +3,600% or Breakout). These rising queries are the single most valuable output for early-trend detection — they surface the searches gaining momentum right now, before they show up in any keyword tool.

How to scrape Google Trends data

1. Add your keywords (up to 5 share one comparable 0–100 scale).
2. Set a region — a country code like US, a subregion like US-CA, or leave it empty for worldwide.
3. Pick a time range from the past 7 days up to the past 5 years.
4. Toggle the data types you want: interest over time, interest by region, related queries, related topics.
5. Run the actor and export the dataset as JSON, CSV, or Excel, or read it from the Apify API.

No account or API key is required on Google's side — the scraper handles cookies, sessions, and proxy rotation for you.

How to find rising search trends

Enable Related queries (and optionally Related topics). In the output, filter for rows where isRising is true. The change field tells you how fast each query is climbing — a percentage jump or Breakout for surges too large to quantify.

Because rising queries reflect momentum rather than absolute volume, they are the earliest public signal that a topic is heating up. Pull them on a short time range (past 7 days or past month) to catch trends while they are still forming.

How much does it cost to scrape Google Trends

You pay only for Apify platform usage (compute + proxy) — there is no Google API fee, because there is no API key involved. Cost scales with how many rows you collect, which is why every data type is an opt-in toggle: enable only interest over time for a lean run, or turn on regions and related data when you need the full picture.

If a run collects zero rows because every batch was rate-limited, the actor stops with an error instead of silently returning an empty dataset, so you are not left paying for nothing.

How to track keyword interest over time

Keep Interest over time enabled and choose your window. Each row is one keyword at one point in time, with a normalized value from 0 to 100 and a date. Sort by keyword then timestamp to reconstruct the full curve, or pivot on date to compare several keywords side by side.

The most recent data point is marked isPartial: true because its period is still in progress — exclude those rows when you need only finalized values.

How to do SEO keyword research with Google Trends

1. Put your seed keywords (up to 5) in one batch so their interest values are directly comparable on the shared 0–100 scale.
2. Enable Related queries to harvest the searches Google associates with each seed — these are ready-made topic and long-tail ideas.
3. Filter rising queries to find low-competition topics you can publish on before the rest of the market catches up.
4. Add Interest by region to prioritize the countries or states where demand is strongest.

How to export Google Trends data to CSV or Google Sheets

After a run, open the dataset and export in one click as CSV, Excel, or JSON, or pull it programmatically from the Apify Dataset API. The dataset ships with three ready-made views — Interest over time, Related queries & topics, and Interest by region — so each data type lands in its own clean table. Because rows are long-format, they drop straight into Google Sheets, Looker Studio, or a pandas DataFrame without reshaping.

Google Trends API alternative

Google does not offer an official public Google Trends API. This actor is a drop-in alternative: it returns the same 0–100 normalized data the Trends website shows, as structured rows, over a simple input — no key, no OAuth, no daily quota. Call it on a schedule via the Apify API or MCP and treat it as the Trends endpoint Google never shipped.

Is it legal to scrape Google Trends?

This actor collects only publicly available Google Trends data — the same information any visitor can see on trends.google.com without logging in. It does not access private accounts or personal data. As always, review Google's terms and your own local regulations, and use the data responsibly. See the disclaimer below.

Input configuration

Field	Type	Default	Description
keywords	array (required)	["ai agents"]	Search terms to analyze. Up to 5 are compared on a shared 0–100 scale per batch; more are split into separate batches.
geo	string	"" (worldwide)	Country/region code like US, GB, DE, or a subregion like US-CA.
timeRange	string	today 12-m	Look-back window: now 7-d, today 1-m, today 3-m, today 12-m, or today 5-y.
category	integer	0	Google Trends category ID to narrow results (0 = all; e.g. 5 = Computers & Electronics).
includeTimeline	boolean	true	Interest-over-time values (0–100) per keyword.
includeRegions	boolean	false	Interest breakdown by country or subregion.
includeRelatedQueries	boolean	false	Top and rising queries related to each keyword.
includeRelatedTopics	boolean	false	Top and rising topics related to each keyword.

FAQ

Why is my run sometimes slower? When Google rate-limits an IP, the actor rotates to a fresh sticky session and retries (each attempt is logged). Delivering complete data in 60 seconds beats "finishing" in 5 seconds with an empty dataset — reliability is the whole point.

Do the values match trends.google.com? Yes. The actor uses the same internal API the website uses, with the same 0–100 normalization applied per batch. Numbers within a batch are directly comparable; numbers from different batches are each normalized independently.

Do I need an API key? No. No key, no login, and no quota — just provide keywords.

Why is the latest data point marked partial? Google flags the trailing period as incomplete because it is still in progress. Those rows carry isPartial: true so you can exclude them when you need only settled values.

Integrations

Connect the Actor to the tools you already use through Apify integrations:

• Trends → Google Sheets — auto-append interest-over-time and rising queries into a live trend dashboard.
• Trends → Slack / Discord — get alerted when a tracked keyword's rising queries spike.
• Trends → Make / Zapier — trigger content or SEO workflows off fresh trend data.
• Trends → BigQuery / Snowflake — warehouse trend series via Airbyte for forecasting and analysis.
• Scheduled runs & webhooks — run daily/weekly to build a keyword time series, or POST results on completion.

Use with AI agents via MCP

The actor exposes clean, typed rows that plug straight into LLM pipelines. Run it through Apify's MCP integration so an AI agent can pull live Google Trends data — interest curves, regional demand, and rising queries — as a tool call, then reason over the results or trigger alerts on emerging trends.

Related scrapers

• App Store Reviews Scraper — mine iOS app reviews for pain points and feature requests.
• Google Play Reviews Scraper — the same review intelligence for Android apps.
• YouTube Outlier Finder — surface breakout videos on small channels before they blow up.
• Telegram Channel Scraper — pull posts and signals from public Telegram channels.

Disclaimer

This actor is not affiliated with, endorsed by, or sponsored by Google. Google Trends is a trademark of Google LLC. The actor accesses only publicly available data and is intended for lawful use in compliance with Google's terms and applicable regulations.

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