Google Trends Scraper — Keywords, Related Searches and Category Rankings

Google Trends for any keyword, in any country or region and over any of Google's time ranges: how interest in it rose and fell, the top and rising searches related to it, and where it is searched most. Or, with no keyword at all, the top and rising searches of any of Google's 928 categories — what people search for in Shopping, in Autos & Vehicles, in Vehicle Brands — down to the third level of Google's category tree. An independent tool, not affiliated with Google.

📖 What it does

• 🔍 Keyword lookups: one row per keyword, place and time range, with Google's interest over time, the top and rising related searches (Breakout ones marked), and interest by region or city.
• 📊 Category rankings: the top and rising searches of a category, one row per search, for any of the 928 categories down to the third level, all categories together, or a category with all its subcategories.
• 🌍 Any place: a country (US), a region inside one (US-CA, GB-SCT, DE-BY), a US metro area (US-CA-807), or worldwide — as many as you like in one run.
• 📈 Every time range Google offers: the past hour, 4 hours, 24 hours, 7 days, 30 days, 90 days, 12 months, 5 years, or everything since 2004 — several in one run, each read on its own.
• 🗂️ Ready for a history: each lookup and each ranked search has an itemKey that stays the same from run to run, so scheduled runs add up to a timeline.
• 📦 A run summary that tells "no data" from "failed": every lookup and every ranking is listed with how it went and, where something went wrong, why.

🚀 Quick start

1. Put a keyword in Keywords, for example bitcoin.
2. Pick the Countries (the United States by default) and the Time ranges (the past 12 months by default).
3. Run. Each keyword, place and time range is one row in the dataset.

For a category's top and rising searches instead, put the category in Categories to rank: its name (Shopping), its path (Shopping > Apparel) or its id (18).

💡 What people use it for

• SEO and content planning — the rising searches around a topic, and the regions where it draws most, before writing for it.
• Product and market research — whether interest in a product, a brand or a category is growing, flat or seasonal, and where.
• Category watch — what people search for in Shopping, Travel or any niche, month after month, with the searches that are breaking out.
• Data pipelines and dashboards — scheduled lookups across keywords, markets and time ranges, in rows ready for a database.

📋 Input

Field	Type	Default	What it does
keywords	array of strings	none	Searches to look up, each on its own, in every place and time range.
keywordCategory	string	all categories	Look the keywords up within one category, to tell one meaning from another: jaguar in Autos & Vehicles.
categories	array of strings	none	Categories whose top and rising searches to read: a name (Shopping), a path (Shopping > Apparel), an id (18), or 0 for all categories together.
subcategories	boolean	false	Rank each category's subcategories too, down to the third level.
allCategories	boolean	false	Rank all 928 categories down to the third level, and all categories together: 929 rankings for each place and time range, about an hour and a half, so give the run a timeout of two hours or more.
countries	array of strings	["US"]	Where to look: a country code (US), a region (US-CA), a US metro area (US-CA-807), or worldwide.
windows	array	["12m"]	1h, 4h, 24h, 7d, 30d, 90d, 12m, 5y or all (since 2004).
maxItemsPerList	integer	0	At most this many searches from each top or rising list. 0 keeps all Google gives.
maxItems	integer	0	Stop after this many results in the whole run, lookups and ranked searches together. 0 means no limit.
proxy	object	Apify residential proxy	Used for every request.

Give keywords, categories or both; every place and time range applies to each. Two keywords and Shopping's top and rising searches, in two countries, over the past 30 days and the past 12 months — 8 lookups and 4 rankings:

{
    "keywords": ["bitcoin", "ethereum"],
    "categories": ["Shopping"],
    "countries": ["US", "GB"],
    "windows": ["30d", "12m"]
}

Category rankings exist only over the past 7 days, 30 days, 90 days and 12 months; a ranking asked for over another range is listed in the run summary as not_available, and costs nothing.

📤 Output

Keyword lookup — recordType: "lookup"

bitcoin in the United States over the past 12 months, on 6 October 2026 (the lists are shortened here; the full row had 53 weekly points, 25 top and 25 rising searches and 51 regions):

{
    "recordType": "lookup",
    "platform": "google",
    "itemKey": "google|lookup|US|12m|all|bitcoin",
    "keyword": "bitcoin",
    "geo": "US",
    "geoScope": "country",
    "geoRequested": "US",
    "window": "12m",
    "category": null,
    "status": "ok",
    "reason": null,
    "points": [
        { "time": "2025-10-05T00:00:00.000Z", "value": 37, "hasData": true, "partial": false },
        { "time": "2025-10-12T00:00:00.000Z", "value": 41, "hasData": true, "partial": false },
        { "time": "2026-09-27T00:00:00.000Z", "value": 17, "hasData": true, "partial": false },
        { "time": "2026-10-04T00:00:00.000Z", "value": 17, "hasData": true, "partial": true }
    ],
    "relatedQueries": {
        "top": [
            { "query": "bitcoin price", "value": 100, "label": "100", "breakout": false },
            { "query": "bitcoin today", "value": 18, "label": "18", "breakout": false }
        ],
        "rising": [
            { "query": "how to buy bitcoin safely", "value": 10950, "label": "Breakout", "breakout": true },
            { "query": "spacex stock", "value": 1750, "label": "+1,750%", "breakout": false }
        ]
    },
    "regions": [
        { "code": "US-WY", "name": "Wyoming", "value": 100 },
        { "code": "US-NV", "name": "Nevada", "value": 49 }
    ],
    "observedAt": "2026-10-06T11:45:57.230Z",
    "url": "https://trends.google.com/trends/explore?date=today+12-m&geo=US&q=bitcoin"
}

Ranked search — recordType: "trend"

The first of Shopping's top searches in the United States over the past 12 months:

{
    "recordType": "trend",
    "platform": "google",
    "list": "explore_top",
    "listKey": "google|explore_top|US|12m|18|2026-10-06T11:46:40.583Z",
    "itemKey": "google|explore_top|US|18|12m|amazon",
    "entityId": null,
    "rank": 1,
    "term": "amazon",
    "termLanguage": null,
    "kind": "search",
    "category": { "id": 18, "name": "Shopping", "path": [{ "id": 18, "name": "Shopping" }] },
    "categories": [],
    "metrics": [{ "name": "interest", "value": 100, "unit": "index", "label": "100", "nullReason": null }],
    "primaryMetric": "interest",
    "startedAt": null,
    "endedAt": null,
    "related": [],
    "geo": "US",
    "geoScope": "country",
    "geoRequested": "US",
    "window": "12m",
    "observedAt": "2026-10-06T11:46:40.583Z",
    "url": "https://trends.google.com/trends/explore?date=today+12-m&geo=US&q=amazon&cat=18",
    "extra": { "category": "Shopping", "value": "100", "breakout": false, "country": "United States" }
}

A rising search has list: "explore_rising" and an increase metric instead: meta glasses led Shopping's rising searches with +160%.

The dataset has two views: Keyword lookups and Category rankings.

🗂️ Data fields

Keyword lookups

Field	What it is
itemKey	The same for the same lookup in every run: place, time range, category and keyword.
keyword	The keyword, as you gave it.
geo, geoScope	The place ("" for worldwide) and what it is: country, region or worldwide.
window	The time range.
category	The category the keyword was looked up in; null for all categories.
status, reason	ok, or not_available when Google has no data for the lookup, with why.
points	Interest over time, 0 to 100, relative to the highest point of the range, from a point a minute over the past hour to a point a month since 2004. Times are UTC. The last point of a range that reaches now is partial; hasData is false where Google had too few searches.
relatedQueries	top: the most searched related searches, valued 0 to 100. rising: the related searches that grew most, valued by their rise in percent; breakout marks those Google shows as Breakout.
regions	Where the keyword is searched most, 0 to 100, the highest first: countries worldwide, states or regions in a country, cities in a region.
observedAt	When the lookup was read.
url	The lookup's page on Google Trends.

Category rankings

Field	What it is
list	explore_top or explore_rising.
listKey	The same for every row of one list as read in this run; matches an entry of the run summary.
itemKey	The same for the same search in the same ranking in every run.
rank	Its place in Google's list, 1 first.
term	The search.
category	The category ranked, with its path from the top level.
metrics	interest, 0 to 100, for a top search; increase, in percent, for a rising one. label is the text Google shows, such as +160% or Breakout.
geo, geoScope, window, observedAt	As for lookups.
url	The search's page on Google Trends, in that category, place and time range.
extra	The same as text, for reading at a glance: category (its path), value, breakout, country.

💳 Pricing

Pay per event: one price per keyword lookup stored with data, and one per ranked search stored. A lookup Google has no data for is stored with the reason and costs nothing; so do a lookup or a ranking that could not be read, an empty ranking, a ranking over a time range Google does not rank, and the run summary. If Apify restarts a run, what it had stored is not stored or charged again.

Event	Free	Starter	Scale	Business and up
Keyword lookup, per 1,000	$3.00	$2.60	$2.30	$2.00
Ranked search, per 1,000	$0.20	$0.20	$0.20	$0.20
Actor start, per run	$0.00005	$0.00005	$0.00005	$0.00005

A ranking is two lists of up to 25 searches each; rising lists are often shorter. In our runs a category's ranking came to between 31 and 50 rows, $0.006 to $0.01; Shopping and its 44 subcategories in Germany over 90 days to about 2,060 rows, about $0.41; and every category worldwide over 7 days to about 44 rows a ranking, so about 41,000 rows and $8.20 for all 929. The run's maximum cost caps what a run can charge; a run that reaches it stores what fits and marks the rest not_reached.

⚠️ Limitations

• The numbers are Google's relative interest, 0 to 100 within each lookup, not search counts. Two lookups are not on the same scale, so a keyword's 50 and another keyword's 50 are not the same number of searches.
• Related topics are not included: Google returns them empty to automated requests.
• Category rankings exist only over the past 7 days, 30 days, 90 days and 12 months, and only down to the third level of Google's category tree: Google ranks no deeper.
• Rare keywords have no data in small places or short ranges; such a lookup is stored with status: "not_available".

❓ FAQ

Why is the highest point always 100? Google scales each lookup to its own highest point. A steady rise from 50 to 100 means interest doubled over the range, whatever the number of searches.

What is a Breakout? Google's mark, in place of a percentage, for a related search that grew by more than 5,000%. Its value is the rise Google gives with it, such as 10950.

Can I look up a city? Inside a region, regions lists cities. As a place to look in, use a region (US-CA) or a US metro area (US-CA-807, San Francisco–Oakland–San Jose).

Do I need a proxy? Residential proxies are the default: Google refuses more of these requests from datacenter addresses. A refused request is sent again from another address, and a lookup or ranking still refused after that is tried once more at the end of the run.

How long does a run take? Three lookups took 7 seconds in our tests, and 45 category rankings about two minutes. A long run goes slower, as Google turns more requests away: every category in one place over one time range is 929 rankings, which Apify read at 550 to 700 an hour on 9 October 2026, so about an hour and a half. Give a run that large a timeout of two hours (7,200 seconds) or more; the default is one hour. A run close to its time limit stops by itself, stores what it has and writes its summary, with the rest marked not_reached.

🤖 Use with AI agents

This Actor is callable as a tool by any MCP-capable agent — Claude, Cursor, VS Code — or by your own code, with no wrapper and nothing extra to deploy.

Connect over MCP

https://mcp.apify.com?tools=autofacts/google-trends

In a client that reads an mcpServers configuration block:

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com?tools=autofacts/google-trends",
      "headers": { "Authorization": "Bearer YOUR_APIFY_TOKEN" }
    }
  }
}

The agent reads this Actor's parameters and their descriptions straight from the input schema, and the hosted server infers the result field types from the dataset schema — so a model knows what to send and what comes back before it ever calls anything.

Or call the API directly

curl -X POST "https://api.apify.com/v2/acts/autofacts~google-trends/run-sync-get-dataset-items?token=$APIFY_TOKEN" \
  -H 'Content-Type: application/json' \
  -d '{"keywords": ["bitcoin"], "categories": ["Shopping"], "countries": ["US"], "windows": ["12m"], "proxy": {"useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"]}}'

The response body is the dataset rows described above, and nothing else: to tell a lookup Google has no data for from one that failed, start the run through /runs instead and read its SUMMARY record.

Run summary — SUMMARY

Every run that gets as far as reading writes a SUMMARY record to its default key-value store, also when a lookup or a ranking could not be read. A run stopped by its input writes none, nor does one that is aborted or being restarted by Apify.

GET https://api.apify.com/v2/key-value-stores/{defaultKeyValueStoreId}/records/SUMMARY?token=$APIFY_TOKEN

The run of the API call above:

{
  "status": "SUCCESS",
  "note": "Everything asked for was read.",
  "itemsStored": 34,
  "lists": [
    {
      "listKey": "google|explore_top|US|12m|18|2026-10-06T11:46:40.583Z",
      "platform": "google",
      "list": "explore_top",
      "geoRequested": "US",
      "geo": "US",
      "geoScope": "country",
      "window": "12m",
      "windowStart": "2025-10-06T11:46:40.583Z",
      "windowEnd": "2026-10-06T11:46:40.583Z",
      "category": { "id": 18, "name": "Shopping", "path": [{ "id": 18, "name": "Shopping" }] },
      "sourceAsOf": null,
      "observedAt": "2026-10-06T11:46:40.583Z",
      "served": 25,
      "total": 25,
      "filtered": false,
      "status": "ok",
      "reason": null,
      "url": "https://trends.google.com/trends/explore?date=today+12-m&geo=US&cat=18"
    },
    {
      "listKey": "google|explore_rising|US|12m|18|2026-10-06T11:46:40.583Z",
      "platform": "google",
      "list": "explore_rising",
      "geoRequested": "US",
      "geo": "US",
      "geoScope": "country",
      "window": "12m",
      "windowStart": "2025-10-06T11:46:40.583Z",
      "windowEnd": "2026-10-06T11:46:40.583Z",
      "category": { "id": 18, "name": "Shopping", "path": [{ "id": 18, "name": "Shopping" }] },
      "sourceAsOf": null,
      "observedAt": "2026-10-06T11:46:40.583Z",
      "served": 8,
      "total": 8,
      "filtered": false,
      "status": "ok",
      "reason": null,
      "url": "https://trends.google.com/trends/explore?date=today+12-m&geo=US&cat=18"
    }
  ],
  "lookups": [
    {
      "itemKey": "google|lookup|US|12m|all|bitcoin",
      "keyword": "bitcoin",
      "geoRequested": "US",
      "geo": "US",
      "window": "12m",
      "category": null,
      "observedAt": "2026-10-06T11:45:57.230Z",
      "status": "ok",
      "reason": null,
      "url": "https://trends.google.com/trends/explore?date=today+12-m&geo=US&q=bitcoin"
    }
  ],
  "restarted": false,
  "startedAt": "2026-10-06T11:45:50.688Z",
  "finishedAt": "2026-10-06T11:46:40.707Z",
  "extra": {}
}

status	Meaning	What to do
SUCCESS	Every lookup and ranking asked for was read, or stopped by a limit you set	Use the dataset
PARTIAL_RESULTS	Some could not be read	Use the dataset; run the rest again later
NO_RESULTS	The same, and nothing was stored	Run again in a few minutes
RUN_FAILED	The run stopped with an error	The rows already in the dataset are valid

Each entry of lookups is one keyword in one place and time range, with its status:

status	Meaning
ok	Read; its row is in the dataset.
not_available	Google has no data for it; its row is in the dataset with the reason.
not_reached	Not stored: the run had stopped at Maximum results in total or at the maximum charge you set, or the run was close to its time limit.
failed	Could not be read, also when tried again at the end of the run; reason says why.

Each entry of lists is one top or rising list of one category in one place and time range: its listKey (the rows' own), the windowStart and windowEnd it covers and when it was read (observedAt) — all three null for a ranking Google was not asked for, could not be read, or was not stored — the searches stored from it (served) and those in Google's list (total), filtered (always false: a ranking is stored as Google gives it, up to your maximum per ranking), the list's page on Google Trends (url), and its status, with a reason where there is something to say:

status	Meaning
ok	Read. served may be less than total for your limits; reason says which.
empty	Google lists no searches there.
not_available	Google has no such ranking, such as over the past 24 hours.
not_reached	Not stored: the run had stopped at Maximum results in total or at the maximum charge you set, or the run was close to its time limit.
failed	Could not be read, also when tried again at the end of the run; reason says why.

stoppedBy, only when the run stopped before reading everything, says why: maxItems, chargeLimit or timeLimit. restarted says whether the run picked up after Apify restarted it; a restarted run does not store a lookup or a list twice.

🧰 Other Actors by autofacts

Apify only auto-recommends Actors in the same category, so here are the ones that actually pair with this one:

Actor	What it's for
Google Trends Trending Now	What is trending on Google Search right now, in each of 125 countries, with search volumes
Schema Markup Scraper & SEO Auditor	What the pages that rank for a keyword say about themselves to search engines
Google Ads Scraper	The ads the brands behind a search run on Google
YouTube Subtitle & Transcript Scraper	What the videos about a topic say, as clean text
Shopify Scraper	The products and prices behind a rising shopping search

All of them: apify.com/autofacts