Google Trends Scraper

Give it keywords, a Google Trends link or a country and it returns Google Trends data as JSON: one row per keyword with interest over time, interest by region, related queries and related topics, or one row per live "Trending now" search. $2.70 per 1,000 rows on the free plan, less on paid plans. You pay only for rows you get.

$2.70 per 1,000 result rows on the Free plan, down to $0.27 on higher plans

Why this actor

• Compares 12+ keywords on one scale in one run, not only Google's limit of 5.
• Monitoring mode (onlyChanges): after a baseline, a keyword comes back only when a new rising query appears or interest moves; unchanged keywords are free.
• Free error rows with a code for every input that fails.

Drop-in input

Drop-in input. Input written for the Apify-made apify/google-trends-scraper works as it is (searchTerms, geo, timeRange...), and the output keeps its field names. 20.8% of that actor's runs failed or timed out (Apify Store, 30 days to 2026-10-31). Here a keyword that cannot be read is a free error row with a code, and the other keywords still arrive.

As stated in the actor’s README. The full list of accepted input names is on the Store page.

What you get

Every keyword is one row. The field names follow the well-known apify/google-trends-scraper, so a pipeline built for it keeps working (see "Switching from another Google Trends actor").

"Trending now" rows look different: keyword, geo, searchVolume (lower bound of Google's bracket), increasePercent, startedAt, endedAt, active, relatedKeywords, categoryIds, articleCount, windowHours.

Sample row (from the README example; long text shortened, lists cut to two items):

{
  "rowType": "trend",
  "searchTerm": "coffee",
  "geo": "US",
  "timeRange": "today 12-m",
  "averageInterest": 77.7,
  "interestOverTime_timelineData": [
    {
      "time": "1760832000",
      "formattedTime": "Oct 19 – 25, 2025",
      "value": [
        63
      ],
      "hasData": [
        true
      ],
      "formattedValue": [
        "63"
      ]
    }
  ],
  "interestBySubregion": [
    {
      "geoCode": "US-WY",
      "geoName": "Wyoming",
      "value": [
        100
      ]
    }
  ],
  "relatedQueries_top": [
    {
      "query": "coffee near me",
      "value": 100,
      "formattedValue": "100"
    }
  ],
  "relatedQueries_rising": [
    {
      "query": "best coffee near me",
      "value": 160,
      "formattedValue": "+160%"
    }
  ],
  "scale": {
    "method": "single",
    "keywords": [
      "coffee"
    ]
  }
}

Price

Live Apify price on 2026-10-31, per 1,000 rows, by Apify plan. You pay only for rows delivered; error and summary rows marked free in the README cost nothing. Plus $0.00 per GB of memory when a run starts.

Use cases

• SEO and content: find what is rising for a topic and plan around the season.
• E-commerce: compare product or brand interest across countries and weeks.
• Market research: track many brands on one scale with a scheduled monitor.
• News and social teams: poll "Trending now" every few hours.

Run it from code or an AI agent

Actor ID arcadium/google-trends. Set APIFY_TOKEN to your Apify API token. The input below is the actor’s prefilled example; see the guide for every field.

curl -X POST "https://api.apify.com/v2/acts/arcadium~google-trends/run-sync-get-dataset-items" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"searchTerms":["webscraping"],"maxRetries":6,"proxyCountry":"US"}'

// npm install apify-client
import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('arcadium/google-trends').call({
  "searchTerms": [
    "webscraping"
  ],
  "maxRetries": 6,
  "proxyCountry": "US"
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

# pip install apify-client
import os
from apify_client import ApifyClient

client = ApifyClient(os.environ["APIFY_TOKEN"])
run = client.actor("arcadium/google-trends").call(run_input={
    "searchTerms": ["webscraping"],
    "maxRetries": 6,
    "proxyCountry": "US",
})
items = client.dataset(run["defaultDatasetId"]).list_items().items
print(items)

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com/?tools=arcadium/google-trends",
      "headers": {
        "Authorization": "Bearer <APIFY_TOKEN>"
      }
    }
  }
}

# pip install langchain-apify   (reads APIFY_API_TOKEN from the environment)
from langchain_apify import ApifyActorsTool

tool = ApifyActorsTool("arcadium/google-trends")
rows = tool.invoke({"run_input": {
    "searchTerms": ["webscraping"],
    "maxRetries": 6,
    "proxyCountry": "US",
}})
# or give `tool` to an agent: create_react_agent(llm, [tool])

# pip install llama-index-readers-apify
import os
from llama_index.core import Document, VectorStoreIndex
from llama_index.readers.apify import ApifyActor

reader = ApifyActor(os.environ["APIFY_TOKEN"])
documents = reader.load_data(
    actor_id="arcadium/google-trends",
    run_input={
        "searchTerms": ["webscraping"],
        "maxRetries": 6,
        "proxyCountry": "US",
    },
    dataset_mapping_function=lambda item: Document(text=str(item.get("title") or ""), metadata={"url": item.get("url")}),
)
index = VectorStoreIndex.from_documents(documents)

# pip install crewai crewai-tools langchain-apify   (reads APIFY_API_TOKEN from the environment)
from crewai import Agent
from crewai_tools import ApifyActorsTool

tool = ApifyActorsTool(actor_name="arcadium/google-trends")
researcher = Agent(
    role="Research analyst",
    goal="Answer with data collected by the tool",
    backstory="Uses public web data.",
    tools=[tool],
)

{
  "nodes": [
    {
      "name": "Run arcadium/google-trends",
      "type": "n8n-nodes-base.httpRequest",
      "typeVersion": 4,
      "position": [
        0,
        0
      ],
      "parameters": {
        "method": "POST",
        "url": "https://api.apify.com/v2/acts/arcadium~google-trends/run-sync-get-dataset-items",
        "authentication": "genericCredentialType",
        "genericAuthType": "httpHeaderAuth",
        "sendBody": true,
        "specifyBody": "json",
        "jsonBody": "{\"searchTerms\":[\"webscraping\"],\"maxRetries\":6,\"proxyCountry\":\"US\"}",
        "options": {
          "timeout": 300000
        }
      }
    }
  ],
  "connections": {}
}

// Extensions > Apps Script. Store your token once: Project Settings > Script properties > APIFY_TOKEN.
function importLastRun() {
  const token = PropertiesService.getScriptProperties().getProperty('APIFY_TOKEN');
  const url = 'https://api.apify.com/v2/acts/arcadium~google-trends/runs/last/dataset/items?status=SUCCEEDED&clean=true&format=json';
  const res = UrlFetchApp.fetch(url, { headers: { Authorization: 'Bearer ' + token } });
  const rows = JSON.parse(res.getContentText());
  if (!rows.length) return;
  const keys = Object.keys(rows[0]);
  const values = rows.map((r) => keys.map((k) => (typeof r[k] === 'object' ? JSON.stringify(r[k]) : r[k])));
  const sheet = SpreadsheetApp.getActiveSheet();
  sheet.clearContents();
  sheet.getRange(1, 1, 1, keys.length).setValues([keys]);
  sheet.getRange(2, 1, values.length, keys.length).setValues(values);
}

Limitations

• Public Google Trends data only. Nothing behind a login.
• Google shows relative interest (0-100), not search counts. Trending now gives a volume bracket (for example 100,000+), not an exact number.
• Google sometimes answers "too many requests". The actor retries on the same or a fresh connection, repeats the lookup for new tokens, and after a short pause tries the whole keyword again, so a keyword may take a few seconds (rarely a minute) longer; if all retries fail it returns a free blocked row.
• If three keywords in a row still end blocked, Google is limiting the whole shared connection pool. The actor then pauses for about a minute once and starts the next keywords at most every 5 seconds, so it does not prolong the limit for this run or for other users. After three successful keywords in a row it returns to normal speed. Expect a long list to take a few minutes longer on such a day rather than fail.
• Related topics are empty for many rare keywords; that is Google's answer, not a failure.
• Values for more than 5 compared keywords are approximate (see above).

FAQ

Why do two runs of the same keyword differ slightly? Google samples its data and updates it continuously, and the last point of a period is still being filled in (isPartial).

What do the codes in geo look like? Country codes like US, regions like US-CA, GB-ENG. Interest-by-region rows use the same codes.

Something looks wrong in the output. Who do I tell? Open an issue on the actor page with the run link. We read them all.

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