How to get Google Trends data with an API (Python, Node or no code)

#javascript #python #api #seo

Google Trends has no official public API, and the website hands you one chart at a time. If you want trend data in a spreadsheet, a dashboard or an AI agent's context (tracking demand for a product category every week, or spotting rising queries before they peak), you need another way to get it.

This tutorial uses Google Trends Scraper, an Apify actor I built. It returns three Google Trends widgets for up to 20 keywords per run: interest over time, interest by region and related queries. The output is flat rows that drop straight into Sheets or a BI tool. It works for any country or worldwide, over 7 days to 5 years, with no browser and no API key. The full examples are on GitHub: auto-actor/google-trends-scraper-all-widgets.

What people use it for

Weekly demand tracking for your product category or brand in one spreadsheet.
Finding rising related queries before they peak, for content and ads.
Comparing interest across countries for market entry decisions.

Input

{"keywords": ["bitcoin"], "geo": "", "timeRange": "past_12_months"}

Field	What it does
`keywords`	Up to 20 search terms to analyse.
`geo`	Two-letter country code such as `US`, `AU` or `GB`, or empty for worldwide.
`timeRange`	One of `past_7_days`, `past_30_days`, `past_90_days`, `past_12_months`, `past_5_years`.

Python

"""Run Google Trends Scraper on Apify and print the results.

    pip install apify-client
    export APIFY_TOKEN=...   # Apify Console -> Settings -> Integrations
    python example.py
"""
import os

from apify_client import ApifyClient

client = ApifyClient(os.environ["APIFY_TOKEN"])

run = client.actor("daedal_quintuplet/google-trends-scraper-all-widgets").call(
    run_input={
        "keywords": [
            "bitcoin"
        ],
        "geo": "",
        "timeRange": "past_12_months"
    }
)

rows = client.dataset(run["defaultDatasetId"]).iterate_items()
for row in rows:
    print(row["kind"], "|", row["label"], "|", row["value"])

Node.js

// Run Google Trends Scraper on Apify and print the results.
//
//   npm install apify-client
//   APIFY_TOKEN=... node example.js     (token: Apify Console -> Settings -> Integrations)

const { ApifyClient } = require('apify-client');

async function main() {
    const client = new ApifyClient({ token: process.env.APIFY_TOKEN });

    const run = await client.actor('daedal_quintuplet/google-trends-scraper-all-widgets').call({
        "keywords": [
            "bitcoin"
        ],
        "geo": "",
        "timeRange": "past_12_months"
    });

    const { items } = await client.dataset(run.defaultDatasetId).listItems();
    for (const row of items) {
        console.log(row.kind, '|', row.label, '|', row.value);
    }
}

main().catch((err) => {
    console.error(err);
    process.exit(1);
});

No code: one HTTP request

Works from n8n, Make, Zapier or curl:

curl -X POST "https://api.apify.com/v2/acts/daedal_quintuplet~google-trends-scraper-all-widgets/run-sync-get-dataset-items?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"keywords": ["bitcoin"], "geo": "", "timeRange": "past_12_months"}'

What you get

Every row has a kind, so you can filter it into one table per widget:

Field	Meaning
`keyword`	The search term the row belongs to
`kind`	`interest_over_time`, `interest_by_region` or `related_query`
`label`	Week range, region name or related query text, depending on `kind`
`time`	Unix seconds for `interest_over_time` rows; null otherwise
`value`	Google's relative score, 0 to 100
`geo`	Country code or `worldwide`
`trend`	`related_query` rows only: whether the query is from the top or rising list
`link`	`related_query` rows only: link to that query on Google Trends

Google Trends values are relative: 100 is the highest point for that keyword in the period you picked, not a count of searches.

Price

$0.0025 per row ($2.50 per 1,000 rows), paid per result, with no monthly fee. One keyword over 12 months produced about 170 rows in our tests, so about $0.43. Apify's free plan includes $5 of usage a month, which is enough to try it.

Links: Store page · GitHub examples

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