Google Trends Scraper – Pay Per Result, No Browser

What does Google Trends Scraper do?

It pulls Google Trends data through the same JSON API the Trends website uses, with no browser involved. For each search term, or for one comparison of up to 5 terms, you get a single clean dataset item with:

• Interest over time: every point has an ISO date, a value from 0 to 100 and an isPartial flag
• Interest by region: countries, or subregions when you set a country
• Related queries: top and rising, including "Breakout" terms
• Related topics: top and rising, when Google returns them

Every Google Trends option is supported: location (country or subregion), preset or custom time range, category, and search type (web, images, news, Google Shopping, YouTube).

Google Trends API alternative without a browser

Google has no official Trends API, and the Python library pytrends breaks whenever Google changes its endpoints. This scraper is a maintained pytrends alternative that runs on Apify: it calls the Trends JSON endpoints directly, retries rate limits with a fresh proxy session and returns typed JSON you can load into pandas, Google Sheets or a database without reshaping.

• Fast. A typical term finishes in a few seconds, not minutes, at 256 MB of memory.
• Built for rate limits. When Google answers 429, the term is retried with a fresh residential session and backoff.
• Pay only for results. Terms that fail or have no data are not charged, and there is no start fee beyond $0.00005.
• Honest failures. If every term fails because of errors, the run fails, so a scheduled job can't quietly return nothing.

Input

Field	Description
searchTerms	Keywords to look up (up to 500). Each term becomes one result, or all terms become one comparison.
compareTerms	Put all terms (max 5) into one comparison, like adding several terms in the Google Trends UI.
geo	ISO country code (US, DE) or subregion (US-CA, GB-ENG). Empty means worldwide.
timeRange	Preset period, from the past hour to 2004–present.
customTimeRange	Exact dates as YYYY-MM-DD YYYY-MM-DD; overrides timeRange.
category	Google Trends category ID (0 = all).
property	Web, image, news, Google Shopping or YouTube search.
maxConcurrency, maxRetries	Parallelism (1–5) and attempts per term (1–3).

{
  "searchTerms": ["bitcoin", "ethereum", "solana"],
  "compareTerms": true,
  "geo": "US",
  "timeRange": "today 12-m"
}

Output fields

Field	Description
query, searchTerms	The term, or "bitcoin vs ethereum" plus the list of compared terms
geo, timeRange, category, property	The options the result was fetched with
interestOverTime	List of {date, formattedTime, values: {term: 0–100}, isPartial}
interestBySubregion	List of {geoCode, geoName, values}; regions without data are dropped
relatedQueries	Per term: top and rising lists of {query, value, formattedValue}
relatedTopics	Per term: top and rising lists of {topic, topicType, mid, value}
scrapedAt	ISO 8601 UTC timestamp

{
  "query": "bitcoin vs ethereum",
  "searchTerms": ["bitcoin", "ethereum"],
  "geo": "US",
  "timeRange": "today 12-m",
  "interestOverTime": [
    {"date": "2026-10-25T00:00:00Z", "formattedTime": "Oct 25 – 31, 2026", "values": {"bitcoin": 21, "ethereum": 3}, "isPartial": true}
  ],
  "interestBySubregion": [{"geoCode": "US-NV", "geoName": "Nevada", "values": {"bitcoin": 87, "ethereum": 13}}],
  "relatedQueries": {"bitcoin": {"top": [{"query": "bitcoin price", "value": 100, "formattedValue": "100"}], "rising": []}},
  "scrapedAt": "2026-10-28T12:00:00Z"
}

How much does it cost to scrape Google Trends?

You pay per result: one dataset item per term, or one per comparison. Platform usage (compute and proxy) is included in the price.

Plan	Price per 1,000 results
Free	$2.00
Starter (Bronze)	$1.50
Scale (Silver)	$1.20
Business (Gold)	$1.00

Each run also charges $0.00005 for the start. Example: 100 terms on the Starter plan cost $0.15. Set a maximum total charge on the run and the scraper stops once that budget is used up. Terms that fail or have no data cost nothing.

Use Google Trends data in Python or Google Sheets

from apify_client import ApifyClient

client = ApifyClient("<YOUR_API_TOKEN>")
run = client.actor("murmuring_headlamp/google-trends-fast").call(run_input={"searchTerms": ["coffee"], "geo": "US"})
items = client.dataset(run["defaultDatasetId"]).list_items().items

In Google Sheets, use the Apify integration or export the dataset as CSV from the run's Export tab. Dates are ISO 8601 UTC and values are keyed by term, so no reshaping is needed.

Tips

• In comparison mode Google scales all terms against each other, so the values are comparable. Separate terms are each scaled 0–100 on their own.
• Keep maxConcurrency at 2–3 for large lists: slower, but far fewer rate limits.
• Leave the default residential proxy on. Google rate-limits datacenter IPs heavily.

FAQ

Why do related queries contain unrelated terms like "how to bake a cake"? Google itself returns them for automated access, so every Google Trends scraper, browser-based ones included, gets the same entries. Filter rising queries by your search term downstream.

A term came back without data. Rare terms have no interest-over-time data in Google Trends. The run reports them as "without data" in its status message, nothing is pushed for them, and they are not charged.

Related topics are empty? Google currently leaves related topics out for many queries and regions. The field is still there, so your schema stays stable.

Is scraping Google Trends legal? Google Trends shows public, aggregated, anonymous data. This scraper collects no personal data. You're responsible for how you use the results.

Related scrapers

• Google Jobs Scraper: job postings with salaries, descriptions and apply links.

This Actor is not affiliated with Google.