Google Trends Scraper: Compare Unlimited Keywords, Daily Data

Get Google Trends data without a browser. It's fast, cheap, and you pay only for keywords that succeed.

A pytrends alternative that doesn't hit 429 Too Many Requests. pytrends was archived in 2025, and Google's official Trends API is still invite-only. This Actor uses rotating proxy sessions and automatic retries. In our 30-keyword, 5-year daily test, it returned 54,810 data points with zero errors.

What makes it different

• Compare more than 5 keywords on one scale. Google Trends only compares 5 terms at a time, and scores from separate searches can't be compared. This Actor sorts your keywords by popularity and chains overlapping batches. That puts 10, 50 or 200 keywords on one 0-100 scale. In our tests, the results match Google's direct comparisons within about 3%.
• Daily data for long ranges. For ranges over about 9 months, Google only returns weekly or monthly points. Turn on Daily data to get one point per day for years, stitched from overlapping daily windows. Over 3 years of bitcoin data, the stitched daily series correlates 0.997 with Google's own weekly curve.
• No browser. The Actor calls Google Trends directly, with automatic retries and fresh proxy sessions. Five keywords with regions and related queries finish in about a minute.

What you get

Data	Description
Interest over time	A 0-100 score per date for every keyword, all on one scale
Interest by region	Countries, sub-regions, cities or US metros, scored 0-100
Related queries	Top and rising searches for each keyword, including "Breakout" terms
Trending Now	Today's trending searches for a country, with news links

Filter by country or region, time range (past hour to 2004), category, and search type (web, images, news, Shopping, YouTube).

Example input

{
  "keywords": ["coffee", "tea", "matcha", "espresso", "latte", "chai", "kombucha"],
  "geo": "US",
  "timeRange": "today 5-y",
  "dailyData": true,
  "includeRelatedQueries": true
}

Example output

{"type": "interest_over_time", "keyword": "matcha", "geo": "US", "timeRange": "today 5-y", "date": "2026-03-14", "value": 7.42, "isPartial": false}
{"type": "related_query", "keyword": "matcha", "list": "rising", "query": "matcha latte recipe", "value": 350, "formattedValue": "+350%"}
{"type": "region", "keyword": "matcha", "geoCode": "US-HI", "geoName": "Hawaii", "value": 100}

Every row has a type field, so you can filter the dataset or export one type at a time to CSV or Excel.

Pricing

$0.002 per keyword ($2 per 1,000), however many dates, regions or related queries it returns. A Trending Now list costs the same $0.002. There's no start fee and no extra platform usage charge. Keywords that fail are free.

Use it from Python instead of pytrends

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("rishupishu/google-trends-scraper").call(run_input={
    "keywords": ["coffee", "tea", "matcha", "espresso", "latte", "chai"],
    "timeRange": "today 5-y",
    "dailyData": True,
})
rows = client.dataset(run.default_dataset_id).list_items().items

For a pandas DataFrame, run pd.DataFrame(rows).query("type == 'interest_over_time'").

Notes

• Values are relative (0-100), not absolute search counts. That's how Google Trends works.
• When you compare more than 5 keywords, rounding means very small keywords next to very large ones still lose a little precision. The Actor groups similar keywords together to keep this small.
• Related topics are not included. Google only serves them to real browsers.
• If you set a maximum charge for a run, the Actor stops cleanly when it reaches it.