Google Trends Bulk Keyword Comparison

Compare up to 500 keywords on Google Trends and get every one on the same 0 to 100 scale. Google only compares five keywords at a time and rescales each comparison, so numbers from separate comparisons can't be ranked against each other. This Actor links comparisons through shared keywords, so your whole list comes back as if Google had compared it in one chart. No login, no API key.

Use it to rank a product catalogue by search demand, size markets, pick content topics, or compare brands, competitors and features side by side.

Sample output (real run: 10 drinks, US, past 12 months, one shared scale)

Keyword	Average interest	Peak	Peak week
coffee	76.5	100	2026-04-12
tea	36.6	45	2026-04-05
espresso	9.6	14.8	2026-04-12
matcha	6.2	8.6	2026-04-12
energy drink	3.7	7.9	2026-04-12
chai	3.0	4.2	2026-08-23
cold brew	2.0	3.4	2026-06-21
kombucha	1.1	1.6	2026-06-21

Google Trends only compares 5 terms at a time and rescales every request to 0-100. This Actor chains overlapping batches so every keyword sits on the same scale (validated within 0-1.7% of Google's own numbers), and the full time series comes with each row.

Why this one

	This Actor	pytrends / DIY	Typical Store alternative
Keywords compared on one scale	Hundreds	5	5
Daily data for multi-year ranges	Yes, stitched and calibrated	Weekly or monthly only	Rarely
Rate limits (429)	Handled with session rotation	Breaks	Some fail 1 run in 4
Price	$3 / 1,000 keyword series	Free, your time	$2 to $25 / 1,000, often plus start fees

What it costs: 100 keywords with their time series = about $0.50.

What this Actor does

• Takes any list of keywords or topics (up to 500) and returns them on one shared scale, where 100 is the single highest point of any keyword in the run.
• Orders keywords by size and links each Google comparison through a shared pivot keyword, so even keywords hundreds of times smaller than the leader keep their detail.
• Returns average, peak, peak date, latest value and change % for every keyword, plus the full time series.
• Works for any location (country, state, US metro) and any time range, with optional daily data over long ranges.
• Optionally adds interest by region and related and rising queries for every keyword.

How accurate is it?

We checked it against Google itself. Eighteen keywords were compared together, then pairs that had landed in different Google comparisons were compared directly on Google Trends:

Pair	Google, compared directly	This Actor	Difference
chatgpt / yoga	5.27	5.27	0.0%
netflix / pilates	7.82	7.81	0.1%
coffee / sourdough	9.23	9.26	0.4%
airbnb / padel	21.67	21.76	0.4%
bitcoin / kombucha	14.70	14.52	1.2%
tesla / notion	11.66	11.86	1.7%

A 94-keyword run spanning a 1,300-fold range of search volume, from "amazon" to "evernote", finished in about a minute. 93 of the 94 keywords were marked high precision.

What data do you get?

Field	Description
keyword, keywordTitle	The keyword, and the readable name for topic IDs
geo, timeframe, startDate, endDate, resolution	What was measured
average, peak, peakDate, latest, changePct	Headline numbers on the shared scale
timeline	Date and value for every point
scale.precision	high, medium or low; low means the keyword is tiny next to the largest one
interestByRegion	Optional: interest per region
relatedQueries	Optional: top and rising related searches

How to compare keywords on Google Trends in bulk

1. Paste your keywords, one per line.
2. Add a location (for example US), or leave it empty for worldwide.
3. Pick a time range, and turn on daily data for long ranges if you need it.
4. Run it, sort by average to rank your list, and export to CSV or Excel.

Example input

{
  "keywords": ["coffee", "tea", "matcha", "kombucha", "yerba mate", "cold brew", "chai", "espresso", "oat milk", "energy drink"],
  "geos": ["US"],
  "timeframe": "today 12-m"
}

How much does it cost?

You pay per keyword, plus a small charge per keyword for putting more than five on one scale. Region breakdowns, related queries and daily history are optional extras. Current prices, with discounts on higher Apify plans, are on the pricing tab.

FAQ

Why not just compare five at a time on Google Trends? Each comparison is scaled so its own top keyword is 100, so a 40 in one chart and a 40 in another usually mean different things. This Actor removes that problem.

Why do values differ from what I see on Google Trends? They're relative to the biggest keyword in your whole list. Ratios between keywords match Google; the absolute level depends on the list.

What does low precision mean? Google rounds to whole numbers, so a keyword over about 100 times smaller than the largest in the run carries less detail. Run small keywords in their own list for finer resolution.

Related Actors

• Google Trends Scraper: the all-in-one version, including Trending Now.
• Google Trends Trending Now Scraper: what people are searching right now, with volume.

Use it as an API

Run it from your own code and get the results back in one call. Replace YOUR_TOKEN with your Apify API token.

curl -X POST "https://api.apify.com/v2/acts/headply~google-trends-bulk-keyword-comparison/run-sync-get-dataset-items?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"keywords": ["coffee", "tea", "matcha", "kombucha", "yerba mate", "cold brew", "chai", "espresso", "oat milk", "energy drink"], "geos": ["US"], "timeframe": "today 12-m"}'

from apify_client import ApifyClient

client = ApifyClient("YOUR_TOKEN")
run_input = {'keywords': ['coffee',
              'tea',
              'matcha',
              'kombucha',
              'yerba mate',
              'cold brew',
              'chai',
              'espresso',
              'oat milk',
              'energy drink'],
 'geos': ['US'],
 'timeframe': 'today 12-m'}
run = client.actor("headply/google-trends-bulk-keyword-comparison").call(run_input=run_input)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

It also works from Make, Zapier, n8n, Google Sheets and as a tool for AI agents through the Apify MCP server.

More data tools from the same developer

• Threads Scraper & API: posts, reply trees, profiles and keyword search from Threads
• Yelp Scraper & API: every business in a city with phones, websites and all reviews
• TikTok & YouTube Transcript API: video to text, even without captions
• Google Trends Scraper & API: hundreds of keywords on one scale, daily history
• Airbnb & Vrbo Scraper: listings, calendars, occupancy and revenue
• Jumia Scraper & API: prices and sellers across 8 African countries