Google Trends Scraper API for Interest Over Time

Compare how search interest in a few terms changes over time, and export the results to a spreadsheet. The Actor collects interest over time, related queries, regional interest and the public trending-searches feed. Related topics are also available, but Google often returns them empty.

This Actor uses Google Trends website endpoints and its public RSS feed. It is not Google's official API and is not affiliated with Google. Google also offers a separate Trends API alpha, with its own access requirements.

Start with a small run

The form opens with a ready comparison: iced coffee and cold brew in the United States over the Past 12 months, with Interest over time selected. Start it as it is, or replace the two terms with your own.

1. Enter up to five Search terms, one per line (a comma also separates terms). Keep terms you want to compare in the same run.
2. Choose Results to collect. For a comparison, Interest over time is enough.
3. Choose Country and Time range.
4. Start the run and open Interest over time in the Output tab. To download it, open Storage > Dataset, choose Interest over time, then CSV, Excel or JSON.

On 2 October 2026 this comparison returned 106 rows (53 weekly values per term) and cost $0.368 at base prices: $0.05 at startup plus 106 x $0.003. Google chooses the intervals, so the row count can differ slightly between runs.

Custom dates (optional) is only for an exact period. Category, region detail, language and proxy settings are under Advanced options; you do not need them for a first run.

Watch: compare two search terms

Let's use a Christmas tree seller as an example. The video follows a real run comparing artificial and real Christmas tree searches in the United States over five years, from the input form to the weekly rows, the related queries and the CSV/Excel export.

The chart in the video is drawn from the exported interest-over-time rows. The coffee example below shows the same kind of rows for two other terms.

Selected rows from the 2 October 2026 run:

Week	Keyword	Relative interest	Partial week?
Dec 21 – 27, 2025	iced coffee	41	false
Dec 21 – 27, 2025	cold brew	35	false
Jun 21 – 27, 2026	iced coffee	68	false
Jun 21 – 27, 2026	cold brew	100	false
Sep 27 – Oct 3, 2026	cold brew	45	true

Cold brew reached the peak of the comparison (100) in late June, while iced coffee stayed lower. These are relative interest values, not search counts: 100 is the highest point in this comparison, not 100 searches. The last week is marked partial because it had not finished.

More examples

• Weekly Google Trends report for Google Sheets: three coffee terms in the US over the past 12 months, one row per term and week (159 rows, about $0.53 at base prices). Schedule it weekly with the Google Sheets integration.
• Compare ChatGPT and Claude in the United States: interest over time for the past three months. In a September run it returned 186 daily rows, about $0.61 at base prices. For a step-by-step guide to turning the rows into a chart, read Compare Google Trends terms in a spreadsheet.
• Export current US trending searches: no search terms needed. Ten rows cost $0.08 at base prices, including startup. The feed size varies.
• Compare Nike and Adidas search interest: Weekly worldwide Google Trends interest for Nike and Adidas over the past 12 months, ready for a chart.
• Find rising searches related to air fryers: Related and rising Google searches for 'air fryer' in the United States over the past 12 months, for content and product ideas.
• See which US states search for pickleball most: Google Trends interest by US state for pickleball over the past 12 months.
• Download Google Trends data as CSV for the past year: Weekly Google Trends interest for bitcoin over the past 12 months, as rows you can export to CSV, Excel or JSON.

Choose what to collect

You want	Form settings	Output view
Compare terms over time	Enter Search terms; select Interest over time; choose the country and time range.	Interest over time
Related searches	Enter terms; select Related and rising queries.	Related queries
Geographic interest	Enter terms; select Interest by region. Adjust Region detail only if needed.	Interest by region
Current trending searches	Select only Trending now; choose Country for Trending now. Search terms and Time range are not used by this feed.	Trending now
Related topics	Enter terms; select Related topics (limited availability). Empty lists are common.	Related topics

Each selected type adds its own rows and has its own table in the Output tab, so you can select several in one run. All rows keeps every row together, with a dataType column. To download one table, open Storage > Dataset, choose it in the Dataset menu, then CSV, Excel or JSON. The Export button at the top downloads All rows. From the API, the run's storageIds.datasets lists the tables (timeline, relatedQueries, relatedTopics, regions, trending); the default dataset is All rows. related_queries and related_topics hold the same rows, for integrations built before October 2026.

A small regional-interest request:

{
  "searchTerms": ["cold brew"],
  "dataTypes": ["interest_by_region"],
  "geo": "US",
  "timeframe": "today 3-m",
  "regionResolution": "REGION"
}

Trending searches need no search terms:

{
  "dataTypes": ["trending_now"],
  "trendingGeo": "US"
}

Countries and dates

Choose countries by name. Country applies to interest over time, related data and regional interest; Worldwide is also available. Country for Trending now is a separate setting used only by Trending now.

For Time range, pick a preset such as Past 7 days, Past 3 months or Past 12 months. For an exact period, fill in Start date and, if you like, End date; they override the preset. Without an end date the range runs to today. A reversed or invalid date stops the run with an explanation before any data is requested.

Results to collect and availability

dataType	One row represents	What to expect
interest_over_time	A keyword at one returned time point	Relative interest; Google chooses the intervals
related_queries	A related query for one keyword, in the top or rising list	Lists can be empty or blocked
related_topics	A related topic for one keyword, in the top or rising list	Often empty; not guaranteed
interest_by_region	A keyword in one geographic area	Depends on the term, country and region detail
trending_now	One item from the country's trending feed	A current snapshot, not a full archive

Related topics are requested separately for each keyword, because Google can leave them out of comparison requests. Topic scores rank topics within one keyword; they are not comparable between keywords. In September 2026 tests, Google returned empty topic lists for several ordinary keywords. Empty lists are reported as empty; the Actor never fills them with related queries or invented topics.

Retries and proxy rotation help with temporary failures. They cannot guarantee complete data or uninterrupted access to Google.

Regional results leave out places where Google explicitly reports insufficient data for a term. A zero score that Google marks as available is kept.

Input reference

Field	API default	Meaning
searchTerms	None	Up to five keywords; not needed for trending searches
dataTypes	interest_over_time and trending_now	Result types from the table above
geo	Empty (worldwide)	Country code for keyword research, such as US or FI
timeframe	today 12-m	For example today 5-y, now 7-d, or YYYY-MM-DD YYYY-MM-DD
startDate	None	Exact start date, YYYY-MM-DD. Without an end date, the range runs to today.
endDate	None	Optional end date, on or after startDate. Custom dates override timeframe.
category	0	Google Trends category ID; 0 means all categories
language	en-US	Language of Google's labels; results are not translated
regionResolution	COUNTRY	COUNTRY (worldwide searches; with a country chosen, its regions are used), REGION, CITY or DMA (United States only; other countries fall back to REGION)
trendingGeo	US	Country of the trending feed. It does not follow geo; set it for any other country.
proxyConfiguration	Residential Apify Proxy	You can set direct or custom routing explicitly

The form opens with example values (iced coffee, cold brew, United States, Interest over time). API requests do not get these values; they use the defaults above. A comma separates terms, so "iced coffee, cold brew" is read as two terms, like on Google Trends itself. Only the first five terms are used, and the run says which. Some valid-looking country and time combinations can still fail at Google.

Output reference

Rows come in five shapes, identified by dataType:

Type	Fields in addition to dataType
Timeline	keyword, geo, timeframe, date, dateUtc, timestamp, value, isPartial
Related queries	keyword, geo, timeframe, relatedQuery, kind, value, formattedValue, link
Related topics	keyword, geo, timeframe, topicTitle, topicType, kind, value, formattedValue, link
Regions	keyword, geo, timeframe, resolution, geoName, geoCode, value, plus latitude and longitude for cities
Trending	geo, rank, query, approxTraffic, pubDate, relatedNews

A timeline row from the 2 October 2026 run:

{
  "dataType": "interest_over_time",
  "keyword": "cold brew",
  "geo": "US",
  "timeframe": "today 12-m",
  "date": "Jun 21 – 27, 2026",
  "dateUtc": "2026-06-21",
  "timestamp": "1782000000",
  "value": 100,
  "isPartial": false
}

date is Google's own label. Use dateUtc (YYYY-MM-DD, with the time for 24-hour and 7-day data) to sort or chart; timestamp is the same moment in Unix seconds, as text. isPartial is true for an unfinished interval. Unknown values stay null.

For related data, kind tells top and rising lists apart. Rising values describe growth, not 0-100 interest, and formattedValue keeps labels such as Breakout. link opens the same comparison on Google Trends. For trending items, approxTraffic is Google's rounded label, not an exact count, and relatedNews holds up to five headlines, not articles or links.

Reading the numbers

Interest values are relative scores, not search counts. Zero can mean too little data to report, not zero searches. Requesting 90 days does not guarantee 90 time points, because Google chooses the intervals. Separate runs can be scaled differently, so only compare values from the same run.

Run report

Open Run summary in the Output tab for a readable status of each requested result type. RUN_REPORT in the run's key-value store has the same information for automation. Each type is marked ok (rows returned), empty (no rows and no detected error), failed (a request or parsing error) or skipped (search terms missing).

A run can succeed while one type is empty or failed, so check the report when completeness matters. If every requested type fails, the run fails.

Pricing

$3 per 1,000 rows ($0.003 each), plus a startup fee of $0.05 per GB of memory, at least one per run. The default memory is 1 GB, so most runs pay one startup fee. Every selected result type adds rows. The startup fee applies even when no rows are returned.

Billable unit	Base / Free tier	Bronze (-10%)	Silver (-15%)	Gold, Platinum, Diamond (-20%)
Startup, per GB of memory	$0.05	$0.045	$0.0425	$0.04
1,000 rows	$3.00	$2.70	$2.55	$2.40

Apify applies your tier's price automatically; the Pricing tab shows your rate. Base-price examples:

One run	At the 1 GB default	With 4 GB memory
24 rows	$0.122	$0.272
106 rows (the coffee example)	$0.368	$0.518
1,000 rows	$3.05	$3.20

Some other Trends Actors charge one result for a whole keyword history, so compare the total cost of the same data when choosing a tool.

Maximum cost per run covers both the startup fee and the rows. If the next row would go over it, the Actor stops and says so in the run summary. If a run is restarted, rows already saved are kept and are not exported or charged again; Apify may charge another startup fee for the restart.

Weekly Google Trends report in Google Sheets

Keep a sheet that updates itself every week with the latest interest for your terms:

1. Enter up to five terms, a country and Past 12 months as the time range, and keep only Interest over time under Results to collect.
2. Save it as a task and add a weekly schedule.
3. In the task's Integrations tab, add the Google Sheets Import & Export integration and connect your Google account. Choose replace mode, paste your spreadsheet's ID, and enter {{resource.defaultDatasetId}} as the dataset ID.

The ready-made example Weekly Google Trends report for Google Sheets has step 1 filled in. Every week the sheet then holds the latest 12 months, one row per term and week, ready for a chart. Replace mode fits Trends best: Google rescales each request, so values from different runs should not be mixed in one chart. Keep one task per comparison, for example your brand against two competitors. Three terms over 12 months are about 160 rows: around $0.53 a run, or $2.30 a month, at the base price.

API and recurring workflows

Use the API tab for ready-made code examples, and keep your API token secure. To track terms regularly, save a task, add a schedule, and fetch each run's dataset through the API or your automation tool. Keep the keyword, country, time range and row type with each value. The Actor does not keep history between runs, send alerts or make forecasts.

Use it from an AI agent

This Actor works as a tool in Claude, Cursor and other AI assistants that support MCP, through Apify's MCP server. Add this server and sign in with your Apify account when asked:

https://mcp.apify.com?tools=cleanscrape/google-trends-scraper

Then ask in plain words, for example: "Compare Google Trends interest for "electric bike" and "e-scooter" in Germany over the past 12 months." The assistant runs the Actor in your Apify account and reads the results. The price per result is the same as in Console.

Common questions

Is there an official Google Trends API?

Google offers a separate Trends API alpha through an application process. This Actor reads Google Trends website endpoints and the public trending-searches feed; it does not require access to that alpha.

Is this a pytrends alternative?

Yes. The pytrends repository was archived in April 2025. This Actor handles bounded retries and proxy connections and returns the available results through Apify.

If you already have pytrends code, use trendreq: the same TrendReq methods and DataFrames, running on this Actor. Change the import to from trendreq import TrendReq and set APIFY_TOKEN.

Or call the Actor directly:

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("cleanscrape/google-trends-scraper").call(run_input={
    "searchTerms": ["iced coffee", "cold brew"],
    "dataTypes": ["interest_over_time"],
    "geo": "US",
    "timeframe": "today 12-m",
})
for row in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(row)

Why does the interest only go up to 100?

Google Trends shows relative interest. 100 is the peak for the terms and period you compared, not 100 searches. Keep terms you want to compare in the same run.

How many terms can I compare?

This Actor supports up to five terms per comparison. If you enter more, only the first five are used.

How much does it cost?

$3 per 1,000 rows plus a $0.05 start fee at the default 1 GB of memory. Two terms over 12 months come to about $0.37. See Pricing above.

Support

CleanScrape maintains this Actor for one-off research and recurring workflows. We investigate reported errors, update the Actor when Google changes, and test changes against existing inputs and output formats.

What you see	What to try
No related topics	Expected for many terms; check the run summary.
Keyword results skipped	Add Search terms. Only Trending now works without them.
HTTP 429 or blocked requests	Keep the residential proxy on and try a smaller run later.
Higher cost than expected	Count the rows of every selected result type, and the startup fee per GB of memory.
Fewer time points than expected	Google chose a longer interval for the time range.

If something still looks wrong, open an issue or email contact.cleanscrape@gmail.com with the run ID, a short input example and the result type affected. Never include API tokens or private data.

What worked well, and what could be better? Share your experience in Reviews. Honest feedback is welcome, including anything that fell short. Leaving feedback is optional and does not affect access, pricing or support.

Disclaimer

This Actor is an independent tool developed by CleanScrape. It is not affiliated with, endorsed by, or sponsored by Google. It is not an official Google Trends API. Google, Google Trends and all other trademarks are the property of their respective owners. Brand names are used only to identify supported sources and illustrate usage.

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