Google Trends Scraper — API & Trending Now | $0.50/1k keywords
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from $0.50 / 1,000 results
Google Trends Scraper — API & Trending Now | $0.50/1k keywords
Google Trends without a login or API key, one result per keyword: interest over time, interest by region and top/rising related queries nested in one row for $0.0005. Compare up to 5 terms in any country, time range or category. Plus Trending now per country with traffic and news.
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from $0.50 / 1,000 results
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What does Google Trends Scraper do?
Google Trends Scraper turns Google Trends into data you can export to CSV, Excel or JSON, or pull from the API. Type search terms and get one result per keyword: its interest over time, interest by region and top and rising related queries, all in one row. Or list countries and get what is trending now, with search volume, start time, related searches and news articles. It works as a Google Trends API alternative: no Google account, no API key, no browser.
Typical use cases:
- SEO and content planning: compare keywords on one 0-100 scale, find rising related queries and "Breakout" searches before competitors write about them.
- Market and product research: track the seasonality of hundreds of products over 5 years, see which states or countries search for them most.
- Newsrooms, social teams and AI agents: pull the Trending now list every hour for several countries, with the news articles behind each trend.
It reads only data Google Trends shows publicly to anyone. It does not log in and does not collect personal data.
Why use this Google Trends scraper?
- One result per keyword, $0.0005. A keyword with all three data types (about 50 dates, 50 regions and 50 related queries) is one row and one billed result. 1,000 keywords cost $0.50, platform usage included.
- Summary numbers included. Every keyword row also has
latestValue,averageValue,peakValueandpeakDate, so you can sort 500 keywords without opening a single timeline. - Flat tables when you want them. Switch Output format to one row per data point for spreadsheet-ready rows (one per date, region or related query; each row is billed).
- Reliable from Apify's servers. The Actor handles Google's cookie handshake and rate limits itself (pacing, backoff, and a switch to Apify's datacenter proxy when Google slows it down). Tested at 100% success over 300+ calls through the datacenter proxy.
- Honest results. Every row carries a
status(ok,not_found,error), so you or an AI agent can tell "Google has no data for this term" apart from "could not be read". You pay only forokrows.
What data can Google Trends Scraper extract?
Default: one row per keyword (dataType: search_term):
| Field | Type | Description |
|---|---|---|
searchTerm | string | The keyword (or topic id) |
comparedWith | array | The other terms when keywords were compared on one scale |
geo | string | Location code (US, GB, US-CA) or WORLDWIDE |
timeRange | string | Time range, e.g. today 12-m, or custom 2024-01-01 2024-12-31 |
category | integer | Google Trends category id (0 = all) |
property | string | web, images, news, youtube or froogle (Shopping) |
latestValue | number | Interest (0-100) in the latest complete period |
averageValue | number | Average interest over the range |
peakValue, peakDate | number, string | Highest interest and when it happened |
interestOverTime | array | Every date: {date, value, isPartial} (value 0-100; isPartial = period not finished yet) |
interestByRegion | array | Every region with data: {geoCode, geoName, value} (plus latitude/longitude for cities) |
resolution | string | Region level: COUNTRY, REGION, CITY or DMA |
relatedQueries | object | {top: [{query, value, formattedValue}], rising: [{query, value, formattedValue, isBreakout}]} |
partialError | string | Set only when one requested data type could not be read |
Trending now: one row per trending search (dataType: trending_now):
| Field | Type | Description |
|---|---|---|
title | string | The trending search |
rank | integer | Position in the Trending now list |
approxTraffic | string | Search volume as Google prints it, e.g. 200K+ |
searchVolume | integer | Approximate number of searches |
increasePercent | integer | Rise in searches, percent |
startedAt, endedAt | string | When the trend started / ended (ISO 8601) |
isActive | boolean | Still trending |
trendCategories | array | e.g. Sports, Entertainment |
trendBreakdown | array | The searches Google groups into the trend |
newsArticles | array | {title, url, source, publishedAt} |
Flat format (outputFormat: rows): one row per data point, dataType interest_over_time, interest_by_region or related_queries:
| Field | Type | Description |
|---|---|---|
dataType | string | search_term, interest_over_time, interest_by_region, related_queries or trending_now |
date | string | Interest over time: YYYY-MM-DD, or a UTC timestamp for hourly data |
dateLabel | string | Interest over time: the period as Google labels it (e.g. a week) |
value | number | Interest 0-100; region share for comparisons; related-query score or rise % |
formattedValue | string | The value as Google prints it: 73, 68%, +250%, Breakout |
isPartial | boolean | Interest over time: true for the latest, still incomplete period |
hasData | boolean | Interest over time: false where Google shows no data |
geoCode | string | By region: region code (US-CA, DE, 602 for a metro area) |
regionName | string | By region: country, state, city or metro area |
latitude, longitude | number | By region, city level: coordinates |
rankType | string | Related queries: top or rising |
query | string | Related queries: the related search |
isBreakout | boolean | Related queries: rising more than +5000% |
Every row also has url (the Google Trends page), status, error and scrapedAt.
Result status (tri-state output)
status | Meaning | Billed? |
|---|---|---|
ok | Data was read. | Yes |
not_found | Google Trends answered but has too little search volume for the keyword, or nothing trends with your filters. | No |
error | Google Trends could not be read after retries, or the input was not usable. error says why. | No |
How to use the Google Trends API alternative
- Open the Actor in Apify Console and click Try for free.
- Type Search terms, one per line. To compare terms on one scale, put up to 5 on one line separated by commas (
coffee, tea, matcha). - Pick the Location (empty = worldwide), Time range, and which data to include.
- For Trending now, add country codes under Trending now: countries (search terms can stay empty).
- Click Start. The default input (5 keywords) finishes in about 20 seconds. Open Output or Export as CSV, Excel or JSON.
To automate it, use the API tab (Node.js, Python, curl) or add a Schedule (e.g. Trending now every hour).
How much does it cost to scrape Google Trends?
Pay-per-event pricing; Apify platform usage (compute and proxy) is included, so you pay only these events:
| Event | Price |
|---|---|
| Actor start | $0.005 per run |
Result (status: ok row) | $0.0005 per row ($0.50 per 1,000) |
What counts as one result depends on Output format:
- One row per keyword (default): one result per keyword. Interest over time, interest by region and related queries of a keyword are one row, so one keyword costs $0.0005, and 1,000 keywords cost $0.50. A comparison line such as
coffee, teais one row per keyword (2 results). - One row per data point (
rows): every data point is billed. Each date, region and related query is its own row. One keyword over 12 months with all three data types is about 154 rows = $0.077. Use it only when you need the flat table. - Trending now: one result per trending search. The US list for the past 24 hours is about 370 trends = $0.19; cap it with Maximum rows.
Examples: 5 keywords in one run = $0.005 start + 5 × $0.0005 = $0.0075. 1,000 keywords = $0.005 + $0.50 = $0.505.
Rows with not_found or error are free. Cap spending with Maximum rows and the run's Max total charge.
Input
| Field | Type | Default | Description |
|---|---|---|---|
searchTerms | array | - | One keyword per line; a, b, c on one line compares up to 5 terms |
geo | string | "" (worldwide) | US, GB, US-CA, GB-ENG... |
timeRange | string | today 12-m | now 1-H, now 4-H, now 1-d, now 7-d, today 1-m, today 3-m, today 12-m, today 5-y, all |
startDate, endDate | string | - | Custom range YYYY-MM-DD (overrides timeRange) |
category | integer | 0 | Google Trends category id |
property | string | web | web, images, news, youtube, froogle |
includeInterestOverTime | boolean | true | Interest over time |
includeInterestByRegion | boolean | true | Interest by region |
regionResolution | string | auto | COUNTRY, REGION, CITY, DMA |
includeRelatedQueries | boolean | true | Top and rising related queries |
outputFormat | string | perTerm | perTerm (one row per keyword) or rows (one row per data point) |
trendingGeos | array | - | Country codes for Trending now |
trendingHours | string | 24 | 4, 24, 48, 168 |
trendingCategory | string | 0 | Trending category id (17 = Sports, 18 = Technology...) |
trendingActiveOnly | boolean | false | Only trends that are still active |
trendingNewsPerTrend | integer | 3 | News articles per trend (0-10) |
startUrls | array | one example URL | Google Trends explore or Trending now URLs from your browser |
maxItems | integer | 1000 | Stop after this many rows (keywords in the default format) |
proxyConfiguration | object | off | Optional Apify Proxy (datacenter) |
Example input:
{"searchTerms": ["coffee", "iphone 17, galaxy s26, pixel 11"],"geo": "US","timeRange": "today 5-y","trendingGeos": ["US", "GB"],"trendingHours": "24"}
Output
Download the dataset as JSON, CSV, Excel, XML or HTML. A real row from a run of the default input on the Apify platform (keyword coffee, US, past 12 months; 2026-09-28). This whole row is one result ($0.0005); the arrays are shortened here (the run returned 53 dates, 51 states, 25 top and 25 rising queries):
{"url": "https://trends.google.com/trends/explore?date=today+12-m&geo=US&q=coffee&hl=en-US","status": "ok","scrapedAt": "2026-09-28T19:55:25.761Z","dataType": "search_term","searchTerm": "coffee","geo": "US","timeRange": "today 12-m","category": 0,"property": "web","latestValue": 72,"averageValue": 76.4,"peakValue": 100,"peakDate": "2026-04-12","interestOverTime": [{ "date": "2025-09-28", "value": 66, "isPartial": false },{ "date": "2025-10-05", "value": 60, "isPartial": false },{ "date": "2026-09-20", "value": 72, "isPartial": false },{ "date": "2026-09-27", "value": 71, "isPartial": true }],"interestByRegion": [{ "geoCode": "US-WY", "geoName": "Wyoming", "value": 100 },{ "geoCode": "US-HI", "geoName": "Hawaii", "value": 47 },{ "geoCode": "US-KS", "geoName": "Kansas", "value": 42 }],"resolution": "REGION","relatedQueries": {"top": [{ "query": "coffee near me", "value": 100, "formattedValue": "100" },{ "query": "coffee shop", "value": 91, "formattedValue": "91" }],"rising": [{ "query": "how to remove coffee stain from carpet", "value": 5150, "formattedValue": "Breakout", "isBreakout": true },{ "query": "sports scores today", "value": 4900, "formattedValue": "+4,900%", "isBreakout": false }]}}
A Trending now row from the platform (GB, past 24 hours, 2 news articles per trend), breakdown trimmed:
{"url": "https://trends.google.com/trends/explore?date=now+1-d&geo=GB&q=belgium+vs+france&hl=en-US","status": "ok","scrapedAt": "2026-09-28T19:28:06.057Z","dataType": "trending_now","title": "belgium vs france","rank": 1,"geo": "GB","timeRange": "past 24 hours","approxTraffic": "20K+","searchVolume": 20000,"increasePercent": 1000,"startedAt": "2026-09-28T17:50:00.000Z","isActive": true,"trendCategories": ["Sports"],"trendBreakdown": ["france vs belgium", "france fc", "belgium v france"],"newsArticles": [{"title": "Belgium vs France: UEFA Nations League stats & head-to-head","url": "https://www.bbc.co.uk/sport/football/live/cmzxzevvrd6nt","source": "BBC","publishedAt": "2026-09-28T19:07:30.000Z"},{"title": "Belgium v France, Northern Ireland v Hungary and more: Nations League – live","url": "https://www.theguardian.com/football/live/2026/sep/28/belgium-v-france-northern-ireland-v-hungary-and-more-nations-league-live","source": "The Guardian","publishedAt": "2026-09-28T17:45:00.000Z"}]}
In the flat format (outputFormat: rows) the same keyword comes back as one row per data point, for example {"dataType": "interest_over_time", "searchTerm": "coffee", "date": "2025-09-28", "value": 66, "isPartial": false, ...}, {"dataType": "interest_by_region", "regionName": "Wyoming", "geoCode": "US-WY", "value": 100, ...} and {"dataType": "related_queries", "rankType": "top", "rank": 1, "query": "coffee near me", "value": 100, ...}.
A keyword Google has no data for comes back as one free row: {"status": "not_found", "searchTerm": "...", "error": "Google Trends has too little search volume for \"...\" (US, past 90 days) to show interest over time, related queries."}
Tips
- Put many keywords in one run instead of one run per keyword; the start fee is paid once.
- Sort by
latestValue,averageValueorpeakValueto rank keywords without opening their timelines. - For large runs (hundreds of keywords), turn on Apify Proxy (datacenter) so the calls spread over many IPs.
- Compare keywords on one line (
a, b) when you need them on the same scale; separate lines are each scaled 0-100 on their own.
Limitations
- Google Trends values are relative indexes (0-100), not search counts. Each request is scaled to its own peak, so values from separate runs, terms or regions are not directly comparable unless the terms were compared on one line.
- Google samples the data, so the same request can return slightly different values on different days (for short ranges even minutes apart).
- Related topics are not offered: Google Trends returns an empty list to automated clients. Related queries work.
- Region data for comparisons shows each keyword's share of the region (
formattedValue68%), as on the Google Trends page. City-level data is sparse: many keywords have none at country level (metro areas,DMA, are usually filled). - Trending now volumes (
approxTraffic) are Google's rounded buckets (2K+,200K+). - Very large runs are paced to stay within Google's rate limits, so hundreds of terms take minutes, not seconds.
FAQ
Does Google have a Trends API?
Google offers a Trends API only to selected testers. This Actor reads the same public data the Google Trends website shows and returns it as structured rows.
Is it legal to scrape Google Trends?
Google Trends data is aggregated and anonymous, and this Actor reads only what the public website shows. You are responsible for how you use the output; read the legal notice below and Google's terms of service.
Can I use this Actor from an AI agent or MCP client?
Yes. Call it with {"searchTerms": ["your term"]} or {"trendingGeos": ["US"]}. Every row is self-describing (dataType, status, error), and one row per keyword with summary numbers (latestValue, peakValue) keeps answers short.
Why did I get fewer rows than expected?
Google shows no data for low-volume keywords (you get a free not_found row), regions without enough data are left out of interestByRegion, and the run stops at Maximum rows or your Max total charge.
Can I search a topic instead of a keyword?
Yes. Paste the topic id Google Trends uses in its URLs (for example /m/02vqfm from ...explore?q=%2Fm%2F02vqfm) as a search term, or paste the whole explore URL into Google Trends URLs.
Legal and data-protection notice
This Actor extracts only data that Google Trends publishes publicly; it does not extract private user data such as e-mail addresses, phone numbers, gender or precise location, and it does not log in or circumvent access controls. However, your results could still contain personal data, for example a person's name inside a trending search or a news headline. Personal data is protected by the GDPR in the European Union and by other regulations around the world. You should not scrape personal data unless you have a legitimate reason to do so. If you are unsure whether your reason is legitimate, consult your lawyers. You are responsible for complying with Google's terms of service and applicable law when using the extracted data.
This Actor is an independent tool and is not affiliated with, endorsed by or sponsored by Google LLC. Google and Google Trends are trademarks of Google LLC. All trademarks belong to their respective owners.