# Google Trends Scraper: Interest, Regions, Related & Trending (`cprussin/google-trends`) Actor Google Trends interest over time, by region/metro/city, related queries & topics (top + rising) and trending-now searches. Compare 5+ terms on one scale. Web, News, YouTube, Shopping. - **URL**: https://apify.com/cprussin/google-trends.md - **Developed by:** [Connor Prussin](https://apify.com/cprussin) (community) - **Categories:** SEO tools, Marketing - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 1,000 trend results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event ## What's an Apify Actor? An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md. ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run. For examples already wired to this Actor's own input schema, see the [API](#api) section below. Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`). # README ## Google Trends Scraper: Interest, Regions, Related & Trending **Google Trends Scraper** exports Google Trends data as clean JSON, CSV or Excel. There's no official Google Trends API for most people (the alpha has a waitlist), so this actor reads the same data the trends.google.com website shows: - ✅ **Interest over time** for any search term: minute, hourly, daily, weekly or monthly points from 2004 to now. - ✅ **Interest by region**: countries, states/provinces, **US metro areas (DMA)** or cities. - ✅ **Related queries**, both **Top** and **Rising** (including "Breakout"). **Related topics** too, when Google returns them (see FAQ). - ✅ **Trending now**: the searches trending in a country over the past 4 hours to 7 days, with search volume, % increase, start/end time, category and related queries. - ✅ **Compare more than 5 keywords on one scale.** Google compares at most 5 terms per chart. The actor batches larger lists and repeats your first term in every batch as an anchor, then rescales all terms onto one 0–100 scale (`normalizedValue`). - ✅ Filter by **location**, **timeframe** (presets or custom dates), **category** and **search type**: Web, News, Images, YouTube or Google Shopping. - ✅ Handles Google's rate limits and flaky proxies: switches to a new proxy IP on every failed request (429, captcha, timeout, 5xx), falls back to direct requests when the proxy is down, and caps retry time. - ✅ Pay only for results that contain data. Empty results are free. ### Who uses Google Trends data? - **SEO and content teams**: find rising queries and topics to write about, and check a keyword's seasonality before investing in it. - **Marketers and brand managers**: compare brand vs competitors over time and by region, and pick the regions or metros where to spend ad budget. - **E-commerce and product teams**: spot rising product demand early with Google Shopping and YouTube search interest. - **Investors, analysts and researchers**: use search interest as an alternative-data signal alongside sales, stock or survey data. - **Newsrooms and social media teams**: monitor what's trending right now in any country. - **Data scientists and AI agents**: feed Trends data into models, dashboards or LLM workflows via the Apify API or MCP server. ### How does the Google Trends scraper work? 1. Add search terms (Explore mode) or pick **Trending now**. 2. Choose location, timeframe, category, search type and which datasets you want. 3. The actor calls Google Trends' own web endpoints (explore → widget data), the same way the website does, and returns one dataset item per **search term × dataset**. 4. If a term has too little search volume for a dataset, you still get the item (with `hasData: false`, `rows: []`), and you're not charged for it. ### How do I choose Google Trends terms, regions and timeframes? | Field | Description | Example | | ------------------------- | ---------------------------------------------------------------------------------------------------------------- | ----------------------------- | | `mode` | `explore` (your search terms) or `trendingNow` | `"explore"` | | `searchTerms` | Keywords. Any number; more than 5 are batched automatically, anchored on the first term | `["coffee", "tea", "matcha"]` | | `datasets` | Any of `interestOverTime`, `interestByRegion`, `relatedQueries`, `relatedTopics` | `["interestOverTime"]` | | `geo` | Empty = worldwide, or country `US`, region `US-CA`, metro `US-NY-501` | `"GB"` | | `timeframe` | `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`, `custom` | `"today 5-y"` | | `startDate` / `endDate` | Custom range, `YYYY-MM-DD` (or `YYYY-MM-DDTHH` for hourly data within 7 days) | `"2024-01-01"` | | `category` | Google Trends category ID (0 = all; e.g. 7 Finance, 71 Food & Drink, 20 Sports) | `71` | | `property` | `web`, `news`, `images`, `youtube`, `froogle` (Google Shopping) | `"youtube"` | | `regionResolution` | `auto`, `COUNTRY`, `REGION`, `DMA` (US metros), `CITY` | `"DMA"` | | `includeLowVolumeRegions` | Also return regions without enough data | `false` | | `language` | Interface language for names and labels | `"en-US"` | | `trendingHours` | Trending now window: `4`, `24`, `48` or `168` hours | `"24"` | | `maxTrendingSearches` | Max trending searches to return | `50` | | `proxyConfiguration` | Apify Proxy (on by default; Google rate-limits single IPs quickly) | `{ "useApifyProxy": true }` | Example: five years of YouTube search interest for three brands in the US, by metro area. ```json { "searchTerms": ["nike", "adidas", "puma"], "geo": "US", "timeframe": "today 5-y", "property": "youtube", "datasets": ["interestOverTime", "interestByRegion"], "regionResolution": "DMA" } ``` ### What Google Trends data do you get? Every Explore item has the same fields; `rows` depends on `dataset`. ```json { "dataset": "interestOverTime", "term": "coffee", "geo": "US", "timeframe": "today 12-m", "category": 0, "property": "web", "resolution": null, "comparedWith": ["tea"], "anchorTerm": null, "hasData": true, "rowCount": 53, "rows": [ { "date": "2025-09-28T00:00:00.000Z", "formattedTime": "Sep 28 – Oct 4, 2025", "value": 74, "normalizedValue": 74, "hasData": true, "isPartial": false } ], "exploreUrl": "https://trends.google.com/trends/explore?q=coffee%2Ctea&date=today+12-m&geo=US&hl=en-US" } ``` Row shapes per dataset: - `interestOverTime`: `date` (ISO, UTC), `formattedTime`, `value` (0–100, relative to the highest point among the terms in the same request), `normalizedValue` (0–100 across **all** your terms; see below), `hasData`, `isPartial` (the latest, incomplete period). - `interestByRegion`: `geoCode` (e.g. `US-CA`, DMA code `807`), `geoName`, `value` (0–100), `hasData`, `coordinates` (cities only). - `relatedQueries`: `ranking` (`top` / `rising`), `rank`, `query`, `value`, `formattedValue` (e.g. `"100"`, `"+250%"`, `"Breakout"`), `isBreakout`, `link`. - `relatedTopics`: same as related queries, with `topicId` (Knowledge Graph ID like `/m/02vqfm`), `title` and `topicType` instead of `query`. Trending now items: ```json { "dataset": "trendingNow", "term": "national coffee day", "geo": "US", "timeframe": "past 24 hours", "searchVolume": 100000, "increasePercent": 1000, "startedAt": "2026-09-28T23:00:00.000Z", "endedAt": null, "isActive": true, "categories": ["Food and Drink"], "relatedQueries": ["national coffee day deals", "free coffee today"], "newsArticleCount": 9, "exploreUrl": "https://trends.google.com/trends/explore?q=national+coffee+day&date=now+1-d&geo=US&hl=en-US" } ``` `searchVolume` is Google's rounded lower bound (e.g. 100000 = "100K+"). #### Comparing more than 5 terms Google Trends scales every chart so that its highest point is 100, and it compares at most 5 terms at a time. With 6+ terms the actor sends batches of 5 that all include your **first** term (the anchor). It rescales each batch by the anchor's total interest in it, so `normalizedValue` puts every term on one 0–100 scale. `value` stays exactly what Google returned for that batch. The anchor works best when it's reasonably popular throughout the timeframe. If the anchor has zero interest in a batch, that batch's `normalizedValue` is `null`, and the run log says so. Rescaling rounds Google's integer values, so very small terms lose precision, just as they do on the website. ### How much does it cost to scrape Google Trends? Pay-per-event, only for results with data: | Event | Price | | ------------------------------------------------------------- | ---------- | | Trend result (one term × dataset, or one trending-now search) | **$0.002** | That's **$2 per 1,000 results**. One result holds a whole time series, region table or related list (up to 50 rows), not one row. The default input (2 terms × 3 datasets) costs $0.012. Results without data are free. If you set a **maximum cost per run**, the actor stops cleanly when it reaches it. ### Tips for scraping Google Trends - **Keyword research:** set `datasets: ["relatedQueries"]` and look at rows with `ranking: "rising"`. `isBreakout` marks queries that grew more than 5000%. - **Seasonality:** use `timeframe: "today 5-y"` for weekly data, or `all` for monthly data since 2004. - **Daily data for a long period:** Google returns daily points for ranges up to ~9 months. Use custom `startDate`/`endDate` windows. - **Monitoring:** schedule Trending now every few hours and send new items to Slack, Google Sheets or a webhook with Apify integrations. - **Topics vs search terms:** Google Trends compares exact search terms here. Related topics give you Knowledge Graph IDs (`topicId`) if you need entity-level data. ### Google Trends scraper FAQ **Is this the official Google Trends API?** No. It reads the public data that the trends.google.com website loads. Values are identical to what you see in the browser for the same settings. **Why do values differ between runs?** Google Trends computes values from a sample of searches, so numbers can shift slightly between requests, especially for low-volume terms and short timeframes. Values are always relative (0–100), never absolute search counts. **Do I need a proxy?** Google rate-limits Trends heavily per IP (often after a dozen or so requests). Apify Proxy is enabled by default, and the actor switches IP automatically when it's throttled. Large runs take longer when Google throttles, but they keep going. **Why are some rising queries unrelated to my term?** Rising queries are what Google returns: the terms whose share grew the most among searches containing your term. For broad terms and long timeframes these can be noisy. **Why are related topics empty?** As of September 2026, Google Trends' endpoint returns an empty related-topics list for the requests we tested, so `relatedTopics` is off by default. If you enable it, empty results come back with `hasData: false` and are **not charged**. They fill in automatically if Google serves the data again. **Can I use it through the API or with AI agents?** Yes. Call it through the Apify API, the Apify MCP server or any Apify integration. Pricing is per event only, so agent payments work too. **Disclaimer:** This actor is not affiliated with, endorsed by or sponsored by Google. Google Trends is a trademark of Google LLC. You are responsible for complying with Google's terms when using the data. ### Related actors - [google-ads-transparency](https://apify.com/cprussin/google-ads-transparency): Ads from the Google Ads Transparency Center by advertiser or domain. - [product-hunt-launches](https://apify.com/cprussin/product-hunt-launches): Product Hunt launches, leaderboards, upvotes and makers. - [youtube-transcripts](https://apify.com/cprussin/youtube-transcripts): Captions and transcripts from YouTube videos and channels. # Actor input Schema ## `mode` (type: `string`): Explore = interest over time, by region and related queries/topics for your search terms (like trends.google.com/explore). Trending now = what is trending in a country right now (like trends.google.com/trending). ## `searchTerms` (type: `array`): Keywords to look up (Explore mode). Up to 5 are compared on one scale per Google request; with more, the actor batches them automatically and repeats the FIRST term in every batch so all terms can be put on one scale (see normalizedValue). Pick a reasonably popular first term. ## `datasets` (type: `array`): Which Google Trends data to return for each search term (Explore mode). Each term x dataset is one result. Note: Google currently often returns no related topics; such results are returned empty and not charged. ## `geo` (type: `string`): Empty = worldwide. Otherwise a country code (US, GB, DE, IN, ...), a region (US-CA, GB-ENG) or a US metro (US-NY-501). Trending now needs a country code. ## `timeframe` (type: `string`): Time range. Choose Custom and set start/end date for any range since 2004. Google picks the granularity: minutes for 1-4 hours, hourly for up to 7 days, daily up to ~9 months, weekly up to 5 years, monthly beyond. ## `startDate` (type: `string`): YYYY-MM-DD, or YYYY-MM-DDTHH for hourly data over at most 7 days. Setting it switches the timeframe to custom. ## `endDate` (type: `string`): YYYY-MM-DD (or YYYY-MM-DDTHH). Defaults to today. ## `category` (type: `integer`): Category ID (0 = all). Top-level: 3 Arts & Entertainment, 47 Autos & Vehicles, 44 Beauty & Fitness, 22 Books, 12 Business & Industrial, 5 Computers & Electronics, 7 Finance, 71 Food & Drink, 8 Games, 45 Health, 65 Hobbies, 11 Home & Garden, 13 Internet & Telecom, 958 Jobs & Education, 19 Law & Government, 16 News, 299 Online Communities, 14 People & Society, 66 Pets, 29 Real Estate, 533 Reference, 174 Science, 18 Shopping, 20 Sports, 67 Travel. Sub-category IDs: cat= in Trends URLs. ## `property` (type: `string`): Which Google search to measure. ## `regionResolution` (type: `string`): Level of the interest-by-region breakdown. Auto = countries for worldwide, sub-regions (states) for a country. DMA (metro areas) is US only. ## `includeLowVolumeRegions` (type: `boolean`): Also return regions where Google has too little data (value 0, hasData false). ## `language` (type: `string`): Interface language (hl), e.g. en-US, de, fr, ja. Affects region names, topic titles and date labels. ## `trendingHours` (type: `string`): Trending searches started in the past N hours (Trending now mode). ## `maxTrendingSearches` (type: `integer`): Stop after this many trending searches (Trending now mode). Each is one result. ## `proxyConfiguration` (type: `object`): Google Trends rate-limits IP addresses after a handful of requests. Apify Proxy is strongly recommended; the actor switches to a new IP whenever Google returns 429. ## Actor input object example ```json { "mode": "explore", "searchTerms": [ "coffee", "tea" ], "datasets": [ "interestOverTime", "interestByRegion", "relatedQueries" ], "geo": "US", "timeframe": "today 12-m", "category": 0, "property": "web", "regionResolution": "auto", "includeLowVolumeRegions": false, "language": "en-US", "trendingHours": "24", "maxTrendingSearches": 50, "proxyConfiguration": { "useApifyProxy": true } } ``` # Actor output Schema ## `results` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "searchTerms": [ "coffee", "tea" ], "datasets": [ "interestOverTime", "interestByRegion", "relatedQueries" ], "geo": "US", "timeframe": "today 12-m", "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("cprussin/google-trends").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "searchTerms": [ "coffee", "tea", ], "datasets": [ "interestOverTime", "interestByRegion", "relatedQueries", ], "geo": "US", "timeframe": "today 12-m", "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("cprussin/google-trends").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}") for item in client.dataset(run.default_dataset_id).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "searchTerms": [ "coffee", "tea" ], "datasets": [ "interestOverTime", "interestByRegion", "relatedQueries" ], "geo": "US", "timeframe": "today 12-m", "proxyConfiguration": { "useApifyProxy": true } }' | apify call cprussin/google-trends --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,cprussin/google-trends" } } } ``` The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer ` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations). ## OpenAPI specification Download the OpenAPI definition: https://api.apify.com/v2/actors/W6Y8cQFpfQEH2unYT/builds/V77PuXa4aK6y7grxz/openapi.json