# Google Trends Scraper (No Login) (`scrapemint/google-trends-scraper`) Actor Scrape Google Trends for any keyword. Interest over time, interest by region, and related rising and top queries. Filter by country, time range, and category. No login, no API key. Pay per row. - **URL**: https://apify.com/scrapemint/google-trends-scraper.md - **Developed by:** [Ken M](https://apify.com/scrapemint) (community) - **Categories:** Marketing, SEO tools, Business - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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. Actors are written with capital "A". ## 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. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Google Trends Scraper (No Login) Get Google Trends data for any keyword as clean rows: interest over time, interest by region, and related rising and top queries. No login, no API key, no browser. Give it keywords, pick a country and time range, and it returns the same data the Trends UI shows. ### What you get Each keyword produces up to three row types (choose which in `dataTypes`): - `interest_over_time` (1 row per keyword): full `timeline` of dated 0 to 100 values, plus `averageValue`, `peakValue`, `latestValue` - `interest_by_region` (1 row per region): `geoCode`, `geoName`, `value`, highest interest first - `related_query` (1 row per query): `query`, `rank` (`top` or `rising`), `value`, `formattedValue` (rising shows growth like `+250%` or `Breakout`), `link` Every row carries `keyword`, `geo`, `timeRange`, `category`, `property`, and `scrapedAt`. ### Input - `keywords` (one or more terms; each explored on its own 0 to 100 scale) - `geo` (two letter country code, empty = worldwide) - `timeRange` (`now 1-H` to `all`, default past 12 months) - `category` (Google Trends category ID, 0 = all) - `property` (Web, Image, News, YouTube, or Shopping search) - `dataTypes`, `maxRegionsPerKeyword`, `maxRelatedPerKeyword`, `maxRows` ### Example input ```json { "keywords": ["web scraping", "chatgpt"], "geo": "US", "timeRange": "today 12-m" } ```` Find rising searches around a niche worldwide: ```json { "keywords": ["standing desk"], "geo": "", "timeRange": "today 3-m", "dataTypes": ["relatedQueries"] } ``` ### Uses - Keyword research and SEO content planning - Spotting rising product or niche demand before it peaks - Validating market interest by country or region - Tracking brand or competitor search interest over time - Feeding trend signals into dashboards and alerts ### Pricing Pay per row. The first 10 rows of every run are free so you can validate output before you scale up. An interest-over-time series is a single row (the whole timeline is embedded), so a typical keyword costs a few cents. ### Notes - Values are Google's relative 0 to 100 index, scaled per keyword and time range, not absolute search volumes. - Google Trends rate limits by IP. The Actor paces requests and retries with backoff; if you run many keywords back to back and see 429 warnings, supply a residential proxy in `proxyConfiguration`. - Low volume keywords can return an empty timeline or no related lists; that is Google having no data, and no rows means no charge. - Related topics (as opposed to related queries) are not offered because Google does not serve them to keyless sessions. - This Actor reads only public data and never logs in. # Actor input Schema ## `keywords` (type: `array`): One or more search terms to look up on Google Trends. Each keyword is explored on its own, so values are that keyword's own 0 to 100 scale. ## `geo` (type: `string`): Two letter country code, e.g. US, GB, DE, IN. Leave empty for worldwide. ## `timeRange` (type: `string`): How far back to look. ## `category` (type: `integer`): Optional Google Trends category ID to narrow results (0 = all categories). Find IDs in the Trends UI URL after picking a category, e.g. 7 = Finance, 12 = Business & Industrial. ## `property` (type: `string`): Which Google surface to measure. ## `dataTypes` (type: `array`): Which row types to output per keyword. ## `maxRegionsPerKeyword` (type: `integer`): Cap on interest-by-region rows per keyword, highest interest first. ## `maxRelatedPerKeyword` (type: `integer`): Cap on related query rows per list (top and rising are separate lists, Google serves up to 25 each). ## `maxRows` (type: `integer`): Maximum number of rows to return across all keywords. First 10 rows per run are free. ## `proxyConfiguration` (type: `object`): Optional. Google Trends rate limits by IP; if you run many keywords back to back and see 429 warnings, supply a residential proxy here. ## Actor input object example ```json { "keywords": [ "web scraping" ], "geo": "US", "timeRange": "today 12-m", "category": 0, "property": "", "dataTypes": [ "interestOverTime", "interestByRegion", "relatedQueries" ], "maxRegionsPerKeyword": 20, "maxRelatedPerKeyword": 25, "maxRows": 500 } ``` # 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 = { "keywords": [ "web scraping" ], "geo": "US" }; // Run the Actor and wait for it to finish const run = await client.actor("scrapemint/google-trends-scraper").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 = { "keywords": ["web scraping"], "geo": "US", } # Run the Actor and wait for it to finish run = client.actor("scrapemint/google-trends-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "keywords": [ "web scraping" ], "geo": "US" }' | apify call scrapemint/google-trends-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapemint/google-trends-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Google Trends Scraper (No Login)", "description": "Scrape Google Trends for any keyword. Interest over time, interest by region, and related rising and top queries. Filter by country, time range, and category. No login, no API key. Pay per row.", "version": "0.1", "x-build-id": "zgZPeXbJcv72mAXbn" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapemint~google-trends-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapemint-google-trends-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapemint~google-trends-scraper/runs": { "post": { "operationId": "runs-sync-scrapemint-google-trends-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapemint~google-trends-scraper/run-sync": { "post": { "operationId": "run-sync-scrapemint-google-trends-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "keywords" ], "properties": { "keywords": { "title": "Keywords", "type": "array", "description": "One or more search terms to look up on Google Trends. Each keyword is explored on its own, so values are that keyword's own 0 to 100 scale.", "items": { "type": "string" } }, "geo": { "title": "Country", "type": "string", "description": "Two letter country code, e.g. US, GB, DE, IN. Leave empty for worldwide.", "default": "" }, "timeRange": { "title": "Time range", "enum": [ "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" ], "type": "string", "description": "How far back to look.", "default": "today 12-m" }, "category": { "title": "Category ID", "type": "integer", "description": "Optional Google Trends category ID to narrow results (0 = all categories). Find IDs in the Trends UI URL after picking a category, e.g. 7 = Finance, 12 = Business & Industrial.", "default": 0 }, "property": { "title": "Search property", "enum": [ "", "images", "news", "youtube", "froogle" ], "type": "string", "description": "Which Google surface to measure.", "default": "" }, "dataTypes": { "title": "Data to return", "type": "array", "description": "Which row types to output per keyword.", "items": { "type": "string", "enum": [ "interestOverTime", "interestByRegion", "relatedQueries" ], "enumTitles": [ "Interest over time (1 row per keyword)", "Interest by region (1 row per region)", "Related queries (1 row per query)" ] }, "default": [ "interestOverTime", "interestByRegion", "relatedQueries" ] }, "maxRegionsPerKeyword": { "title": "Max regions per keyword", "type": "integer", "description": "Cap on interest-by-region rows per keyword, highest interest first.", "default": 20 }, "maxRelatedPerKeyword": { "title": "Max related per list", "type": "integer", "description": "Cap on related query rows per list (top and rising are separate lists, Google serves up to 25 each).", "default": 25 }, "maxRows": { "title": "Max rows total", "type": "integer", "description": "Maximum number of rows to return across all keywords. First 10 rows per run are free.", "default": 500 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Optional. Google Trends rate limits by IP; if you run many keywords back to back and see 429 warnings, supply a residential proxy here." } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```