# Google Trends Scraper (`scrapesmith/google-trends-scraper`) Actor Extract Google Trends data for any keyword — interest over time, related queries, regional interest (250+ countries), and daily trending searches. Custom date ranges, 100+ categories, minute-level granularity. No browser, no proxy. - **URL**: https://apify.com/scrapesmith/google-trends-scraper.md - **Developed by:** [Scrape Smith](https://apify.com/scrapesmith) (community) - **Categories:** Developer tools, SEO tools, Automation - **Stats:** 0 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.50 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## 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 — Interest Over Time, Related Queries & Trending Searches Extract structured data from Google Trends for any keyword, any country, any time period — from the last hour to all time (2004–present). No browser, no proxy, no login required. Supports keyword analysis, keyword comparison, regional breakdowns across 250+ countries, related query discovery, and real-time daily trending searches with news articles. --- ### Why This Scraper? - **3,000 results in 18 seconds** for 20 keywords — the fastest Google Trends scraper on Apify - **No browser, no proxy** — runs on 256 MB, 16x less memory than alternatives - **Custom date ranges** — not just presets, any `YYYY-MM-DD` to `YYYY-MM-DD` - **250+ countries** — worldwide regional breakdown or drill down to individual states - **Minute-level granularity** — hourly data has per-minute precision - **Flat, CSV-ready rows** — no nested blobs, every data point is its own row --- ### What Data Do You Get? | Output Type | Fields | Description | |---|---|---| | **Interest Over Time** | 10 fields | Time-series of search interest (0–100 scale) with date, value, partial data flag | | **Related Queries** | 10 fields | Top and rising search queries with relevance scores and growth percentages | | **Regional Interest** | 8 fields | Per-country or per-state breakdown of search interest with geo codes | | **Daily Trending** | 14 fields | Real-time trending searches with traffic estimates, news articles, and images | --- ### Input ```json { "mode": "keyword", "keywords": ["bitcoin", "ethereum", "solana"], "geo": "US", "timeRange": "today 12-m", "category": 0, "includeRelatedQueries": true, "includeRegionalInterest": true, "maxResults": 5000 } ```` | Parameter | Type | Default | Description | |---|---|---|---| | `mode` | string | `keyword` | `keyword` for search interest data, `trending` for daily trending searches | | `keywords` | string\[] | — | Keywords to analyze. Up to 5 compared together; more than 5 chunked automatically | | `geo` | string | `US` | Country code (US, GB, DE, IN, etc.). Leave empty for worldwide (250+ countries) | | `timeRange` | string | `today 12-m` | Time period — presets or custom `YYYY-MM-DD YYYY-MM-DD` range | | `category` | integer | `0` | Category filter (0 = all). Finance = 7, Sports = 16, Health = 13, Tech = 5 | | `includeRelatedQueries` | boolean | `true` | Include top and rising related search queries | | `includeRegionalInterest` | boolean | `true` | Include per-region interest breakdown | | `maxResults` | integer | `5000` | Maximum total result items | #### Time Range Options | Value | Period | Granularity | |---|---|---| | `now 1-H` | Past hour | Per-minute (~58 points) | | `now 4-H` | Past 4 hours | Per-minute | | `now 1-d` | Past day | 8-minute intervals | | `now 7-d` | Past 7 days | Hourly (~169 points) | | `today 1-m` | Past 30 days | Daily | | `today 3-m` | Past 90 days | Daily | | `today 12-m` | Past 12 months | Weekly (~53 points) | | `today 5-y` | Past 5 years | Weekly (~261 points) | | `all` | 2004–present | Monthly (~270 points) | | `2024-01-01 2024-12-31` | Custom range | Automatic | *** ### Sample Output #### Interest Over Time ```json { "type": "interest_over_time", "keyword": "bitcoin", "geo": "US", "timeRange": "today 12-m", "date": "2026-06-22T00:00:00Z", "formattedDate": "Jun 22, 2026", "value": 78, "formattedValue": "78", "isPartial": false, "hasData": true } ``` #### Related Query ```json { "type": "related_query", "keyword": "bitcoin", "geo": "US", "timeRange": "today 12-m", "rankType": "rising", "rank": 1, "query": "bitcoin etf", "queryLink": "https://www.google.com/search?q=bitcoin+etf", "queryValue": 4250, "queryFormattedValue": "+4,250%" } ``` #### Regional Interest ```json { "type": "regional_interest", "keyword": "bitcoin", "geo": "worldwide", "timeRange": "today 12-m", "geoName": "El Salvador", "geoCode": "SV", "value": 100, "formattedValue": "100" } ``` #### Trending Search ```json { "type": "trending_search", "geo": "US", "trendTitle": "Bitcoin ETF", "approxTraffic": "500K+", "approxTrafficNum": 500000, "pubDate": "Sat, 28 Jun 2026 10:00:00 -0700", "newsTitle": "Bitcoin ETF sees record inflows", "newsUrl": "https://...", "newsSource": "Reuters" } ``` *** ### How Fast Is It? | Scenario | Results | Time | |---|---|---| | 1 keyword, 12 months | ~154 | ~8 seconds | | 5 keywords compared, 12 months | ~770 | ~8 seconds | | 20 keywords, 12 months | ~3,000 | ~27 seconds | | 1 keyword, all time (2004–present) | ~371 | ~8 seconds | | 1 keyword, past hour (minute-level) | ~149 | ~10 seconds | | Trending searches, 1 country | ~30 | ~8 seconds | No browser, no proxy, no Puppeteer — runs on 256 MB. *** ### Use Cases - **SEO & content strategy** — find what people are searching for, discover rising queries before they peak, identify seasonal trends - **Market research** — compare brand interest over time, benchmark against competitors, track industry trends across countries - **Keyword research** — discover related search terms you didn't know existed, find "Breakout" queries growing 5,000%+ - **Investment signals** — monitor search interest in stocks, crypto, commodities — search spikes often precede price moves - **Academic research** — collect longitudinal search interest data from 2004 to present for any topic - **PR & media monitoring** — track daily trending searches by country, see what's making news in real time - **Product launches** — measure launch impact by tracking search interest before and after release dates - **Seasonal planning** — understand when demand peaks for your products or services across different regions *** ### Supported Countries Works with any ISO 3166-1 alpha-2 country code: US, GB, DE, FR, IN, JP, CA, AU, BR, and 200+ more. Leave `geo` empty for **worldwide data** — returns interest broken down by all 250+ countries instead of states. *** ### FAQ **How is this different from the Google Trends website?** The website shows charts you can't export. This scraper returns every data point as structured JSON, CSV, or Excel — ready for analysis, dashboards, or automation. **Can I compare multiple keywords?** Yes. Provide up to 5 keywords and they're analyzed together on the same 0–100 relative scale. More than 5 keywords are automatically split into comparison groups and processed in parallel. **Can I use custom date ranges?** Yes. Set `timeRange` to any `YYYY-MM-DD YYYY-MM-DD` range, like `2024-01-01 2024-06-30` for the first half of 2024. **What does the 0–100 value mean?** Google normalizes search interest to a relative scale where 100 = peak popularity within your selected time range and region. It's not absolute search volume — Google doesn't expose that. **What does "Breakout" mean in related queries?** A query with "Breakout" status grew by more than 5,000% in the selected period. These are typically new or suddenly viral topics — valuable for trend detection. **Does this require a Google account?** No. All data comes from public Google Trends endpoints. No login, no API key, no authentication. **How far back does the data go?** All the way to January 2004 using the `all` time range. That's 20+ years of monthly search interest data for any keyword. **Can I get data for multiple countries?** Use `geo: ""` (empty) for worldwide data covering 250+ countries. Or run the scraper once per country for per-state granularity. **What are the category filters?** Google Trends supports 100+ category IDs. Common ones: Finance (7), Health (13), Sports (16), Technology (5), Shopping (19), News (29). Category 0 means all categories. **Is there a free trial?** Yes. Every run includes free results so you can verify the data quality before committing to a paid plan. **What output formats are supported?** JSON, CSV, Excel, XML, and HTML table — all available directly from the Apify dataset after each run. # Actor input Schema ## `mode` (type: `string`): What to scrape: 'keyword' for interest-over-time & related queries per keyword, 'trending' for daily trending searches by country. ## `keywords` (type: `array`): List of search terms to get trend data for (used in 'keyword' mode). Up to 5 per run (Google Trends limit). ## `geo` (type: `string`): ISO 3166-1 alpha-2 country code (e.g. US, GB, DE, IN). Leave empty for worldwide data. ## `timeRange` (type: `string`): Time range. Presets: '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: 'YYYY-MM-DD YYYY-MM-DD' (e.g. '2024-01-01 2024-12-31'). ## `category` (type: `integer`): Google Trends category ID to filter results. 0 = All categories (default). See README for common category IDs. ## `includeRelatedQueries` (type: `boolean`): Fetch rising and top related queries for each keyword. ## `includeRelatedTopics` (type: `boolean`): Fetch rising and top related topics (entity-based). Google may return empty data for some keywords — this is a known API limitation. ## `includeRegionalInterest` (type: `boolean`): Fetch per-region (state/country) interest breakdown for each keyword. ## `maxResults` (type: `integer`): Maximum total result items to output. Free plan is capped at 25. ## Actor input object example ```json { "mode": "keyword", "keywords": [ "python", "javascript", "typescript" ], "geo": "US", "timeRange": "today 12-m", "category": 0, "includeRelatedQueries": true, "includeRelatedTopics": false, "includeRegionalInterest": true, "maxResults": 5000 } ``` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("scrapesmith/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 = {} # Run the Actor and wait for it to finish run = client.actor("scrapesmith/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 '{}' | apify call scrapesmith/google-trends-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapesmith/google-trends-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Google Trends Scraper", "description": "Extract Google Trends data for any keyword — interest over time, related queries, regional interest (250+ countries), and daily trending searches. Custom date ranges, 100+ categories, minute-level granularity. No browser, no proxy.", "version": "0.0", "x-build-id": "MnXB5hXWyfdaQlttU" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapesmith~google-trends-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapesmith-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/scrapesmith~google-trends-scraper/runs": { "post": { "operationId": "runs-sync-scrapesmith-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/scrapesmith~google-trends-scraper/run-sync": { "post": { "operationId": "run-sync-scrapesmith-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", "properties": { "mode": { "title": "Mode", "enum": [ "keyword", "trending" ], "type": "string", "description": "What to scrape: 'keyword' for interest-over-time & related queries per keyword, 'trending' for daily trending searches by country.", "default": "keyword" }, "keywords": { "title": "Keywords", "type": "array", "description": "List of search terms to get trend data for (used in 'keyword' mode). Up to 5 per run (Google Trends limit).", "items": { "type": "string" } }, "geo": { "title": "Country / Region (geo)", "type": "string", "description": "ISO 3166-1 alpha-2 country code (e.g. US, GB, DE, IN). Leave empty for worldwide data.", "default": "US" }, "timeRange": { "title": "Time Range", "type": "string", "description": "Time range. Presets: '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: 'YYYY-MM-DD YYYY-MM-DD' (e.g. '2024-01-01 2024-12-31').", "default": "today 12-m" }, "category": { "title": "Category", "type": "integer", "description": "Google Trends category ID to filter results. 0 = All categories (default). See README for common category IDs.", "default": 0 }, "includeRelatedQueries": { "title": "Include Related Queries", "type": "boolean", "description": "Fetch rising and top related queries for each keyword.", "default": true }, "includeRelatedTopics": { "title": "Include Related Topics (experimental)", "type": "boolean", "description": "Fetch rising and top related topics (entity-based). Google may return empty data for some keywords — this is a known API limitation.", "default": false }, "includeRegionalInterest": { "title": "Include Regional Interest Breakdown", "type": "boolean", "description": "Fetch per-region (state/country) interest breakdown for each keyword.", "default": true }, "maxResults": { "title": "Max Results", "minimum": 1, "type": "integer", "description": "Maximum total result items to output. Free plan is capped at 25.", "default": 5000 } } }, "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 } } } } } } } } } } ```