# Google Trends Scraper - Interest, Related Queries, Trending (`renzomacar/google-trends-scraper`) Actor - **URL**: https://apify.com/renzomacar/google-trends-scraper.md - **Developed by:** [Renzo Madueno](https://apify.com/renzomacar) (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 $3.00 / 1,000 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/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, Related Queries, Trending Pull real **Google Trends** data into clean, structured JSON, CSV, or Excel - without a browser, without flaky screenshots, and without writing your own token-handling code. This scraper talks directly to the same data endpoints that power trends.google.com, so it is fast, cheap, and reliable. Track how a keyword's popularity moves over time, see exactly which states or countries search for it most, discover the **related queries and topics** people search alongside it (including breakout "rising" terms), and grab the live **Trending now** list for any country. One run, one dataset, everything you need for SEO, content planning, and market research. ### Features Every bullet below is a real query this actor answers: - **"How has interest in `bitcoin` changed over the last 12 months?"** - Interest over time returns a clean timeline (0-100 relative popularity) for each date, with partial-period flags so you know which data points are still settling. - **"Compare `chatgpt` vs `claude` vs `gemini` in one chart"** - Multi-keyword comparison done right. Pass up to 5 keywords and get one aligned row per date with a value for each keyword - the thing most Google Trends scrapers get wrong. - **"Which US states search for `electric cars` the most?"** - Interest by region breaks demand down by country, state, or metro, ranked and normalized so you can spot geographic hotspots. - **"What do people search right after `protein powder`?"** - Related queries returns both **top** (consistently popular) and **rising** (fast-growing / breakout) searches, each with a relative value and a direct Trends link. - **"What topics are associated with `marathon`?"** - Related topics surfaces the entities and themes Google clusters around your keyword, split into top and rising. - **"What is trending in the US / UK / India right now?"** - Trending now returns today's surging searches with approximate traffic volume and the news articles driving each spike. - **No browser, no Puppeteer** - pure HTTP against Google's internal JSON API. It handles the `)]}'` anti-hijacking prefix, NID cookie warm-up, token negotiation, retries, and proxy rotation for you. - **Geo + timeframe + category control** - scope any query by country/region, by time window (past hour to 2004-present), and by Google Trends category. ### Use cases **SEO & keyword research.** Find rising search terms before your competitors do. Pull related queries for a seed keyword, filter for "rising / breakout," and you have a content calendar grounded in real demand - not guesswork. Combine interest-over-time with seasonality to time your publishing. **Content & social planning.** Hook into Trending now for a country and turn surging searches (plus the news articles behind them) into timely posts, newsletters, or videos while the topic is hot. **Market & product research.** Compare brand vs competitor interest, validate demand for a new product across regions, or measure whether a campaign actually moved the needle by watching the interest curve before and after launch. **Investing & trend monitoring.** Track attention on tickers, technologies, or themes over 5-year windows and break interest down by geography. ### Input ```json { "keywords": ["bitcoin", "ethereum"], "dataTypes": ["interest_over_time", "interest_by_region", "related_queries", "related_topics"], "geo": "US", "timeframe": "today 12-m", "category": 0, "trendingGeo": "US", "hl": "en-US", "requestDelayMs": 1500 } ```` | Field | Type | Description | |---|---|---| | `keywords` | array | Up to 5 keywords to analyze / compare. Required for interest & related modes. | | `dataTypes` | array | Any of `interest_over_time`, `interest_by_region`, `related_queries`, `related_topics`, `trending_now`. | | `geo` | string | Country/region code (`US`, `GB`, `PE`, `US-CA`). Empty = Worldwide. | | `timeframe` | string | `now 1-H`, `now 7-d`, `today 3-m`, `today 12-m`, `today 5-y`, `all`, or a custom `YYYY-MM-DD YYYY-MM-DD` range. | | `category` | integer | Google Trends category ID (0 = all). | | `trendingGeo` | string | Country code used for `trending_now`. | | `requestDelayMs` | integer | Pause between calls; raise it if you hit rate limits. | ### Output Each dataset item carries a `dataType` so mixed runs stay easy to parse. Interest over time: ```json { "dataType": "interest_over_time", "geo": "US", "date": "Jun 8, 2025", "values": [{ "keyword": "bitcoin", "value": 29 }], "isPartial": false } ``` Related queries: ```json { "dataType": "related_queries", "keyword": "bitcoin", "rankType": "rising", "query": "how to buy bitcoin safely", "value": 12550, "formattedValue": "Breakout", "link": "https://trends.google.com/trends/explore?q=how+to+buy+bitcoin+safely" } ``` Trending now: ```json { "dataType": "trending_now", "geo": "US", "rank": 1, "query": "delta airlines", "approxTraffic": "200+", "relatedNews": [{ "title": "...", "url": "...", "source": "..." }] } ``` ### Pricing This actor uses **pay per event**: a small fee per run start plus a tiny fee per result item. You only pay for what you pull - a single keyword's yearly timeline costs a fraction of a cent. No monthly subscription, no Google Trends API key required. ### FAQ **Does Google Trends have an official API?** No public one. This actor uses the same internal JSON endpoints the website itself calls, handling tokens and cookies automatically. **Can I compare multiple keywords?** Yes - up to 5 at once, with values aligned per date/region so comparisons are apples-to-apples. **What do the values mean?** Google Trends numbers are *relative* (0-100), where 100 is peak interest within your query's scope, not absolute search counts. For related/rising, large numbers (or "Breakout") indicate fast growth. **Why is some related-topic data empty?** Google legitimately returns no rising/top topics for some keyword + geo + timeframe combinations. The actor reports this as "no data" rather than failing. **I'm getting rate-limited.** Increase `requestDelayMs` and the run will route through residential proxies automatically. The actor retries and rotates IPs on blocks. **What timeframes are supported?** Everything from `now 1-H` (last hour) to `all` (2004-present), plus custom date ranges. # Actor input Schema ## `keywords` (type: `array`): Up to 5 keywords to analyze and compare. Required for interest/related data types. ## `dataTypes` (type: `array`): Which Google Trends datasets to collect. ## `geo` (type: `string`): Two-letter country code (e.g. US, GB, PE) or region code (e.g. US-CA). Leave empty for Worldwide. ## `timeframe` (type: `string`): Time range. Examples: 'now 1-H', 'now 7-d', 'today 1-m', 'today 3-m', 'today 12-m', 'today 5-y', 'all', or a custom range like '2023-01-01 2023-12-31'. ## `category` (type: `integer`): Google Trends category ID to narrow the topic (0 = All categories). E.g. 7 = Finance, 5 = Computers & Electronics. ## `trendingGeo` (type: `string`): Country code for the 'Trending now' data type (e.g. US, GB, PE, IN). ## `hl` (type: `string`): UI language for labels (e.g. en-US, es-419). ## `requestDelayMs` (type: `integer`): Pause between Google Trends API calls. Higher values reduce rate-limit blocks. ## Actor input object example ```json { "keywords": [ "bitcoin" ], "dataTypes": [ "interest_over_time", "related_queries" ], "geo": "US", "timeframe": "today 12-m", "category": 0, "trendingGeo": "US", "hl": "en-US", "requestDelayMs": 1500 } ``` # Actor output Schema ## `results` (type: `string`): All result items as JSON. # 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": [ "bitcoin" ] }; // Run the Actor and wait for it to finish const run = await client.actor("renzomacar/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": ["bitcoin"] } # Run the Actor and wait for it to finish run = client.actor("renzomacar/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": [ "bitcoin" ] }' | apify call renzomacar/google-trends-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=renzomacar/google-trends-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Google Trends Scraper - Interest, Related Queries, Trending", "version": "0.1", "x-build-id": "VOdoY3tbyYc8NQmN4" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/renzomacar~google-trends-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-renzomacar-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/renzomacar~google-trends-scraper/runs": { "post": { "operationId": "runs-sync-renzomacar-google-trends-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/renzomacar~google-trends-scraper/run-sync": { "post": { "operationId": "run-sync-renzomacar-google-trends-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "dataTypes" ], "properties": { "keywords": { "title": "Keywords", "maxItems": 5, "type": "array", "description": "Up to 5 keywords to analyze and compare. Required for interest/related data types.", "items": { "type": "string" } }, "dataTypes": { "title": "Data types", "type": "array", "description": "Which Google Trends datasets to collect.", "items": { "type": "string", "enum": [ "interest_over_time", "interest_by_region", "related_queries", "related_topics", "trending_now" ], "enumTitles": [ "Interest over time", "Interest by region", "Related queries", "Related topics", "Trending now" ] }, "default": [ "interest_over_time", "related_queries" ] }, "geo": { "title": "Geo (country/region code)", "type": "string", "description": "Two-letter country code (e.g. US, GB, PE) or region code (e.g. US-CA). Leave empty for Worldwide.", "default": "US" }, "timeframe": { "title": "Timeframe", "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": "Time range. Examples: 'now 1-H', 'now 7-d', 'today 1-m', 'today 3-m', 'today 12-m', 'today 5-y', 'all', or a custom range like '2023-01-01 2023-12-31'.", "default": "today 12-m" }, "category": { "title": "Category ID", "minimum": 0, "type": "integer", "description": "Google Trends category ID to narrow the topic (0 = All categories). E.g. 7 = Finance, 5 = Computers & Electronics.", "default": 0 }, "trendingGeo": { "title": "Trending Now country", "type": "string", "description": "Country code for the 'Trending now' data type (e.g. US, GB, PE, IN).", "default": "US" }, "hl": { "title": "Language", "type": "string", "description": "UI language for labels (e.g. en-US, es-419).", "default": "en-US" }, "requestDelayMs": { "title": "Delay between requests (ms)", "minimum": 0, "maximum": 10000, "type": "integer", "description": "Pause between Google Trends API calls. Higher values reduce rate-limit blocks.", "default": 1500 } } }, "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 } } } } } } } } } } ```