Google Trends Scraper: Interest, Regions & Related Queries
Pricing
from $3.00 / 1,000 keyword reports
Get Google Trends data for any keywords: interest over time, interest by region and related queries. Compare keywords on one scale, batch many keywords, countries and time ranges. Fast HTTP, no browser.
You can access the Google Trends Scraper: Interest, Regions & Related Queries programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in API & Integrations in Apify Console.
{ "openapi": "3.0.1", "info": { "version": "0.1", "x-build-id": "m8P0WprcBZ11TRkDr" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/tidyscrape~google-trends-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-tidyscrape-google-trends-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/tidyscrape~google-trends-scraper/runs": { "post": { "operationId": "runs-sync-tidyscrape-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/tidyscrape~google-trends-scraper/run-sync": { "post": { "operationId": "run-sync-tidyscrape-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": "Search terms to get Trends data for, e.g. \"sourdough starter\". Each keyword is one result per geo and timeframe.", "items": { "type": "string" } }, "geos": { "title": "Countries / regions", "type": "array", "description": "Where to measure search interest: 2-letter country codes (US, GB, DE), sub-regions (US-CA, GB-ENG), or an empty entry for worldwide. Each geo is scraped separately.", "default": [ "" ], "items": { "type": "string" } }, "timeframes": { "title": "Time ranges", "type": "array", "description": "One or more of: \"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\" (since 2004), or a custom range \"2024-01-01 2024-12-31\".", "default": [ "today 12-m" ], "items": { "type": "string" } }, "compare": { "title": "Compare keywords on one scale", "type": "boolean", "description": "Put keywords side by side on the same 0-100 scale, like Google Trends' Compare (up to 5 per comparison; more are split into groups of 5). Off = each keyword on its own scale.", "default": false }, "includeRegions": { "title": "Interest by region", "type": "boolean", "description": "Include search interest by sub-region (states, countries...) for each keyword.", "default": true }, "includeRelatedQueries": { "title": "Related queries", "type": "boolean", "description": "Include the top 25 and rising 25 related search queries for each keyword.", "default": true }, "category": { "title": "Category", "minimum": 0, "type": "integer", "description": "Google Trends category id to narrow the meaning of a keyword (0 = all categories). Examples: 71 = Food & Drink, 5 = Computers & Electronics, 7 = Finance.", "default": 0 }, "property": { "title": "Search type", "enum": [ "web", "images", "news", "shopping", "youtube" ], "type": "string", "description": "Which Google search to measure: web search, image search, news search, Google Shopping or YouTube search.", "default": "web" }, "maxConcurrency": { "title": "Parallel sessions", "minimum": 1, "maximum": 10, "type": "integer", "description": "How many keywords to fetch at once, each through its own session. Higher is faster but more likely to be rate-limited by Google.", "default": 3 }, "proxyConfiguration": { "title": "Proxy", "type": "object", "description": "Proxy servers used for requests. Google rate-limits by IP; residential proxies are the most reliable.", "default": { "useApifyProxy": true } } } }, "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 }, "PROXY_UNBLOCKER_UNITS": { "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 }, "PROXY_UNBLOCKER_UNITS": { "type": "integer", "example": 0 } } } } } } } } }}OpenAPI is a standard for designing and describing RESTful APIs, allowing developers to define API structure, endpoints, and data formats in a machine-readable way. It simplifies API development, integration, and documentation.
OpenAPI is effective when used with AI agents and GPTs by standardizing how these systems interact with various APIs, for reliable integrations and efficient communication.
By defining machine-readable API specifications, OpenAPI allows AI models like GPTs to understand and use varied data sources, improving accuracy. This accelerates development, reduces errors, and provides context-aware responses, making OpenAPI a core component for AI applications.
You can download the OpenAPI definitions for Google Trends Scraper: Interest, Regions & Related Queries from the options below:
If you’d like to learn more about how OpenAPI powers GPTs, read our blog post.
You can also check out our other API clients: