# Google Trends Scout — Demand & Interest Over Time (`agency-shift/google-trends-scout`) Actor Scout trending topics and search demand shifts on Google Trends. Track real-time interest by keyword, region, and time horizon. Essential for SEO researchers, content strategists, and indie hackers validating demand. - **URL**: https://apify.com/agency-shift/google-trends-scout.md - **Developed by:** [Valdeir Lima](https://apify.com/agency-shift) (community) - **Categories:** SEO tools, News, AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN 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 — Demand & Trending Searches **Scrape Google Trends** to validate demand. Get **interest over time** for any keyword and the **daily trending searches** for any country. Use it to spot **rising niches, seasonal demand and breakout topics** before they peak — for SEO, content, product and market research. ### What this Google Trends scraper does - **Interest over time** — relative search interest (0–100) for keywords, with an average and a recent-trend percentage - **Daily trending** — the top trending searches by country, with approximate traffic - Localized by **geo** (US, DE, FR, GB, BR…) > Reliability note: the **daily** trending mode is robust. The **interest-over-time** mode depends on Google's heavily rate-limited endpoint — enable `useProxy` (residential) and expect occasional retries. ### Use cases - **Demand validation** — is interest in a niche rising or fading? - **Seasonality** — find the best months for a product or campaign - **Trend spotting** — catch breakout topics from daily trending searches - **Geo research** — compare demand across countries for geo-expansion - **Content calendars** — plan around rising search interest ### Input | Field | Type | Default | Description | |---|---|---|---| | `mode` | string | `interest` | `interest` (over time) or `daily` (trending) | | `keywords` | array | — | Keywords to measure (interest mode) | | `geo` | string | `US` | Country code; empty = worldwide | | `timeframe` | string | `today 12-m` | e.g. `today 3-m`, `now 7-d` | | `useProxy` | boolean | `true` | Residential proxy (recommended) | #### Example input ```json { "mode": "interest", "keywords": ["ai agents"], "geo": "US", "timeframe": "today 12-m" } ```` ### Output ```json { "keyword": "ai agents", "geo": "US", "avgInterest": 62.4, "recentTrendPct": 38, "points": [{ "date": "Jun 2025", "value": 41 }] } ``` ### FAQ **Does it need an API key?** No. **Why use a proxy?** Google Trends blocks datacenter IPs; residential proxy is needed for interest-over-time. **Which mode is most reliable?** `daily` trending. `interest` works but Google rate-limits it. **Can I compare countries?** Yes — run per `geo` and compare the results. # Actor input Schema ## `mode` (type: `string`): interest = interest-over-time for keywords; daily = trending searches by geo. ## `keywords` (type: `array`): Search terms to measure (interest mode). ## `geo` (type: `string`): Country code (US, DE, FR, GB, BR...). Empty = worldwide. ## `timeframe` (type: `string`): e.g. 'today 12-m', 'today 3-m', 'now 7-d'. interest mode only. ## `useProxy` (type: `boolean`): Route through Apify Proxy (recommended — Google often blocks datacenter IPs). Uses credit. ## Actor input object example ```json { "mode": "interest", "keywords": [ "ai agents" ], "geo": "US", "timeframe": "today 12-m", "useProxy": true } ``` # 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": [ "ai agents" ], "geo": "US" }; // Run the Actor and wait for it to finish const run = await client.actor("agency-shift/google-trends-scout").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": ["ai agents"], "geo": "US", } # Run the Actor and wait for it to finish run = client.actor("agency-shift/google-trends-scout").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": [ "ai agents" ], "geo": "US" }' | apify call agency-shift/google-trends-scout --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=agency-shift/google-trends-scout", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Google Trends Scout — Demand & Interest Over Time", "description": "Scout trending topics and search demand shifts on Google Trends. Track real-time interest by keyword, region, and time horizon. Essential for SEO researchers, content strategists, and indie hackers validating demand.", "version": "0.0", "x-build-id": "CBfosvdtgb6tVt28r" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/agency-shift~google-trends-scout/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-agency-shift-google-trends-scout", "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/agency-shift~google-trends-scout/runs": { "post": { "operationId": "runs-sync-agency-shift-google-trends-scout", "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/agency-shift~google-trends-scout/run-sync": { "post": { "operationId": "run-sync-agency-shift-google-trends-scout", "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": [ "mode" ], "properties": { "mode": { "title": "Mode", "enum": [ "interest", "daily" ], "type": "string", "description": "interest = interest-over-time for keywords; daily = trending searches by geo.", "default": "interest" }, "keywords": { "title": "Keywords", "type": "array", "description": "Search terms to measure (interest mode).", "items": { "type": "string" } }, "geo": { "title": "Geo (ISO country)", "type": "string", "description": "Country code (US, DE, FR, GB, BR...). Empty = worldwide." }, "timeframe": { "title": "Timeframe", "type": "string", "description": "e.g. 'today 12-m', 'today 3-m', 'now 7-d'. interest mode only.", "default": "today 12-m" }, "useProxy": { "title": "Use Apify Proxy", "type": "boolean", "description": "Route through Apify Proxy (recommended — Google often blocks datacenter IPs). Uses credit.", "default": 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 } } }, "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 } } } } } } } } } } ```