# Google Trends Opportunity Radar (`signalcrawl/google-trends-opportunity-radar`) Actor Find rising Google Trends topics by country with traffic floors, keyword matches, trend scores, categories, and content/SEO action notes. - **URL**: https://apify.com/signalcrawl/google-trends-opportunity-radar.md - **Developed by:** [SignalCrawl](https://apify.com/signalcrawl) (community) - **Categories:** SEO tools, Automation, AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 1 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 Opportunity Radar Find rising Google Trends topics by country and turn them into action-ready SEO, content, ecommerce, and market-research opportunities. This Actor uses Google's public daily trending-search RSS feed, which is more stable than the fragile Google Trends widget endpoints that often return rate limits. It returns clean trend records with traffic floors, categories, keyword matches, opportunity scores, content angles, and action notes. ### Why Use This Actor Raw trend lists are not enough. Users need to know what to act on. This Actor helps you: - Monitor trending searches across countries. - Spot topics matching your niche keywords. - Prioritize trends with traffic, freshness, and category scores. - Generate content, SEO, social, product, or market-research angles. - Feed daily trend alerts into dashboards, agents, Slack, Notion, Airtable, or content workflows. ### Good For | User | Workflow | |---|---| | SEO teams | Find rising keywords before competitors react. | | Content marketers | Build trend-based article, video, and newsletter ideas. | | Ecommerce sellers | Watch product and shopping demand spikes. | | Agencies | Monitor client markets by country. | | Indie builders | Discover fast-moving niches and content angles. | | AI agents | Pull structured trend opportunities with stable fields. | ### Input Example ```json { "geos": ["US", "GB", "FR"], "keywords": ["ai", "chatgpt", "iphone", "crypto", "jobs", "travel", "stock"], "maxTrendsPerGeo": 10, "minTraffic": 0, "freshnessHours": 168, "includeLowSignal": true } ```` ### Output Each dataset item contains: ```json { "platform": "google_trends_rss", "geo": "US", "title": "openai stock", "category": "ai_tools", "approxTraffic": "20K+", "trafficFloor": 20000, "publishedAt": "2026-05-22T13:50:00+00:00", "ageHours": 2, "keywordMatches": ["openai"], "trendScore": 73, "opportunityLabel": "WATCH_NOW", "contentAngle": "Create comparison, tutorial, or alternatives content around 'openai stock' while search intent is rising.", "actionNote": "Good watchlist item: validate search intent and schedule recurring monitoring.", "sourceUrl": "https://trends.google.com/trending/rss?geo=US", "dedupeKey": "...", "scrapedAt": "2026-05-22T13:55:00+00:00" } ``` ### Notes And Limitations - This Actor is optimized for stable daily trending-search discovery. - It does not currently return full historical interest-over-time charts because the Google Trends widget API is rate-limited and less reliable. - Approximate traffic is a floor from Google Trends, such as `500+`, `20K+`, or `1M+`. - Use the output as a discovery and monitoring layer, then validate strong trends with SERP, Reddit, YouTube, ads, or product data. ### Local Development ```powershell apify run --purge --input-file examples\cloud-smoke.json python tests\qa_harness.py ``` # Actor input Schema ## `geos` (type: `array`): Google Trends country codes to monitor, for example US, GB, FR, DE, CA. ## `keywords` (type: `array`): Optional keywords used to tag and score trends that match your niche. ## `maxTrendsPerGeo` (type: `integer`): Maximum number of trend records to save for each country. ## `minTraffic` (type: `integer`): Keep only trends with an approximate traffic floor at or above this value. Use 0 to disable. ## `freshnessHours` (type: `integer`): Keep trends published in the last N hours when dates are available. Use 0 to disable. ## `includeLowSignal` (type: `boolean`): If false, only saves trends with keyword matches, high traffic, or stronger opportunity labels. ## Actor input object example ```json { "geos": [ "US" ], "keywords": [ "ai", "chatgpt", "openai", "iphone", "crypto", "stock", "jobs", "travel" ], "maxTrendsPerGeo": 25, "minTraffic": 0, "freshnessHours": 72, "includeLowSignal": 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("signalcrawl/google-trends-opportunity-radar").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("signalcrawl/google-trends-opportunity-radar").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 signalcrawl/google-trends-opportunity-radar --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=signalcrawl/google-trends-opportunity-radar", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Google Trends Opportunity Radar", "description": "Find rising Google Trends topics by country with traffic floors, keyword matches, trend scores, categories, and content/SEO action notes.", "version": "0.1", "x-build-id": "l1LMce5pzTJDUEeFG" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/signalcrawl~google-trends-opportunity-radar/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-signalcrawl-google-trends-opportunity-radar", "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/signalcrawl~google-trends-opportunity-radar/runs": { "post": { "operationId": "runs-sync-signalcrawl-google-trends-opportunity-radar", "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/signalcrawl~google-trends-opportunity-radar/run-sync": { "post": { "operationId": "run-sync-signalcrawl-google-trends-opportunity-radar", "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": [ "geos" ], "properties": { "geos": { "title": "Countries", "minItems": 1, "type": "array", "description": "Google Trends country codes to monitor, for example US, GB, FR, DE, CA.", "items": { "type": "string", "minLength": 2 }, "default": [ "US" ] }, "keywords": { "title": "Keywords to match", "type": "array", "description": "Optional keywords used to tag and score trends that match your niche.", "items": { "type": "string", "minLength": 1 }, "default": [ "ai", "chatgpt", "openai", "iphone", "crypto", "stock", "jobs", "travel" ] }, "maxTrendsPerGeo": { "title": "Max trends per country", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum number of trend records to save for each country.", "default": 25 }, "minTraffic": { "title": "Minimum traffic floor", "minimum": 0, "type": "integer", "description": "Keep only trends with an approximate traffic floor at or above this value. Use 0 to disable.", "default": 0 }, "freshnessHours": { "title": "Freshness window in hours", "minimum": 0, "maximum": 720, "type": "integer", "description": "Keep trends published in the last N hours when dates are available. Use 0 to disable.", "default": 72 }, "includeLowSignal": { "title": "Include low-signal trends", "type": "boolean", "description": "If false, only saves trends with keyword matches, high traffic, or stronger opportunity labels.", "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 } } } } } } } } } } ```