# Google Trends API — Pay Per Result, No Empty Charges (`greza/google-trends-realtime`) Actor Google Trends via a resilient API: interest over time, cross-term compare (one 0–100 scale), related, interest by region, realtime trending. Pay per result — never charged for empty data. - **URL**: https://apify.com/greza/google-trends-realtime.md - **Developed by:** [Sergei Peleskov](https://apify.com/greza) (community) - **Categories:** SEO tools, Developer tools, News - **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 1,000 keyword 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 API — Pay Per Result, No Empty Charges Google Trends data through a **resilient API**: interest over time, **cross-term compare** (2–5 keywords on one shared 0–100 scale), related queries & topics, interest by region, and **realtime trending**. You pay **per result** — and **never for empty data**. Built for people who tried the official Google Trends API and hit its walls: alpha status, quotas, Google Cloud auth, and **no recent/realtime data**. --- ### Why this Actor #### This Actor vs typical / official Trends scrapers | | This Actor | Typical / official Trends API | |---|---|---| | **Pay for empty results** | ❌ Never — empty = `no_data`, not billed | ✅ You pay for the call regardless | | **Realtime windows** (`now 1-H`…`now 7-d`) | ✅ Yes | ❌ Official alpha has no recent data | | **Retries + residential rotation** | ✅ Built in — survives the first 429, doesn't fall over | ❌ You handle 429s / IP bans yourself | | **Cross-term scaling** (up to 5 keywords, one 0–100 scale) | ✅ Yes | ❌ Single-keyword scales only | | **Related + interest-by-region** | ✅ One Actor, one contract | ⚠️ Fragmented / partial | | **Pricing** | ✅ Pay-per-event, pay for what you use | ❌ Quota tiers / rental subscription | Reliability (retries, residential IP rotation, backpressure with `Retry-After`) is handled server-side — you just get **stable results that don't break on the first rate-limit**. --- ### Scrape types Pick one via `scrapeType`: - **`interestOverTime`** — popularity of each keyword over time (independent 0–100 scale per keyword). - **`compare`** — 2–5 keywords on **one shared 0–100 scale** (cross-term scaling). One request, one price — comparable numbers across terms. - **`related`** — top & rising related queries and topics. - **`interestByRegion`** — geographic breakdown (`COUNTRY` / `REGION` / `CITY` / `DMA`). - **`trendingNow`** — realtime trending searches for a location. --- ### Input ```json { "scrapeType": "interestOverTime", "keywords": ["bitcoin", "ethereum"], "geo": "US", "timeRange": "today 3-m", "category": 0 } ```` | Field | Type | Notes | |---|---|---| | `scrapeType` | enum | `interestOverTime` | `compare` | `related` | `interestByRegion` | `trendingNow` | | `keywords` | string\[] | 1–50; **exactly 2–5 for `compare`**; not required for `trendingNow` | | `geo` | string | `""` = worldwide, `US`, `US-CA` | | `timeRange` | enum | `now 1-H`…`now 7-d`, `today 1-m`…`today 5-y`, `all`, `custom` | | `customTimeRange` | string | when `timeRange=custom`: `YYYY-MM-DD YYYY-MM-DD` | | `category` | integer | Google category id, `0` = all | | `resolution` | enum | `interestByRegion` only: `COUNTRY`/`REGION`/`CITY`/`DMA` | No proxy configuration — residential rotation is included. *** ### Output One dataset item per keyword × scrape type (compare = one item for the group). Data mirrors the normalized API schema, plus the request fields (`kw`/`keywords`, `geo`, `time`) for easy filtering. **interestOverTime** ```json { "scrapeType": "interestOverTime", "kw": "bitcoin", "geo": "US", "time": "today 3-m", "points": [{ "date": "Jun 1, 2026", "value": 52, "isPartial": false }] } ``` **compare** (one shared 0–100 scale, order preserved) ```json { "scrapeType": "compare", "geo": "US", "time": "today 3-m", "keywords": ["btc", "eth", "doge"], "points": [{ "date": "Jun 5, 2026", "isPartial": false, "values": { "btc": 100, "eth": 26, "doge": 13 } }], "keywords_meta": {} } ``` Low-volume terms come back with `values: 0` and a `keywords_meta[kw]: "low_volume"` flag — the run never fails on them. **No data / failed** (never billed) ```json { "scrapeType": "related", "kw": "asdfqwerzxcv", "geo": "US", "status": "no_data" } ``` *** ### Pricing (pay per event) You are charged **only for delivered non-empty results**: | Event | When | Price | |---|---|---| | `keyword-result` | one keyword returned data (iot / related / region) | $0.005 | | `compare-result` | one 2–5 keyword comparison returned data (**once, not ×5**) | $0.005 | | `trending-page` | one realtime trending page returned data | $0.005 | **Never charged:** empty results (`no_data`), failed requests, or any error. Compare is one event for the whole group — that's the point of batching. *** ### FAQ **How is this different from the official Google Trends API?** The official API is alpha: quota-limited, requires Google Cloud auth, and has **no recent/realtime data**. This Actor gives realtime windows (`now 1-H`…`now 7-d`), needs only an Apify token, and bills per delivered result instead of per quota unit. **Why did I get `no_data` for a keyword?** Google returned a valid response with no data for that term (too low volume, or no coverage in the geo). It's in the dataset with `status: "no_data"` and is **not billed**. **What happens under heavy load?** The backing service applies backpressure (`503` + `Retry-After`); the Actor honors it — waits and retries automatically, so your run doesn't drop requests. **Can I compare keywords on the same scale?** Yes — `scrapeType: "compare"` with 2–5 keywords puts them on one shared 0–100 scale (cross-term scaling), so the numbers are directly comparable. *** ### Integrations Works with the Apify **API**, **n8n**, **Make**, and **MCP** — run it and pull results from the dataset like any Actor. Example (API run input): ```json { "scrapeType": "compare", "keywords": ["btc", "eth", "doge"], "geo": "US", "timeRange": "today 3-m" } ``` *** ### Notes for operators - Requires two **secret environment variables** on the Actor: `GATEWAY_URL` and `GATEWAY_API_KEY` (never in input, never hardcoded). - Optional env: `ACTOR_CONCURRENCY` (default 8), `GATEWAY_RETRY_503` (default 6). # Actor input Schema ## `scrapeType` (type: `string`): Which Google Trends dataset to fetch. `compare` puts 2–5 keywords on ONE shared 0–100 scale (cross-term scaling). ## `keywords` (type: `array`): Search terms. 1–50 for most types; exactly 2–5 for `compare`. Not required for `trendingNow`. ## `geo` (type: `string`): ISO country or region: empty = worldwide, `US`, `US-CA`. Pattern `^$|^[A-Z]{2}(-[A-Z0-9]{1,3})?$`. ## `timeRange` (type: `string`): Realtime windows (`now *`) are supported — unlike the official Trends API. Pick `custom` to supply an explicit date range below. ## `customTimeRange` (type: `string`): Only used when Time range = `custom`. Format `YYYY-MM-DD YYYY-MM-DD` (e.g. `2026-01-01 2026-03-01`). ## `category` (type: `integer`): Google Trends category id. 0 = all categories. ## `resolution` (type: `string`): Only for `interestByRegion`: granularity of the geo breakdown. ## Actor input object example ```json { "scrapeType": "interestOverTime", "keywords": [ "bitcoin" ], "geo": "", "timeRange": "today 3-m", "category": 0, "resolution": "COUNTRY" } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "keywords": [ "bitcoin" ] }; // Run the Actor and wait for it to finish const run = await client.actor("greza/google-trends-realtime").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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("greza/google-trends-realtime").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 greza/google-trends-realtime --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=greza/google-trends-realtime", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Google Trends API — Pay Per Result, No Empty Charges", "description": "Google Trends via a resilient API: interest over time, cross-term compare (one 0–100 scale), related, interest by region, realtime trending. Pay per result — never charged for empty data.", "version": "0.1", "x-build-id": "SiIuXBKNVVFwuDA9o" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/greza~google-trends-realtime/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-greza-google-trends-realtime", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/greza~google-trends-realtime/runs": { "post": { "operationId": "runs-sync-greza-google-trends-realtime", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/greza~google-trends-realtime/run-sync": { "post": { "operationId": "run-sync-greza-google-trends-realtime", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "scrapeType" ], "properties": { "scrapeType": { "title": "What to scrape", "enum": [ "interestOverTime", "compare", "related", "interestByRegion", "trendingNow" ], "type": "string", "description": "Which Google Trends dataset to fetch. `compare` puts 2–5 keywords on ONE shared 0–100 scale (cross-term scaling).", "default": "interestOverTime" }, "keywords": { "title": "Keywords", "minItems": 0, "maxItems": 50, "type": "array", "description": "Search terms. 1–50 for most types; exactly 2–5 for `compare`. Not required for `trendingNow`.", "items": { "type": "string" } }, "geo": { "title": "Location (geo)", "pattern": "^$|^[A-Z]{2}(-[A-Z0-9]{1,3})?$", "type": "string", "description": "ISO country or region: empty = worldwide, `US`, `US-CA`. Pattern `^$|^[A-Z]{2}(-[A-Z0-9]{1,3})?$`.", "default": "" }, "timeRange": { "title": "Time range", "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", "custom" ], "type": "string", "description": "Realtime windows (`now *`) are supported — unlike the official Trends API. Pick `custom` to supply an explicit date range below.", "default": "today 3-m" }, "customTimeRange": { "title": "Custom time range", "pattern": "^\\d{4}-\\d{2}-\\d{2} \\d{4}-\\d{2}-\\d{2}$", "type": "string", "description": "Only used when Time range = `custom`. Format `YYYY-MM-DD YYYY-MM-DD` (e.g. `2026-01-01 2026-03-01`)." }, "category": { "title": "Category ID", "minimum": 0, "type": "integer", "description": "Google Trends category id. 0 = all categories.", "default": 0 }, "resolution": { "title": "Region resolution", "enum": [ "COUNTRY", "REGION", "CITY", "DMA" ], "type": "string", "description": "Only for `interestByRegion`: granularity of the geo breakdown.", "default": "COUNTRY" } } }, "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 } } } } } } } } } } ```