# Google Autocomplete Keyword Suggestions Scraper (`dromb/google-autocomplete-keyword-suggestions-scraper`) Actor Discover live Google Autocomplete keyword suggestions for SEO, content planning, paid search, product research, and market demand analysis. - **URL**: https://apify.com/dromb/google-autocomplete-keyword-suggestions-scraper.md - **Developed by:** [Dmitriy Gyrbu](https://apify.com/dromb) (community) - **Categories:** Developer tools, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.09 / 1,000 keyword suggestions This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 Autocomplete Keyword Suggestions Scraper Extract live Google Autocomplete keyword suggestions from seed terms and turn them into a clean dataset for SEO, content planning, paid search, product research, and market demand analysis. This Actor is unofficial and is not affiliated with Google. ### Why Use It Google Autocomplete reflects what people are actively searching for while they type. This Actor helps you turn that demand signal into structured keyword ideas you can export, analyze, cluster, or feed into your SEO and advertising workflows. Use it to: - discover long-tail keyword ideas from a few seed terms; - plan blog posts, landing pages, comparison pages, and FAQ sections; - research buyer intent around products, tools, brands, and categories; - expand paid search keyword lists before campaign setup; - monitor how Google suggestions change around a market, brand, or topic. ### What You Get Each result is a normalized keyword suggestion with the seed keyword, generated query, suggestion text, source, and collection timestamp. ```json { "seedKeyword": "apify", "query": "apify", "suggestion": "apify api", "weight": 1, "source": "google_autocomplete", "collectedAt": "2026-07-01T00:00:00+00:00" } ```` The run also stores an `OUTPUT` summary with the run status, number of requested queries, successful queries, failed queries, pushed items, and structured errors if any query fails. ### Input ```json { "seedKeywords": ["apify", "web scraping"], "expansionMode": "none", "maxQueries": 50, "maxSuggestionsPerQuery": 20, "deduplicate": true } ``` #### Input Fields - `seedKeywords`: Base terms, brands, products, categories, or topics to research. - `expansionMode`: Controls how seed keywords are turned into autocomplete lookups. - `maxQueries`: Maximum number of generated autocomplete lookups for the run. - `maxSuggestionsPerQuery`: Maximum number of suggestions saved per lookup. - `deduplicate`: Keeps only the first occurrence of each suggestion across the run. ### Expansion Modes #### Exact keyword discovery Set `expansionMode` to `none` when you want suggestions for the seed keywords exactly as entered. Best for quick validation, brand monitoring, and small keyword checks. ```json { "seedKeywords": ["apify", "web scraping"], "expansionMode": "none", "maxQueries": 2, "maxSuggestionsPerQuery": 10, "deduplicate": true } ``` Saved Apify task: `google-autocomplete-suggestions-seed-ideas` #### Long-tail alphabet expansion Set `expansionMode` to `alphabet` to generate lookups such as `crm software a`, `crm software b`, and so on. Best for long-tail SEO research, product/category keyword expansion, and finding phrases that are easy to miss with a single seed query. ```json { "seedKeywords": ["crm software"], "expansionMode": "alphabet", "maxQueries": 10, "maxSuggestionsPerQuery": 10, "deduplicate": true } ``` Saved Apify task: `google-autocomplete-suggestions-long-tail-seo` #### Buyer and research questions Set `expansionMode` to `questions` to generate research and commercial-intent lookups such as `what is keyword`, `how to keyword`, `best keyword`, and `keyword alternatives`. Best for comparison pages, FAQ content, buyer journey research, and paid search idea generation. ```json { "seedKeywords": ["web scraping api"], "expansionMode": "questions", "maxQueries": 8, "maxSuggestionsPerQuery": 10, "deduplicate": true } ``` Saved Apify task: `google-autocomplete-suggestions-buyer-questions` ### How To Use 1. Enter one or more seed keywords. 2. Choose an expansion mode. 3. Keep `maxQueries` small for quick checks or raise it for broader research. 4. Run the Actor. 5. Export the dataset as JSON, CSV, Excel, or connect it to your workflow through the Apify API. ### Practical Tips - Use `none` for a fast first pass. - Use `alphabet` when you need broad long-tail coverage. - Use `questions` when you are planning content that answers buyer and research intent. - Keep `deduplicate` enabled when you want a clean keyword list. - Disable `deduplicate` only when you need to see the same suggestion appearing under multiple generated queries. ### Limits And Notes - Suggestions can vary by time, location, language, and Google's current behavior. - The Actor returns autocomplete suggestions, not search volume or ranking difficulty. - Very broad seed keywords can produce generic suggestions; specific seed terms usually produce more actionable results. - Failed lookups are reported in `OUTPUT.errors` instead of being silently ignored. # Actor input Schema ## `seedKeywords` (type: `array`): Base terms, brands, products, categories, or topics to research. ## `expansionMode` (type: `string`): Choose exact seed lookups, alphabet long-tail expansion, or buyer/research question expansion. ## `maxQueries` (type: `integer`): Maximum number of generated autocomplete lookups for this run. ## `maxSuggestionsPerQuery` (type: `integer`): Maximum number of suggestions saved for each autocomplete lookup. ## `deduplicate` (type: `boolean`): Keep only the first occurrence of each suggestion across the run. ## Actor input object example ```json { "seedKeywords": [ "apify", "web scraping" ], "expansionMode": "none", "maxQueries": 50, "maxSuggestionsPerQuery": 20, "deduplicate": 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("dromb/google-autocomplete-keyword-suggestions-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 = {} # Run the Actor and wait for it to finish run = client.actor("dromb/google-autocomplete-keyword-suggestions-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 '{}' | apify call dromb/google-autocomplete-keyword-suggestions-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=dromb/google-autocomplete-keyword-suggestions-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Google Autocomplete Keyword Suggestions Scraper", "description": "Discover live Google Autocomplete keyword suggestions for SEO, content planning, paid search, product research, and market demand analysis.", "version": "0.1", "x-build-id": "r0o3JrEQKUEUqcGHH" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/dromb~google-autocomplete-keyword-suggestions-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-dromb-google-autocomplete-keyword-suggestions-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/dromb~google-autocomplete-keyword-suggestions-scraper/runs": { "post": { "operationId": "runs-sync-dromb-google-autocomplete-keyword-suggestions-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/dromb~google-autocomplete-keyword-suggestions-scraper/run-sync": { "post": { "operationId": "run-sync-dromb-google-autocomplete-keyword-suggestions-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "seedKeywords": { "title": "Seed Keywords", "type": "array", "description": "Base terms, brands, products, categories, or topics to research.", "items": { "type": "string" }, "default": [ "apify", "web scraping" ] }, "expansionMode": { "title": "Expansion Mode", "enum": [ "none", "alphabet", "questions" ], "type": "string", "description": "Choose exact seed lookups, alphabet long-tail expansion, or buyer/research question expansion.", "default": "none" }, "maxQueries": { "title": "Max Queries", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of generated autocomplete lookups for this run.", "default": 50 }, "maxSuggestionsPerQuery": { "title": "Max Suggestions Per Query", "minimum": 1, "maximum": 50, "type": "integer", "description": "Maximum number of suggestions saved for each autocomplete lookup.", "default": 20 }, "deduplicate": { "title": "Deduplicate Suggestions", "type": "boolean", "description": "Keep only the first occurrence of each suggestion across the run.", "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 } } } } } } } } } } ```