# Experience Posts Spider (`getdataforme/experience-posts-spider`) Actor Experience Posts Spider automates scraping detailed post data from Experience.com reviews and Google Local Posts, extracting descriptions, media, actions, and timestamps.... - **URL**: https://apify.com/getdataforme/experience-posts-spider.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** Agents, News, Social media - **Stats:** 8 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $13.67 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. 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 ## Experience Posts Spider ### Introduction The Experience Posts Spider is a powerful Apify Actor designed to scrape and extract detailed post data from Experience.com review pages and related Google Local Posts. It automates the collection of valuable insights such as post descriptions, media, actions, and timestamps, enabling users to gather comprehensive data for analysis and decision-making. This tool is ideal for businesses, researchers, and developers seeking efficient, reliable data extraction without manual effort. ### Features - **Comprehensive Data Extraction**: Scrapes key details from posts, including IDs, descriptions, media URLs, and action links. - **High Reliability**: Built with robust error handling to ensure consistent data retrieval from dynamic web sources. - **Flexible Input**: Accepts multiple URLs for batch processing, allowing scalable scraping operations. - **Structured Output**: Delivers clean, JSON-formatted data ready for integration into databases or analytics tools. - **Performance Optimized**: Utilizes efficient scraping techniques to minimize load times and resource usage. - **Google Integration**: Specifically targets Google Local Posts linked to Experience.com reviews for targeted insights. - **Easy Deployment**: Runs seamlessly on Apify's cloud platform with minimal setup. ### Input Parameters | Parameter | Type | Required | Description | Example | |-----------|--------|----------|-------------|---------| | Urls | array | No | An array of URLs to scrape posts from, such as Experience.com review pages. | ["https://www.experience.com/reviews/MsOceanside"] | ### Example Usage #### Input ```json { "Urls": [ "https://www.experience.com/reviews/MsOceanside" ] } ```` #### Output ```json [ { "post_id": 48876517, "post_path": "accounts/107205323378750551930/locations/5506691445701696962/localPosts/5140700231027023279", "description": "My latest RateMyAgent review in .\n\n\r\n\r\n...\r\n#ratemyagent #realestate #Keller_Williams_Rea5lty", "action_type": "LEARN_MORE", "action_url": "https://www.ratemyagent.com/real-estate-agent/melissa-huk-am859/sales/reviews?externalReviewId=AbFvOqk8u25NlDcteYtMShTFtuP3SBWr9QQ4EBKgwq405vlCEH_DJ6WDpsTCVa9AiQK87m-IvCfLhQ&reviewSource=Google&utm_source=GMB&utm_medium=smm_Scheduled&utm_campaign=individu", "state": "LIVE", "media_url": "https://lh3.googleusercontent.com/p/AF1QipP9EgObra182G3GGzlAEkpmUeXGpQeKmJ71zFt9", "media_format": "PHOTO", "topic_type": "STANDARD", "created_at": "2026-01-21T16:11:51.657Z", "updated_at": "2026-01-28T12:06:55.239Z", "search_url": "https://local.google.com/place?id=15397593567260242780&use=posts&lpsid=CIHM0ogKEPGjvo2M8u34sgE", "source": "google", "resource_name": "Ms. Oceanside Real Estate" }, { "post_id": 47669060, "post_path": "accounts/107205323378750551930/locations/5506691445701696962/localPosts/195573970864585688", "description": "My latest RateMyAgent review in .\n\n\r\n\r\n...\r\n#ratemyagent #realestate #Keller_Williams_Rea5lty", "action_type": "LEARN_MORE", "action_url": "https://www.ratemyagent.com/real-estate-agent/melissa-huk-am859/sales/reviews?externalReviewId=AbFvOqn_FW2NPGm9yodwLx-PoxbQ1rB8Cw3dNH6GnIGz7fyAkih2WNaRVwgONAY6YmxOlfiVii3E&reviewSource=Google&utm_source=GMB&utm_medium=smm_Scheduled&utm_campaign=individual", "state": "LIVE", "media_url": "https://lh3.googleusercontent.com/p/AF1QipOkyLOqFMx0nvSPdvBbaejAstW81-ZPs45GPYbA", "media_format": "PHOTO", "topic_type": "STANDARD", "created_at": "2026-01-14T16:10:44.683Z", "updated_at": "2026-01-28T12:06:55.239Z", "search_url": "https://local.google.com/place?id=15397593567260242780&use=posts&lpsid=CIHM0ogKEJXG-dneiZHY5QE", "source": "google", "resource_name": "Ms. Oceanside Real Estate" }, { "post_id": 46459470, "post_path": "accounts/107205323378750551930/locations/5506691445701696962/localPosts/8199145786242877519", "description": "My latest RateMyAgent review in .\n\n\r\n\r\n...\r\n#ratemyagent #realestate #Keller_Williams_Rea5lty", "action_type": "LEARN_MORE", "action_url": "https://www.ratemyagent.com/real-estate-agent/melissa-huk-am859/sales/reviews?externalReviewId=AbFvOqlL0Kntqje8Mza3hx4KWmtYYjCvBBsC1CO1X29sK65Yd1cHUshze4Q8j_557S8dpQlgw-JZLw&reviewSource=Google&utm_source=GMB&utm_medium=smm_Scheduled&utm_campaign=individu", "state": "LIVE", "media_url": "https://lh3.googleusercontent.com/p/AF1QipMBloXw9v0QjXKK3nRyW4Gmsq1Es5YxWOpYc0e9", "media_format": "PHOTO", "topic_type": "STANDARD", "created_at": "2026-01-07T16:09:47.984Z", "updated_at": "2026-01-28T12:06:55.239Z", "search_url": "https://local.google.com/place?id=15397593567260242780&use=posts&lpsid=CIHM0ogKEOnXnPu2xI6LEQ", "source": "google", "resource_name": "Ms. Oceanside Real Estate" } ] ``` ### Use Cases - **Market Research**: Analyze customer feedback and trends from Experience.com reviews to inform product development. - **Competitive Intelligence**: Monitor competitors' Google Local Posts for insights into their marketing strategies. - **Content Aggregation**: Collect and organize post data for social media analysis or content creation. - **Academic Research**: Gather historical post data for studies on consumer behavior and online reputation. - **Business Automation**: Automate data extraction for dashboards tracking brand mentions and reviews. - **Real Estate Insights**: Extract reviews and posts related to real estate agents for performance evaluation. ### Installation and Usage 1. Search for "Experience Posts Spider" in the Apify Store. 2. Click "Try for free" or "Run". 3. Configure input parameters. 4. Click "Start" to begin extraction. 5. Monitor progress in the log. 6. Export results in your preferred format (JSON, CSV, Excel). ### Output Format The Actor outputs an array of JSON objects, each representing a scraped post. Key fields include `post_id` (unique identifier), `description` (post content), `action_type` and `action_url` (call-to-action details), `media_url` and `media_format` (associated media), `created_at` and `updated_at` (timestamps), `source` (e.g., "google"), and `resource_name` (associated entity). This structured format ensures easy parsing and integration. ### Support For custom/simplified outputs or bug reports, please contact: - Email: support@getdataforme.com - Subject line: "custom support" - Contact form: https://getdataforme.com/contact/ We're here to help you get the most out of this Actor! # Actor input Schema ## `Urls` (type: `array`): The urls for the spider. ## `itemLimit` (type: `integer`): Specifies the maximum number of items to process. ## Actor input object example ```json { "Urls": [ "https://www.experience.com/reviews/MsOceanside" ], "itemLimit": 10 } ``` # Actor output Schema ## `results` (type: `string`): Scraped data items from dataset # 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 = { "itemLimit": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("getdataforme/experience-posts-spider").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 = { "itemLimit": 10 } # Run the Actor and wait for it to finish run = client.actor("getdataforme/experience-posts-spider").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 '{ "itemLimit": 10 }' | apify call getdataforme/experience-posts-spider --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/experience-posts-spider", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Experience Posts Spider", "description": "Experience Posts Spider automates scraping detailed post data from Experience.com reviews and Google Local Posts, extracting descriptions, media, actions, and timestamps....", "version": "0.0", "x-build-id": "nepINKqxPz1x5ctte" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~experience-posts-spider/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-experience-posts-spider", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~experience-posts-spider/runs": { "post": { "operationId": "runs-sync-getdataforme-experience-posts-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~experience-posts-spider/run-sync": { "post": { "operationId": "run-sync-getdataforme-experience-posts-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "Urls": { "title": "Urls", "type": "array", "description": "The urls for the spider.", "default": [ "https://www.experience.com/reviews/MsOceanside" ], "items": { "type": "string" } }, "itemLimit": { "title": "Item Limit", "type": "integer", "description": "Specifies the maximum number of items to process.", "default": 10 } } }, "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 } } } } } } } } } } ```