# Ferguson Reviews Spider (`getdataforme/ferguson-reviews-spider`) Actor The Ferguson Reviews Spider automates scraping detailed product reviews from Ferguson Home, extracting ratings, titles, bodies, and reviewer details. It provides accurate, structured JSON data for market research, competitive intelligence, and informed decision-making.... - **URL**: https://apify.com/getdataforme/ferguson-reviews-spider.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** E-commerce, Jobs, Real estate - **Stats:** 4 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $10.00 / 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 ## Ferguson Reviews Spider ### Introduction The Ferguson Reviews Spider is an Apify Actor designed to scrape and extract detailed product reviews from Ferguson Home, a leading online retailer for plumbing, heating, and HVAC products. This tool automates the collection of customer feedback, ratings, and related data, enabling businesses and researchers to gain valuable insights into product performance and customer sentiment. By providing structured, reliable data, it streamlines market research and decision-making processes. ### Features - **Comprehensive Review Extraction**: Captures full review details including ratings, titles, bodies, reviewer info, submission times, and helpfulness counts. - **High Data Accuracy**: Ensures reliable scraping with built-in error handling and data validation to minimize inaccuracies. - **Flexible Input Options**: Accepts multiple URLs for batch processing, allowing efficient handling of various products. - **Structured JSON Output**: Delivers clean, machine-readable data in JSON format, perfect for integration with analytics tools. - **Fast and Scalable**: Optimized for performance, capable of processing multiple pages quickly without overloading servers. - **No Coding Required**: User-friendly interface on Apify Store for easy setup and execution. - **Reliable Crawling**: Handles dynamic content and anti-bot measures to ensure consistent data retrieval. ### Input Parameters | Parameter | Type | Required | Description | Example | |-----------|--------|----------|-------------|---------| | Urls | array | Yes | A list of URLs pointing to Ferguson Home product pages from which to extract reviews. Each URL must be a valid HTTP or HTTPS link. | ["https://www.fergusonhome.com/schlage-1011/s38699?uid=2970625"] | ### Example Usage #### Input JSON ```json { "Urls": [ "https://www.fergusonhome.com/schlage-1011/s38699?uid=2970625" ] } ```` #### Output JSON ```json [ { "Review_Id": "365857567", "Product_Id": "cp-38699", "Rating": 5, "Title": "No grease", "Body": "Kinda early yet to know. Solid. Less wiggle than other hinges available. I thought they stopped making them. I\u2019m replacing cheap very squeaky hinges. My only issue is there was no grease in the hinge. They used to have this very sticky clear grease that I know worked for decades.", "Reviewer": "", "SubmissionTime": "3 months ago", "IsRecommended": true, "HelpfulCount": 0, "SyndicationSource": "", "Images": [], "BrandResponses": [], "URL": "https://www.fergusonhome.com/schlage-1011/s38699?uid=2970625", "Crawled_Date": "01-14-2026" } ] ``` ### Use Cases - **Market Research and Analysis**: Analyze customer feedback to identify trends in product satisfaction and preferences for plumbing and HVAC items. - **Competitive Intelligence**: Compare reviews across similar products to benchmark performance against competitors. - **Price Monitoring**: Track review sentiments alongside pricing data to inform dynamic pricing strategies. - **Content Aggregation**: Collect and aggregate reviews for content creation, such as blog posts or reports on home improvement products. - **Academic Research**: Gather data for studies on consumer behavior in the retail sector. - **Business Automation**: Integrate review data into dashboards for automated reporting and alert systems. ### Installation and Usage 1. Search for "Ferguson Reviews Spider" in the Apify Store. 2. Click "Try for free" or "Run". 3. Configure input parameters by providing the list of URLs. 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 data in JSON format as an array of objects. Each object represents a single review and includes fields such as Review\_Id (unique identifier), Product\_Id (product code), Rating (numerical score), Title (review headline), Body (full text), Reviewer (author name, if available), SubmissionTime (when posted), IsRecommended (boolean for recommendation), HelpfulCount (number of helpful votes), SyndicationSource (origin if syndicated), Images (array of image URLs), BrandResponses (array of responses), URL (source page), and Crawled\_Date (extraction timestamp). This structure 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. ## Actor input object example ```json { "Urls": [ "https://www.fergusonhome.com/schlage-1011/s38699?uid=2970625" ] } ``` # 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("getdataforme/ferguson-reviews-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 = {} # Run the Actor and wait for it to finish run = client.actor("getdataforme/ferguson-reviews-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 '{}' | apify call getdataforme/ferguson-reviews-spider --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/ferguson-reviews-spider", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Ferguson Reviews Spider", "description": "The Ferguson Reviews Spider automates scraping detailed product reviews from Ferguson Home, extracting ratings, titles, bodies, and reviewer details. It provides accurate, structured JSON data for market research, competitive intelligence, and informed decision-making....", "version": "0.0", "x-build-id": "gBlSACA26YcCdjM6p" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~ferguson-reviews-spider/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-ferguson-reviews-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~ferguson-reviews-spider/runs": { "post": { "operationId": "runs-sync-getdataforme-ferguson-reviews-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~ferguson-reviews-spider/run-sync": { "post": { "operationId": "run-sync-getdataforme-ferguson-reviews-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "minItems": 1, "type": "array", "description": "The urls for the spider.", "default": [ "https://www.fergusonhome.com/schlage-1011/s38699?uid=2970625" ], "items": { "type": "string" } } } }, "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 } } } } } } } } } } ```