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

{
  "Urls": [
    "https://www.fergusonhome.com/schlage-1011/s38699?uid=2970625"
  ]
}

Output 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!