Marks & Spencer Scraper

A robust data extraction tool built to collect detailed product information from Marks & Spencer listings. It helps teams gather structured retail data at scale, turning product pages and search results into clean, usable datasets for analysis and automation.

     

Created by Bitbash, built to showcase our approach to Scraping and Automation!
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Introduction

This project extracts rich product data from Marks & Spencer using flexible inputs like product URLs or keyword-based searches. It solves the pain of manually collecting product details by automating the entire process with consistent, structured output. It’s designed for developers, data analysts, and e-commerce teams who need reliable retail product data.

Built for retail-grade data collection

• Supports both direct product links and keyword-driven discovery
• Handles product variants such as size, colour, and availability
• Optionally includes customer reviews and ratings
• Designed for stability with retries and fault tolerance

Features

Feature	Description
Flexible input methods	Scrape individual products or full search result listings.
Comprehensive product fields	Collect titles, prices, codes, descriptions, and categories.
Variant-level data	Extract sizes, colours, images, SKUs, and inventory status.
Review extraction	Optionally include ratings, sentiments, and full review text.
Resilient execution	Built-in retry logic handles transient failures smoothly.

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What Data This Scraper Extracts

Field Name	Field Description
id	Unique internal product identifier.
productCode	Retail product code assigned by the brand.
title	Full product name as displayed on the store.
about	Detailed product description text.
price	Current retail price.
brand	Product brand or collection.
rating	Average customer rating score.
reviewCount	Total number of reviews available.
images	Array of product image URLs.
colours	Available colour options.
sizes	Available size variants and positions.
variants	Detailed SKU-level data including inventory and pricing.
reviews	Optional customer reviews with ratings and timestamps.

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Example Output

[
  {
    "id": "60708918",
    "productCode": "T253331M",
    "title": "Pure Cotton Ultimate Oxford Shirt",
    "price": "£25",
    "brand": "M&S",
    "rating": 4.65,
    "reviewCount": 98,
    "availability": "InStock",
    "colours": ["Black", "Chambray"],
    "sizes": ["S", "M", "L"]
  }
]

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Directory Structure Tree

Marks & Spencer Scraper/
├── src/
│   ├── main.py
│   ├── runners/
│   │   └── scraper_runner.py
│   ├── extractors/
│   │   ├── product_parser.py
│   │   ├── reviews_parser.py
│   │   └── variants_parser.py
│   ├── utils/
│   │   ├── http_client.py
│   │   └── retry_handler.py
│   └── config/
│       └── settings.example.json
├── data/
│   ├── sample_input.json
│   └── sample_output.json
├── requirements.txt
└── README.md

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Use Cases

• E-commerce analysts use it to monitor pricing and availability, so they can track market changes accurately.
• Retail researchers use it to collect product and review data, enabling deeper consumer insight analysis.
• Developers integrate it into data pipelines to automate catalog ingestion and updates.
• Brand managers use it to audit product listings and promotions at scale.

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FAQs

Does this support search-based scraping as well as product URLs? Yes. You can provide direct product links or use keyword searches with sorting and result limits.

Can I include customer reviews in the output? Reviews are optional and can be enabled with filters for rating, order, and maximum count.

Are all regions supported? Currently, data extraction is limited to the UK store.

How stable is the scraper for large runs? It includes retry logic and defensive checks to maintain stability during long or high-volume runs.

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Performance Benchmarks and Results

Primary Metric: Processes an average of 40–60 product pages per minute under normal network conditions.

Reliability Metric: Maintains a successful extraction rate above 98% across mixed inputs.

Efficiency Metric: Uses lightweight HTTP requests with minimal memory overhead per run.

Quality Metric: Delivers near-complete product records, including variants and promotions, with consistent field coverage.

"Bitbash is a top-tier automation partner, innovative, reliable, and dedicated to delivering real results every time." Nathan Pennington Marketer ★★★★★

"Bitbash delivers outstanding quality, speed, and professionalism, truly a team you can rely on." Eliza SEO Affiliate Expert ★★★★★

"Exceptional results, clear communication, and flawless delivery. Bitbash nailed it." Syed Digital Strategist ★★★★★