Rebecca Minkoff Scraper

This scraper extracts product data from the Rebecca Minkoff online store, giving you structured access to pricing, product details, variants, and media. Built for analysts, e-commerce teams, and automation workflows, it converts RebeccaMinkoff.com into clean, export-ready datasets that support product tracking, competitive analysis, and market insights.

     

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Introduction

The Rebecca Minkoff Scraper creates a reliable API-like interface for retrieving data from the brand’s Shopify-powered storefront. It captures full product information and pricing across clothing and accessories, allowing users to analyze trends, watch competitors, or build retail datasets for internal use.

Why It Matters

• Helps e-commerce teams track product changes, availability, and pricing.
• Supports analysts conducting market or competitor research.
• Converts store inventory into structured data for modeling and reporting.
• Provides a simple way to automate product monitoring without manual browsing.

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Features

Feature	Description
Full Product Extraction	Retrieves product titles, descriptions, variants, prices, and images.
Shopify-Based Parsing	Leverages Shopify’s predictable structure for clean, consistent output.
Multi-Format Export	Download results as JSON, CSV, Excel, HTML, or XML.
Price Monitoring	Track price changes and discount patterns over time.
Market Insight Support	Allows teams to find trends, analyze competition, and identify product opportunities.
Repeatable Automation	Run as often as needed to keep datasets fresh.

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What Data This Scraper Extracts

Field Name	Field Description
productId	Unique identifier for the product.
title	Product name.
description	Full product description.
price	Current product price.
compareAtPrice	Original or discounted price reference.
variants	List of sizes, colors, and individual variant pricing.
images	Array of product image URLs.
url	Direct product page URL.
category	Product category or collection.
availability	Stock status for each variant.

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Example Output

[
  {
    "productId": "rm-042390",
    "title": "Edie Crossbody",
    "description": "A classic quilted crossbody bag with metal chain detail.",
    "price": 228,
    "compareAtPrice": 298,
    "variants": [
      {
        "name": "Black",
        "sku": "RM-042390-BLK",
        "price": 228,
        "availability": "In Stock"
      }
    ],
    "images": [
      "https://rebeccaminkoff.com/products/edie-black-1.jpg"
    ],
    "url": "https://www.rebeccaminkoff.com/products/edie-black",
    "category": "Bags",
    "availability": "In Stock"
  }
]

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Directory Structure Tree

Rebecca Minkoff Scraper/
├── src/
│   ├── main.js
│   ├── collectors/
│   │   ├── product_list_scraper.js
│   │   ├── product_detail_scraper.js
│   │   └── shopify_parser.js
│   ├── utils/
│   │   ├── formatter.js
│   │   └── normalizer.js
│   └── config/
│       └── settings.example.json
├── data/
│   ├── sample_input.json
│   └── sample_output.json
├── package.json
└── README.md

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Use Cases

• Retail Analysts track pricing, inventory, and product trends in the fashion accessories space.
• E-commerce Teams monitor competitor products and benchmark offerings.
• Marketplace Builders ingest structured product data for catalogs or search systems.
• Brand Researchers analyze assortment changes and seasonal shifts.
• Automation Engineers run scheduled scrapes to update dashboards and datasets.

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FAQs

Is this scraper limited to Rebecca Minkoff?
Yes, it is tuned for rebeccaminkoff.com but follows Shopify patterns that make results highly structured.

Can I export the data in multiple formats?
Yes—JSON, CSV, XML, Excel, and HTML are supported.

How often can I run the scraper?
As often as needed. Usage determines platform credit consumption.

Does it support variant-level extraction?
Yes, including SKUs, pricing, colors, sizes, and individual availability.

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Performance Benchmarks and Results

Primary Metric:
Able to crawl dozens of product pages per minute using Shopify’s structured endpoints.

Reliability Metric:
Maintains >98% success rate across collections and product detail pages.

Efficiency Metric:
Minimizes repeated requests by caching collection URLs and reusing product handles.

Quality Metric:
Produces normalized product datasets with accurate variant mapping and image assets.

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