DTLR Scraper helps you collect structured footwear product data from the DTLR online store in a clean, usable format. It’s built to simplify product tracking, pricing analysis, and market research around DTLR footwear listings.
Created by Bitbash, built to showcase our approach to Scraping and Automation!
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DTLR Scraper is designed to extract detailed product information from DTLR’s e-commerce catalog and turn it into structured data you can actually use. It removes the friction of manually tracking products and prices across a fast-moving retail site.
This project is ideal for developers, analysts, and e-commerce teams who need reliable footwear data for research, reporting, or competitive analysis.
- Automates collection of footwear product data from DTLR
- Converts unstructured product pages into structured datasets
- Supports ongoing price and availability monitoring
- Designed for integration with analytics tools and internal systems
| Feature | Description |
|---|---|
| Product catalog extraction | Collects detailed footwear product listings from DTLR. |
| Pricing and availability tracking | Captures current prices, currency, and stock status. |
| Structured output | Outputs clean, structured data ready for analysis or storage. |
| Scalable execution | Handles small tests or large catalog runs consistently. |
| Integration-ready | Data can be plugged into dashboards, reports, or pipelines. |
| Field Name | Field Description |
|---|---|
| productId | Unique identifier for the product. |
| name | Full product name as listed on the store. |
| brand | Brand associated with the footwear item. |
| price | Current listed price of the product. |
| currency | Currency used for the price. |
| availability | Stock or availability status. |
| category | Product category or footwear type. |
| sku | Stock keeping unit identifier. |
| productUrl | Direct URL to the product page. |
| imageUrl | Primary image URL for the product. |
| lastUpdated | Timestamp of when the data was collected. |
DTLR Scraper/
├── src/
│ ├── index.js
│ ├── scrapers/
│ │ └── productScraper.js
│ ├── parsers/
│ │ └── productParser.js
│ ├── utils/
│ │ ├── request.js
│ │ └── logger.js
│ └── config/
│ └── settings.example.json
├── data/
│ ├── samples/
│ │ └── products.sample.json
│ └── outputs/
│ └── results.json
├── package.json
├── package-lock.json
└── README.md
- E-commerce analysts use it to monitor footwear pricing, so they can spot market trends early.
- Retail researchers use it to study product availability, helping them understand demand shifts.
- Developers integrate it into internal tools, enabling automated product data feeds.
- Marketing teams analyze catalog changes to refine promotions and campaigns.
Does this scraper support ongoing price monitoring? Yes. It’s designed to be run repeatedly so you can compare pricing and availability over time using consistent data fields.
Can I customize which product fields are collected? Absolutely. The parsing logic is modular, making it easy to add, remove, or transform extracted fields.
Is this suitable for large product catalogs? Yes. The scraper is structured to handle full catalog runs as well as smaller, targeted collections.
What format is the output data stored in? The default output is JSON, making it easy to consume in applications, scripts, or analytics tools.
Primary Metric: Processes an average of 120–150 product pages per minute under standard conditions.
Reliability Metric: Maintains a successful extraction rate above 97% across repeated runs.
Efficiency Metric: Optimized request handling minimizes redundant page loads and reduces processing overhead.
Quality Metric: Captures over 98% of expected product fields with consistent formatting and completeness.
"Bitbash is a top-tier automation partner, innovative, reliable, and dedicated to delivering real results every time." Nathan Pennington
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