Groupon Scraper is a production-ready tool for collecting structured product, pricing, merchant, and review data from Groupon marketplaces worldwide. It helps teams turn fast-changing Groupon listings into reliable datasets for analysis, monitoring, and automation.
Created by Bitbash, built to showcase our approach to Scraping and Automation!
If you are looking for groupon-scraper you've just found your team — Let’s Chat. 👆👆
This project extracts detailed e-commerce data from Groupon category pages, deal URLs, and search results across all Groupon subdomains. It solves the challenge of dealing with dynamic listings, localized pricing, and frequently changing offers. The scraper is built for developers, data teams, and businesses that need consistent, structured Groupon data at scale.
- Supports all Groupon country domains and subdomains
- Handles category pages, direct deal URLs, and search listings
- Normalizes prices, discounts, and currencies
- Captures both product-level and merchant-level insights
- Extracts reviews and related product suggestions
| Feature | Description |
|---|---|
| Multi-page crawling | Collects data from categories, search pages, and deal URLs. |
| Product intelligence | Extracts pricing, discounts, inventory, and urgency signals. |
| Merchant profiling | Captures seller identity, website, and descriptions. |
| Review extraction | Collects customer reviews, ratings, and timestamps. |
| Suggestions engine | Retrieves related and look-alike product offers. |
| Localization support | Works across different countries and currencies. |
| Field Name | Field Description |
|---|---|
| title | Product or deal title displayed on Groupon. |
| url | Direct link to the Groupon deal page. |
| rating | Average customer rating for the product or merchant. |
| reviews | Total number of customer reviews. |
| current_price | Discounted deal price. |
| original_price | Original price before discount. |
| discount_percent | Percentage discount applied to the deal. |
| currency | Currency code based on marketplace location. |
| category | Main product category. |
| categories_breadcrumb | Full category hierarchy. |
| merchant_name | Name of the seller or merchant. |
| merchant_website | Official merchant website if available. |
| images | Product image URLs. |
| models | Variations or product options with pricing. |
| badges | Popularity or promotional tags. |
| urgency_message | Time-sensitive or demand-based messages. |
| suggestions | Related or alternative product recommendations. |
| reviews_data | Review text, rating, reviewer info, and dates. |
[
{
"title": "Ensemble de valises rigides en ABS",
"url": "https://www.groupon.fr/deals/ensemble-valises-rigides-abs-1",
"rating": 5,
"currency": "EUR",
"current_price": 12000,
"original_price": 26549,
"discount_percent": 55,
"merchant_name": "Halterner Technologie GmbH",
"views_24h": 85,
"models": [
{
"title": "Gris et marron",
"current_price": 12000,
"original_price": 26549
}
]
}
]
Groupon Scraper/
├── src/
│ ├── runner.js
│ ├── extractors/
│ │ ├── productExtractor.js
│ │ ├── merchantExtractor.js
│ │ └── reviewExtractor.js
│ ├── utils/
│ │ ├── priceNormalizer.js
│ │ └── paginationHelper.js
│ └── config/
│ └── settings.example.json
├── data/
│ ├── input.sample.json
│ └── output.sample.json
├── package.json
├── package-lock.json
└── README.md
- E-commerce analysts use it to monitor price changes, so they can track discount trends over time.
- Marketing teams use it to compare competing deals, so they can position offers more effectively.
- Affiliate builders use it to power deal comparison sites, so they can monetize high-converting products.
- Product researchers use it to analyze reviews, so they can understand customer sentiment.
- Dropshipping teams use it to validate demand signals, so they can reduce product risk.
Does this scraper work on all Groupon country sites? Yes, it supports all Groupon subdomains, including regional marketplaces like .fr, .de, and .co.uk.
Can it scrape both category pages and individual deals? It supports category listings, search result pages, and direct deal URLs.
Is review data always available? Review availability depends on the merchant and deal type. Some listings may have limited or no reviews.
How stable is the extracted data format? Fields are normalized and consistent, but availability may vary due to regional or listing-specific differences.
Primary Metric: Processes 1,000–1,500 product listings per hour depending on page complexity.
Reliability Metric: Maintains a 97% successful extraction rate across supported marketplaces.
Efficiency Metric: Optimized pagination and request handling keep memory usage stable under sustained loads.
Quality Metric: Captures over 95% of visible product and merchant fields on standard deal pages.
"Bitbash is a top-tier automation partner, innovative, reliable, and dedicated to delivering real results every time." Nathan Pennington
|
"Bitbash delivers outstanding quality, speed, and professionalism, truly a team you can rely on." Eliza
|
"Exceptional results, clear communication, and flawless delivery. Syed
|