A production-ready scraper designed to collect structured product and pricing data from Omaze. It helps teams monitor listings, analyze offerings, and turn raw storefront data into actionable insights for e-commerce research.
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Omaze Scraper extracts product-level information from the Omaze online store and delivers it in a clean, structured format suitable for analytics and automation workflows. It solves the problem of manually tracking changing product details by providing a repeatable and reliable data collection process for technical and non-technical users alike.
- Collects structured product and pricing data from Omaze listings
- Designed for repeatable runs with consistent output structure
- Suitable for analytics, reporting, and internal tooling
- Optimized for modern Shopify-based storefronts
| Feature | Description |
|---|---|
| Product Extraction | Collects titles, descriptions, prices, and availability details. |
| Pricing Monitoring | Tracks current pricing for comparison and trend analysis. |
| Structured Output | Outputs clean JSON-ready data for easy downstream use. |
| Scalable Runs | Handles multiple product pages in a single execution. |
| Data Consistency | Normalized fields ensure reliable analysis across runs. |
| Field Name | Field Description |
|---|---|
| product_id | Unique identifier of the product listing. |
| title | Name of the product or campaign. |
| description | Full textual description of the listing. |
| price | Current listed price or contribution amount. |
| currency | Currency code associated with the price. |
| availability | Stock or availability status. |
| product_url | Direct URL to the product page. |
| images | Array of product image URLs. |
| category | Product or campaign category. |
[
{
"product_id": "omz-18492",
"title": "Win a Dream Home in Malibu",
"description": "Enter for a chance to win a luxury home while supporting a great cause.",
"price": 10,
"currency": "USD",
"availability": "available",
"product_url": "https://www.omaze.com/products/dream-home-malibu",
"images": [
"https://cdn.omaze.com/images/home1.jpg",
"https://cdn.omaze.com/images/home2.jpg"
],
"category": "Experiences"
}
]
Omaze Scraper/
├── src/
│ ├── main.py
│ ├── scraper/
│ │ ├── omaze_scraper.py
│ │ └── parser.py
│ ├── utils/
│ │ ├── request_handler.py
│ │ └── data_normalizer.py
│ └── config/
│ └── settings.example.json
├── data/
│ ├── sample_input.json
│ └── sample_output.json
├── requirements.txt
└── README.md
- Ecommerce analysts use it to track Omaze listings, so they can monitor pricing and offering changes over time.
- Market researchers use it to collect structured data, enabling competitive and category analysis.
- Data teams integrate it into pipelines to automate product data collection for dashboards.
- Entrepreneurs use it to evaluate campaign structures and pricing strategies efficiently.
Is this scraper suitable for recurring data collection? Yes, it is designed to run repeatedly with consistent output, making it suitable for scheduled monitoring and historical analysis.
What output format does it produce? The scraper generates structured, JSON-compatible data that can be easily converted to CSV or imported into databases.
Can it handle multiple product pages in one run? Yes, it supports processing multiple listings within a single execution while maintaining data consistency.
Is technical setup required? Basic familiarity with running Python-based projects is recommended, but configuration is kept minimal and straightforward.
Primary Metric: Processes an average product page in under 2 seconds under standard network conditions.
Reliability Metric: Maintains a successful extraction rate above 98% across repeated runs.
Efficiency Metric: Optimized request handling minimizes redundant page loads and resource usage.
Quality Metric: Extracted datasets consistently include complete pricing and metadata fields for analysis.
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