DATA SOLUTION
Build Structured Product Datasets Across Marketplaces and Retailers.
Build structured product datasets across marketplaces, retailers, brands, and online stores.
THE CHALLENGE
Getting reliable product data from the web is harder than it looks.
Fragmented catalogs
Product information is distributed across marketplaces, brand websites, retailer stores, and niche platforms, each with its own structure and fields.
Changing page structures
Product pages, category layouts, and attribute listings change frequently, breaking brittle scrapers.
Inconsistent attributes
The same attribute is named, formatted, or structured differently on every source, making cross-source comparison difficult.
Variant complexity
Products with multiple sizes, colors, capacities, or models require careful handling to avoid creating incorrect records.
Duplicate listings
The same product appears under different IDs, sellers, or titles across platforms, requiring deduplication logic.
Image and media variance
Product images differ in size, format, and completeness across retailers, requiring normalization.
THE MYDATASCRAPER APPROACH
From fragmented web pages to structured business intelligence.
MyDataScraper collects product information from the sources you select, then parses, validates, and normalizes it into one consistent schema — with variant handling, category mapping, and image capture built in — so your team works with comparable records instead of raw pages from a dozen different retailers.
What you can build with Product Data Solutions.
Product attributes
Extract brands, categories, specifications, sizes, variants, and other structured fields.
Pricing
Capture current prices, MRP, discounts, and currency information where available.
Variants
Handle size, color, capacity, model, and packaging variants without creating incorrect records.
Availability
Monitor stock indicators and availability status where exposed by the source.
Images & media
Capture product images, gallery images, and media URLs for enrichment.
Ratings & reviews
Collect review counts, average ratings, and top review snippets where available.
Category mapping
Normalize disparate category structures into a single unified taxonomy.
Seller information
Capture seller or vendor details when the marketplace exposes them.
Historical snapshots
Track product and price changes over time for trend analysis.
Multi-source normalization
Combine records from multiple retailers into one comparable dataset.
Build the dataset around your required fields.
| FIELD | EXAMPLE |
|---|
Available fields depend on the source website and specific use case.
Collect data from the sources your business depends on.
MARKETPLACES
- Retail platforms
- Online marketplaces
- Specialized marketplaces
RETAILERS
- Online stores
- Brand websites
- Retail catalogs
NICHE PLATFORMS
- Specialty stores
- Regional retailers
- Direct-to-consumer brands
REVIEW PLATFORMS
- Review websites
- Consumer forums
- Rating aggregators
Sources can be evaluated based on your target data and collection requirements. Not every website can be supported.
A data workflow designed around your requirements.
-
01
Define
Identify sources, fields, locations, filters, and update frequency.
-
02
Extract
Collect relevant information from the selected sources.
-
03
Structure
Normalize fields and standardize records.
-
04
Validate
Check records, remove duplicates, and apply quality controls.
-
05
Deliver
Send data through the selected delivery method.
Receive your data the way your systems need it.
How frequently can the data be updated?
One-Time
A single dataset delivered once.
Daily
Refreshed every day.
Weekly
Refreshed every week.
Scheduled
Custom intervals you define.
Near Real-Time*
Where the source and workflow allow.
*Update frequency depends on source availability, technical requirements, and the specific workflow.
What businesses use this data for.
Catalog management
Build and maintain large structured product catalogs.
Competitive assortment
Compare product ranges and attributes across brands and retailers.
Pricing intelligence
Monitor product pricing and historical changes across sources.
Marketplace aggregation
Feed structured listings into a marketplace or comparison platform.
PIM & ERP enrichment
Fill gaps in internal product information management systems.
AI & data science
Create structured product datasets for machine learning and analysis.
Review intelligence
Analyze consumer feedback and rating patterns across products.
Reporting & dashboards
Power internal BI dashboards with refreshable product data.
Built for teams across data-intensive industries.
API DELIVERY
Put product data solutions directly into your application.
Access structured data through an API instead of maintaining extraction infrastructure yourself.
Illustrative example only. Endpoints and fields are defined per project.
GET /api/products? category=headphones brand=example
{
"name": "Wireless Headphones",
"brand": "Example Brand",
"sku": "WH-210-BLK",
"category": "Electronics > Audio > Headphones",
"price": 2499,
"mrp": 3999,
"discount": 37,
"availability": "in_stock",
"rating": 4.5,
"review_count": 1284,
"variants": [
"Black",
"White",
"Blue"
],
"primary_image": "https://example.com/img1.jpg",
"captured_at": "2026-10-02T09:00:00Z"
}
See the data before you build around it.
Review a sample dataset to understand the structure, fields, and level of detail available for your use case.
| PRODUCT | BRAND | CATEGORY | PRICE | RATING | AVAILABILITY |
|---|---|---|---|---|---|
| Wireless Headphones | Example | Electronics > Audio | ₹2,499 | 4.5 | In stock |
| Running Shoes M | Example | Footwear > Sports | ₹3,299 | 4.3 | In stock |
| Air Fryer 4L | Example | Home > Kitchen | ₹5,999 | 4.4 | Low stock |
| Office Chair Mesh | Example | Furniture > Office | ₹8,499 | 4.2 | In stock |
| Smartwatch Pro | Example | Electronics > Wearables | ₹12,999 | 4.6 | In stock |
More than extraction.
Data engineering
Design workflows around your actual data requirements.
Structured output
Receive consistent and analysis-ready datasets.
Custom workflows
Choose sources, fields, frequency, and delivery around your use case.
Ongoing data operations
Support recurring workflows as source structures and requirements evolve.
Frequently asked questions.
What product data can be collected?
Product name, brand, SKU, category, price, MRP, discount, availability, ratings, reviews, seller information, product attributes, variants, images, and source URLs — depending on what each source exposes.
Which websites can you collect product data from?
Sources can be evaluated based on your target data and collection requirements. Share the marketplaces, retailers, or brand websites you have in mind and we will assess feasibility.
Can you handle products with variants?
Yes. Variants such as size, color, capacity, and model are handled as structured child records rather than separate duplicate products.
How do you handle duplicate listings?
We apply deduplication logic using SKU, GTIN, brand, product name, and other identifiers to merge duplicate records into a single clean entry.
Can categories be normalized to my taxonomy?
Yes. Product categories from multiple sources can be mapped to a unified taxonomy that matches your internal structure.
Can I receive images along with product data?
Yes. Product images and media URLs can be captured and delivered alongside the structured record, either as direct URLs or stored in cloud storage.
What output formats are available?
JSON, CSV, Excel, database delivery, scheduled feeds, cloud storage, or a custom integration.
Can I receive the data as an API?
Yes. Data can be delivered through a REST API designed around your application, search, or dashboard needs.
How often can the data be updated?
Workflows can run daily, weekly, monthly, or on custom schedules depending on the source and your requirements.
Can you build historical product datasets?
Yes. Recurring workflows build a history of product, price, and availability changes over time.
Can you provide a sample dataset?
Yes. Request a sample to review the structure, fields, and level of detail for your use case.
How do you handle website changes?
Recurring workflows are maintained and adjusted as source structures change so delivery keeps matching your requirements.
Build the Product Data Solutions workflow your business needs.
Tell us what data you need, which sources matter, how often it should be updated, and how you want to receive it.
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