DATA SOLUTION
Build Structured E-Commerce Data at Scale.
Product catalogs, pricing, availability, reviews, categories, brands, and marketplace intelligence.
THE CHALLENGE
Getting reliable e-commerce data from the web is harder than it looks.
Fragmented product sources
Product information is distributed across marketplaces, retailers, and brand websites.
Changing structures
Website layouts, product pages, categories, and data structures change over time.
Inconsistent data
Different websites use different names, formats, currencies, and attributes.
Manual monitoring
Teams cannot efficiently monitor thousands of products manually.
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 so your team works with comparable records instead of raw pages.
What you can build with E-Commerce Data Solutions.
Product catalogs
Collect structured product information across online sources.
Pricing
Capture current prices, MRP, discounts, and promotional information where available.
Availability
Monitor product availability and stock indicators where exposed.
Reviews & ratings
Collect review and rating information.
Product attributes
Extract brands, categories, specifications, sizes, variants, and other fields.
Images & URLs
Capture product images and source URLs.
Location data
Support location-specific or regional collection where applicable.
Historical data
Build recurring collection workflows for trend analysis.
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
REVIEW PLATFORMS
- Review websites
- Business directories
- Consumer platforms
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.
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03
Structure
Normalize fields and standardize records.
-
04
Validate
Check records, remove duplicates, and apply quality controls.
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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.
Competitor monitoring
Compare product and market changes across competitors.
Market research
Analyze categories, pricing, and market activity.
Business intelligence
Feed structured data into internal analytics.
Catalog management
Build and maintain large product catalogs.
Price intelligence
Monitor market pricing and historical changes.
AI & data science
Create structured datasets for analysis and modeling.
Built for teams across data-intensive industries.
API DELIVERY
Put e-commerce 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? keyword=headphones location=india
{
"name": "Wireless Headphones",
"brand": "Example",
"price": 2499,
"rating": 4.5,
"availability": true
}
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 | PRICE | MRP | RATING | AVAILABILITY |
|---|---|---|---|---|---|
| Wireless Headphones | Example | ₹2,499 | ₹3,999 | 4.5 | In stock |
| Running Shoes M | Example | ₹3,299 | ₹4,499 | 4.3 | In stock |
| Air Fryer 4L | Example | ₹5,999 | ₹8,999 | 4.4 | Low 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 data can be collected?
We can collect product names, brands, SKUs, prices, MRP, discounts, availability, ratings, reviews, categories, images, and other fields, depending on what each source exposes.
Which websites can you collect data from?
Sources can be evaluated based on your target data and collection requirements. Share the websites you have in mind and we will assess feasibility.
Can I specify custom fields?
Yes. The dataset is built around the fields you need, subject to what the source provides.
Can the data be updated automatically?
Yes. Recurring workflows can run on daily, weekly, or custom schedules. Near real-time updates depend on the source and workflow.
What formats can I receive?
JSON, CSV, Excel, database delivery, scheduled feeds, cloud storage, or a custom integration.
Can you provide an API?
Yes. Data can be delivered through an API designed around your application needs.
Can you collect data for multiple locations?
Yes, where the source supports location-specific results.
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 E-Commerce 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.
Explore related solutions.
Product Data Solutions
Build structured product datasets across marketplaces, retailers, brands, and online stores.
Explore →Competitor Price Monitoring
Track competitor pricing, promotions, product availability, and catalog changes across digital channels.
Explore →Restaurant & Food Data
Build structured restaurant, menu, pricing, availability, location, and review datasets.
Explore →