PD
Product data
Product names, IDs or SKUs where public, brands, categories, descriptions, specifications, attributes, variants, images and product URLs.
E-commerce data intelligence
AI-powered eCommerce web scraping & product data extraction
Turn public eCommerce data into structured, actionable intelligence for pricing, product research, competitor monitoring, assortment analysis and market insight.
We build custom extraction workflows for publicly available product, price, availability, seller, rating and review data—then organize it around the fields your business needs.
From public pages to useful data
What is eCommerce data scraping?
eCommerce data scraping is the structured collection of publicly available information from online stores and marketplaces. Instead of repeatedly checking product pages by hand, your team receives a consistent dataset that can support commercial, research and operational decisions.
Cigma combines tailored extraction logic with AI-assisted mapping and validation where appropriate. The goal is not more raw data; it is a dependable dataset that fits your product taxonomy, analysis workflow and delivery requirements.
eCommerce data we extract
Build the dataset your team actually needs
Every project begins with a data-field map. We collect only fields that are publicly available and relevant to your use case, then normalize them into an agreed structure.
PR
Pricing data
Current and original price, sale price, discount, currency, public promotions, coupons and price-history inputs where available.
AV
Availability data
In-stock or out-of-stock status, public inventory signals, delivery information and store availability where exposed.
SL
Seller data
Seller names, public seller ratings, offer counts and marketplace offer relationships relevant to a product or category.
RV
Review data
Ratings, review counts, public review text and dates, rating distributions and recurring themes for analysis.
CT
Catalog data
Category hierarchy, product and brand assortment, new listings, discontinued items and product variations.
From data to decisions
eCommerce intelligence use cases
The same public data can solve different business questions. We define the collection and output around the decision your team needs to make.
PI
Competitive price intelligence
Monitor public competitor prices, promotions and discounts to give pricing teams a current market reference.
PT
Product intelligence
Follow product catalogs, specifications, brand presence and product-page changes across selected sources.
DS
Digital shelf monitoring
Understand how products appear across retailers and marketplaces, including availability and visible content signals.
AS
Assortment intelligence
Compare product range, availability and brand assortment across competitors, categories or regions.
RI
Review intelligence
Analyze public ratings and review themes to identify customer feedback patterns and potential product issues.
SI
Seller intelligence
Track public marketplace offers and seller-facing signals to support competitive positioning analysis.
AI-powered extraction
A more structured route from page to dataset
AI can help identify page context, map relevant values to defined fields and validate data against agreed rules. We use it as part of a practical workflow—not as an unsupported promise of fully autonomous collection.
- Understand the source and required field structure
- Extract relevant publicly available information
- Validate, normalize and remove duplicates where required
- Structure records to match your agreed schema
- Deliver data in the format and frequency you need
Public web sources
Custom workflows for eCommerce websites and marketplaces
We can assess public eCommerce websites and marketplaces based on your source list and data requirements. Source feasibility, public availability and project constraints are reviewed before delivery is committed.
Relevant sources may include large marketplaces, retailer sites, brand stores, Shopify stores, WooCommerce stores and shopping comparison sites. We do not claim support for a platform until the required workflow has been assessed.
Who uses this data
Useful across retail and research teams
- Retail brands, manufacturers and D2C businesses
- Retailers and online marketplaces
- Consumer packaged goods and pricing teams
- Market research and consulting firms
- Advertising agencies and product intelligence platforms
- Investment and research organizations
Flexible delivery
Get eCommerce data in the format you need
Your delivery method should fit the people and systems using the data. We can prepare structured outputs for on-demand or scheduled delivery.
- CSV, Excel, JSON and XML files
- API or database-ready delivery
- Cloud storage and custom data feeds
- One-time datasets or scheduled updates
- Field normalization based on your schema
How Cigma works
A transparent eCommerce data workflow
01
Define requirements
Share the public sources, products, fields, geographic scope and update frequency that matter to your team.
02
Design the workflow
We assess source feasibility and configure an extraction and data-structure approach for the agreed scope.
03
Extract and validate
Public information is collected, normalized and checked against the data rules defined for the project.
04
Deliver the dataset
Receive a sample or feed in the agreed format so your team can begin using the information.
05
Monitor and update
For recurring needs, the workflow can be maintained and run according to an agreed schedule.
06
Refine as you learn
Add or refine fields as your commercial, research or product questions evolve.
Explore more data intelligence
Related AI-powered web scraping solutions
Explore the broader service hub or the industry-specific data solutions that may support your next research or commercial project.
Service hub
AI-powered web scraping services for custom public-web data collection, validation and delivery.
Industry intelligence
Travel & tourism, food delivery, entertainment and finance data.
More markets
Jobs & recruitment, news & media and real estate intelligence.
Frequently asked questions
eCommerce web scraping FAQs
What is eCommerce web scraping?
It is the structured collection of publicly available product, price, availability, seller and review information from online stores and marketplaces.
Can you collect data from multiple websites?
Yes. We can scope a custom workflow around relevant public sources, fields and refresh frequency.
Can you track public prices and discounts?
Yes, where the source exposes them publicly. The precise fields are confirmed during source and feasibility review.
Can data be delivered through an API?
Yes. API, JSON, CSV, Excel, database and cloud-storage delivery options can be planned around your workflow.
How often can data be updated?
Update frequency is agreed during scoping and depends on the data need, source behavior and project requirements.
Is eCommerce web scraping legal?
Each project should be assessed individually. We focus on publicly available information while considering applicable laws, privacy requirements, contractual restrictions and website terms.