Collect structured public web data from leading ecommerce platforms, marketplaces and digital sources. Start with one source or combine multiple platforms into a managed data pipeline built around the fields, refresh cadence and delivery format that fits your workflow.
Explore Kvetoiq’s current source coverage. Each source page explains the types of public data that can be collected, common business use cases and related solutions.
Product, pricing, seller, rating and availability data.
View Amazon Data Source →Product, pricing, category, seller and stock signals.
View Walmart Data Source →Structured product and storefront data from eligible stores.
View Shopify Data Source →Product, seller, price and social-commerce listing data.
View TikTok Shop Data Source →Marketplace product, pricing, seller and catalog data.
View Flipkart Data Source →Listings, seller, pricing, product condition and marketplace data.
View eBay Data Source →Listing, shop, pricing, rating and product attribute data.
View Etsy Data Source →Electronics pricing, specifications, reviews and availability.
View Best Buy Data Source →Furniture and home-product catalog, pricing and review data.
View Wayfair Data Source →B2B product, supplier, pricing and marketplace information.
View Alibaba Data Source →Product, price, seller, order and review signals.
View AliExpress Data Source →Electronics product, specification, seller and pricing data.
View Newegg Data Source →Marketplace product, pricing, merchant and listing data.
View Wish Data Source →Share the public website or platform, target fields and market. We can assess a custom collection approach.
Check My Data Source →Fields vary by source, but most projects combine several of these data groups into one structured schema.
Titles, IDs, brands, categories, specifications, variants and images.
Current prices, list prices, discounts, coupons and promotion signals.
Availability status, delivery signals, inventory indicators and fulfillment data.
Seller names, offer counts, fulfillment details and marketplace listings.
Ratings, review counts, review text and customer feedback signals where available.
Search result position, category placement, sponsored signals and share-of-search inputs.
Regional availability, store/location attributes and location-specific source variations.
Recurring collection for price, availability, seller and visibility trend analysis.
We are building the first sample datasets around five high-priority sources. Use the sample request to tell us which source and fields matter to your use case.
The source can change. The operating model stays consistent: define the fields, collect, validate, structure and deliver.
Share the websites, platforms or source pages relevant to your use case.
Map the exact attributes, identifiers, markets and refresh requirements.
Build and run the source-specific collection workflow.
Apply schema checks, normalize fields and flag quality issues.
Receive data through CSV, Excel, JSON, API or the agreed workflow.
Source coverage is only useful when the collected data is mapped to a decision, workflow or monitoring objective.
Track competitor prices, discounts and promotions across selected sources.
Explore Price Monitoring →Connect equivalent product listings across retailers and marketplaces.
Explore Product Matching →Measure content, availability and visibility signals across digital shelves.
Explore Digital Shelf →Monitor relevant pricing signals and surface potential policy exceptions.
Explore MAP Monitoring →Track how brands and products appear across marketplace search results.
Explore Share of Search →Monitor seller and listing signals that may require further review.
Explore Brand Protection →The directory above represents current published source pages, not the limit of what can be scoped. Share the website or platform, target fields, markets and expected cadence, and we can assess a custom collection approach.
Send the source URL and the fields you want. If a representative sample is practical, we can use that to define the next step.
Check My Data Source →Choose a managed service based on scale, delivery model and how the data will be used.
Managed collection and structured delivery from public web sources.
View Service →Purpose-built schemas and source-specific extraction workflows.
View Service →Monitored large-scale collection across broader source sets.
View Service →Programmatic access for data workflows that require API delivery.
View Service →Tell us the source, fields and business question. Start with a representative sample, then decide whether a larger managed data pipeline makes sense.
Share the platforms, categories, competitors, SKUs, regions, or business questions you care about. KVETOiQ will help define the right data strategy, output format, and operating cadence.
