A significant amount of ecommerce information is confined within closed platforms or filtered through merchant feeds, leading to sellers selectively showcasing what they want to present. Extralt, however, provides access to the actual data that exists.
Our system retrieves structured product information from any ecommerce platform, standardizes it into a universal format, and identifies identical products across different sellers. This process unfolds in four distinct phases: Extract, which crawls various sites to generate consistent structured data; Enrich, which translates product details into English, categorizes using the Shopify taxonomy, highlights specific attributes, and aligns products from different sellers; Extend, which identifies the same product across multiple sites, uncovers alternatives, and connects related items; and Explore, which allows users to search, compare prices, and perform analytics on the entire data set. Users are charged for the Extract and Enrich phases, while the Extend and Explore functionalities are offered at no cost.
We developed our extraction engine because scraping ecommerce sites can be extremely challenging to maintain. Conventional scrapers often fail when there are changes in site layouts, while AI-driven scrapers, although flexible, can be prohibitively expensive to implement across every page. Therefore, our solution not only ensures reliability but also enhances accessibility to crucial data.