Versori’s One-Click Catalogue Sync lets merchants transfer products between marketplaces with 98% accuracy, saving time and eliminating data mismatches.
In today’s interconnected e-commerce world, seamless product data transfer between marketplaces is no small feat. As businesses expand across platforms, they face a complex challenge: every marketplace speaks its own “data language.”
“The customer’s trying to import their product from one marketplace to the other, and it’s a very big problem,” says Dipit, Senior AI Engineer at Versori. “Different marketplaces have different taxonomies, different data types, and they expect different values. That’s a huge problem when it comes to integration.”
A product catalog from Marketplace A often cannot be directly imported into Marketplace B. Each platform may label product attributes differently, require specific formats, or restrict values to certain predefined lists. Without an automated solution, businesses face tedious, error-prone manual data mapping, slowing expansion and risking lost sales.
Versori’s approach tackles the problem head-on with a one-click integration system. Their technology allows a complete catalog to be transferred from a source marketplace to a target marketplace with up to 98% accuracy, a level already proven with retail giant Walmart.
The process relies on several AI-powered components:
The workflow follows three streamlined steps:
The results speak for themselves: over 3,000 users have already adopted Versori’s catalogue sync solution, processing millions of SKUs in real time. The platform’s scalability ensures it can handle massive data volumes without performance degradation, a crucial requirement for enterprise-level retail operations.
“That’s really a testament to the solution we’ve delivered and our platform, which is able to handle all these requests coming in,” Dipit notes.
As marketplaces continue to proliferate, solutions like Versori’s will be essential for retailers who want to move fast, stay accurate, and expand globally without getting lost in the complexity of data integration.