In modern eCommerce, product discoverability remains one of the most critical — and often underestimated — drivers of customer experience. This presentation explores how taxonomy and semantic structures can be transformed from a backend necessity into a strategic enabler of findability and scalability.
Using zooplus as a case study, the talk begins with a legacy landscape characterized by fragmented taxonomies, inconsistent product classification, duplicated and ambiguous categories, and a heavily manual attribute assignment process. These limitations not only reduced operational efficiency but also created friction in navigation and filtering, ultimately impacting the customer experience.
The session then walks through the transition toward a unified taxonomy, introducing standardized classification layers such as “animal product type” to create clearer and more consistent product grouping across categories. In parallel, facet and filter structures are re-engineered to better reflect how customers search and navigate, improving attribute consistency, reducing ambiguity, and enabling more intuitive discovery paths.
Beyond immediate improvements, the initiative also focuses on preparing the taxonomy for the next generation of commerce. By strengthening semantic foundations, the model is designed to support AI-driven and agentic commerce scenarios, where structured, high-quality data becomes essential for powering intelligent recommendations, conversational interfaces, and automated decision-making.
The presentation will highlight how semantic thinking can effectively bridge the gap between complex data systems and real user behaviour, and how a well-designed unified taxonomy can significantly improve both customer experience and operational scalability.