Datos listos para IA y búsqueda vectorial para el descubrimiento de productos. Minorista de azulejos y acabados de EAU.
Catálogo listo para IA + búsqueda vectorial que reduce el tiempo de búsqueda en un 70% y aumenta la conversión hasta en un 15%. Transformamos el catálogo de productos de un minorista de azulejos de e-commerce en datos estructurados listos para IA, lo que permite la búsqueda vectorial y recomendaciones de productos conversacionales. Anteriormente, los clientes tenían dificultades para buscar manualmente en grandes catálogos de SKU. La nueva experiencia de IA redujo el tiempo de búsqueda en un 60-70%, aumentó la conversión en un 10-15% y mejoró los ingresos interanuales en un 8-12%.
01 —The Impact
The results, up front.
60–70% reduction in search time Conversion increased by 10–15% YoY revenue grew 8–12% Support workload reduced by 30–40% A significantly upgraded purchasing journey
02 — The Challenge
Where they started.
Large tile retailers rely heavily on SKU accuracy and searchability. Customers searching manually encountered friction that slowed decision-making and hurt conversion. Our objective was to turn the catalog into AI-ready data and build a conversational product discovery flow. We began by cleaning and structuring product data, then vectorizing it for similarity search. We implemented embedded vector search that allowed customers to find matching items via chat, natural language, or visual cues. The AI generated product cards with actionable CTAs, comparisons with similar SKUs, and dynamic item lists. This dramatically accelerated decision-making and created an intuitive “assistant-like” experience.
04 — Approach & Methodology
How we got there.
Customers previously spent far too long searching for tiles, often abandoning sessions. With vector search, the system instantly understood intent and surfaced the most relevant SKUs — reducing friction and enabling faster purchase decisions. AI cards and comparison tools addressed uncertainty by helping users evaluate alternatives quickly.
05 —In Practice
Project samples.
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