Dados Prontos para IA e Busca Vetorial para Descoberta de Produtos. Varejista de Azulejos e Acabamentos dos Emirados Árabes Unidos.
Catálogo pronto para IA + busca vetorial que reduz o tempo de busca em 70% e aumenta a conversão em até 15%. Transformamos o catálogo de produtos de um varejista de pisos e revestimentos em dados estruturados prontos para IA, possibilitando busca vetorial e recomendações de produtos conversacionais. Os clientes antes tinham dificuldade em buscar manualmente em grandes catálogos de SKUs. A nova experiência de IA reduziu o tempo de busca em 60–70%, aumentou a conversão em 10–15% e melhorou a receita ano a ano em 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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