面向产品发现的AI就绪数据和向量搜索。阿联酋瓷砖和装修零售商。
AI 就绪目录 + 向量搜索，可将搜索时间缩短 70%，转化率提高 15%。我们将一家电商瓷砖零售商的产品目录转换为 AI 就绪的结构化数据，从而实现了向量搜索和对话式产品推荐。客户以前很难手动搜索大型 SKU 目录。新的 AI 体验将搜索时间缩短了 60-70%，转化率提高了 10-15%，年收入增长了 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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