AI Curtain Recommendation Engine
Interior Design
Project Overview
Online curtain shopping suffers from a visualization problem - customers can't confidently choose colors and styles without seeing how they'll look in their specific room lighting and decor. This AI-powered recommendation engine analyzes room photos to understand lighting conditions, existing color schemes, and spatial characteristics, then suggests curtain options that will look perfect in that specific environment.
The Challenge
Online curtain sales suffer from high return rates because customers can't accurately predict how fabrics will look in their rooms. Color perception varies dramatically between computer screens and real room lighting, while style choices depend on room proportions and existing decor that customers struggle to communicate. Expensive returns hurt both customer satisfaction and retailer profitability.
Solution
Created an intelligent visual analysis system while at Into The Source that processes room photos to understand lighting conditions, color palettes, and spatial characteristics. The AI recommends curtain styles and colors that complement the existing decor while accounting for natural and artificial lighting effects. Customers receive confident purchase recommendations backed by visual analysis, dramatically reducing returns while increasing customer satisfaction and conversion rates.