Case Study: Leading Fashion Product Company achieves hyper-personalized fashion recommendations with Quantiphi

Developing a custom fashion recommendation system using Computer Vision

Leading Fashion Product Company partnered with Quantiphi to build a more personalized shopping experience for retail websites. The customer’s challenge was to create a universal shopper profile for fashion products despite sparse purchase history, limited product metadata, multiple retailer data sources, and rapidly changing fashion trends.

Quantiphi developed an AI-powered fashion recommendation system using computer vision, deep CNN embeddings, Siamese networks, and multimodal ML on Google Cloud services. The solution delivered hyper-personalized “Similar Recommendations” and “Complete the Look” suggestions, improving retailer conversion rates and boosting user engagement through better cross-selling.