Unifying Data and Models for Cross-domain Personalized Fashion Recommendations

Across industries, people have come to expect highly personalized and dynamic experiences - but for those providing them, managing extensive sets of data across various channels to ensure personalized touchpoints can be an incredibly complex task.

In this webinar, we will explore how Stitch Fix evolved its large suite of recommender models into a novel model architecture that unifies data from client interactions to deliver a holistic and real-time understanding of their style preferences. Stitch Fix’s Client Time Series Model (CTSM) is a scalable and flexible sequence-based recommender system that models client preferences over time, based on event data from various sources, to provide multi-domain, channel-specific recommendation outputs.

Data Science Manager, Kevin Zielnicki, will share how the model has enabled Stitch Fix to continuously provide personalized fashion at scale, like no other apparel retailer.