Overview
In response to user feedback indicating difficulties in navigating our clothing collections on The Ensemble, I led the design of AI-powered filters to improve product discovery. This initiative introduced advanced filtering options such as style, occasion, and weather, resulting in an 84% increase in filter adoption rates.
Problem Statement
Users reported challenges in finding desired garments due to limited and confusing filter and sort functionalities. The existing system offered basic categorizations like "Dresses," "Tops," and "Bottoms," with sort options that lacked clarity and relevance, such as unclear "Featured" option and unordinary sort options, like brand names and colors, which were sorted alphabetically.
Project Role
As the lead Product Designer, I was responsible for analyzing user interview results to identify user pain points and designing and prototyping the integrated sort and filter interface.
Process
Research and Insights
Qualitative user interviews revealed that the existing filters and sorting mechanisms were inadequate, leading to difficulties in product discovery. Users expressed the need for more intuitive and meaningful ways to navigate collections.
Collaboration with Data and Engineering
Concurrently, our data and engineering teams were developing algorithms to classify inventory using AI. This technology enabled the categorization of garments by occasion, season, style, and weather suitability.
Design Solution
Integrating user feedback and AI capabilities, I designed a unified sort and filter interface accessible via a single button, opening a drawer with comprehensive options.
The user is now able to sort by price, addressing users' price sensitivity, and filter by occasion, style, length, and weather in addition to size, color, and brand.
Outcome
The implementation of AI-powered filters led to an 84% increase in filter adoption rates and enhanced product discovery, contributing to higher conversion rates.
Continuing the utilization of CaaStle's AI and improving user experience, my colleague Connie Mach designed the AI-powered search function on The Ensemble.
