Evolving an E-commerce Product Finder for Decision Confidence
Sep 2, 2022

Project Overview
This case study details my work reshaping the product finder journey for a nationwide home goods e-commerce platform. The focus: empower users to find the right products quickly and with confidence, using pragmatic UX improvements informed by real user data.
Problem
Clickstream analysis showed users hesitated or bounced at early product selection steps, unsure which filters or comparisons to trust.
The existing finder provided too many options at once, resulting in filter overload and choice anxiety.
Business metrics indicated a drop in average basket size and lower engagement with personalized recommendations.
Process
Mapped user pain points through remote interviews and heuristic evaluation of the current system.
Tested progressive disclosure patterns—only showing advanced filters after core choices are made.
Introduced decision support tools, such as trust markers, social proof, and real-time feedback as users refined results.
Validated the redesign in a staged rollout with A/B testing and follow-up user interviews.
Decisions
Adopted user-centered copy and inline education to reduce filter intimidation and increase task confidence.
Reordered filtering controls based on frequency of use and purchase conversion data.
Balanced business interests (cross-sell, up-sell) with clear user-first interaction patterns to retain trust.
Outcomes / Learnings
Filter-to-purchase conversion ratio grew by 31% within the first two months.
User-reported decision confidence increased dramatically, with a marked drop in shopping cart abandonment.
Project demonstrated that reducing perceived complexity—without hiding powerful features—can drive tangible impact for both users and the business.