Improving Product Discovery
Using iterative experimentation to reduce friction across a complex ticket-purchase journey.
Role:
Senior UX/UI Designer / Creative Lead
Focus:
Growth Design · Conversion Optimization
Tools:
Figma, Adobe Target, Adobe Analytics
Overview
Turning a winning interaction into a broader product-discovery strategy
A mobile ticket-store experiment explored whether making filters a mandatory step before displaying ticket options could help guests make more informed choices and move more efficiently through a complex purchase journey. The winning experience significantly increased orders and revenue per visitor, creating a behavioral insight that we later extended deeper into the funnel and are now adapting for another destination.
Problem
Ticket shopping presents guests with a large number of products, eligibility rules, and configuration choices. Although filtering tools were available, guests could bypass them and immediately encounter a dense product set, increasing the effort required to understand which options were most relevant. The opportunity was not simply to redesign the filters, but to test whether introducing decision support earlier in the journey could improve product discovery and ultimately influence conversion.
Solution
I helped refine an existing opportunity into a testable hypothesis and designed the variation using interaction patterns already established in the ticket store. Rather than introducing a new filtering model, I intentionally preserved familiar patterns so the experiment could focus on the impact of when guests encountered the filters, not whether they could understand a new interface. The experience was handed off to our eCommerce and Commerce UX/UI partners for implementation. The test produced a statistically significant lift in orders and increased revenue per visitor. Rather than treating the result as an isolated win, we used the learning as the basis for additional experiments elsewhere in the purchase journey.
