PUMA Website Experience
Usability, interaction, CRO and personalization
Role
As a Conversion Strategist and Owner, I lead cross-functional teams in executing A/B tests, analyzing user behavior, and implementing UX enhancements that deliver measurable conversion improvements.
Context
Working Framework
Team
UX/UI Designers, Researchers, Data Analysts, Software Engineers
Tools
Dynamic Yield, Google Analytics, MS Clarity, Figma, Jira
Strategy
Marginal gains — break down each stage of the funnel into goals, measure and optimize for them. Make decisions based on individual page goals (indicator metrics). Monitor transactions and revenue.
Focus
Usability, UX design, and personalization
Objective
Maximize the performance of each step in the funnel
Flagship Test
Fit Predictor (Turkey)
Stage
Post-add-to-cart / pre-purchase confidence
Scope
PUMA Turkey online store, new customers, desktop + mobile
My Role
Identified sizing-driven returns as the top return-reason via return data and customer feedback analysis; scoped the third-party integration with engineering; defined the test segmentation (new customers only) and success metrics with the data analyst.
Problem
Footwear returns were above average, driven primarily by sizing issues identified in customer feedback.
Hypothesis
Adding a personalized size recommendation will reduce size-related uncertainty, resulting in higher conversion and lower return rates.
Test
A/B test deploying Fit Predictor (a third-party size-prediction tool) to give new customers personalized size recommendations at the PDP. The control group shopped without assistance.
Results
Run over [X weeks], [X]% statistical confidence, n = [X] sessions
Fit Predictor recommendation on the PDP
Outcome / Next Step
Based on these results, Fit Predictor was recommended for [global rollout / expansion to additional markets].
Web Experience Optimization
Search Fly-out
Stage
Search & discovery
Scope
[Global / region], desktop + mobile
My Role
Reviewed Clarity session recordings to identify friction in the search fly-out; proposed the simplified variant with UX design; ran the test and analyzed engagement data.
Hypothesis
Simplifying the search fly-out by removing extra elements will help users stay focused on the task, reducing cognitive load and encouraging engagement with search results.
Test
A/B test comparing the existing fly-out against a simplified version with non-essential elements removed.
Results
Run over [X weeks], [X]% statistical confidence
Simplified search fly-out — winning variant
Outcome / Next Step
[What happened after — did it ship, inform other pages, etc.]