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Digital Experience Optimization Case Study
Improving Digital Experiences Through Data & Testing
Using behavioral data and structured testing to find and fix the friction points costing sales across a fast-moving gameday storefront.
Project Overview
| Project | Digital Experience Optimization |
| Organization | Hawkeye Fan Shop, The Official Retailer of the University of Iowa Athletics Department |
| Focus | User Behavior Analysis, Experimentation, Conversion Optimization |
| Outcome | Data-backed experience improvements that reduced friction and lifted conversion during peak demand |
The Challenge
A working storefront with reliable data still leaves an open question: is the experience actually working for the people using it? With traffic spiking hard around gameday, roster changes, and postseason runs, even small friction points - a confusing filter, a slow checkout step - get multiplied across a much larger audience than usual.
Key challenges included:
- No structured way to see where fans were hesitating, stalling out, or abandoning a purchase
- Traffic patterns that shift sharply around gameday, making "typical" behavior hard to define
- A mix of new and returning fans with very different levels of familiarity with the storefront
- Pressure to make experience changes with confidence rather than guesswork, given the volume at stake
- A need to validate changes before rolling them out broadly during a live season
The Approach
Rather than redesigning based on assumptions, the work started with watching how fans actually moved through the storefront and testing changes against that evidence.
- Behavioral Analysis
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Reviewed session activity, funnels, and engagement patterns to find exactly where fans hesitated, stalled out, or clicked away.
- Friction Identification
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Pinpointed specific pages and steps - filters, cart, and checkout - where drop-off was highest relative to traffic.
- Structured Experimentation
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Ran controlled tests on proposed changes so decisions were based on measured impact rather than opinion.
- Gameday-Aware Rollouts
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Timed validated changes around the sports calendar so updates landed without disrupting high-traffic windows.
The Solution
A structured, evidence-based process for improving the storefront experience now runs continuously, catching friction points before they cost meaningful sales.
| Capability | Impact |
|---|---|
| Behavioral Insight | Clear visibility into exactly where fans hesitate or abandon a purchase. |
| Structured Testing | Experience changes validated against measured impact before wide rollout. |
| Gameday-Ready Rollouts | Improvements timed to land without disrupting peak traffic windows. |
The Results
With behavioral insight and structured testing driving experience decisions, store and web performance have improved, gameday traffic has been handled without the site buckling under peak demand, and conversion has trended upward across departments over the course of the partnership.
- Friction points identified and addressed using measured behavioral data
- Gameday traffic handled reliably at peak demand
- Upward conversion trends across departments
- An experience optimization process supporting ongoing email campaigns for gameday information, product drops, and student-athlete appearances
Approach & Capabilities
- User Behavior Analysis
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Session activity and funnel analysis used to pinpoint exactly where the experience breaks down.
- Experimentation & Validation
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Structured, data-driven testing used to confirm a change actually improves the experience before it ships broadly.
- Conversion Optimization
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Targeted improvements to the specific steps costing the most conversions.
- Continuous Improvement
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An ongoing process for revisiting the experience as fan behavior and the sports calendar shift.
Business Impact
A storefront that collects data is not the same as one that improves because of it. Watching how fans actually move through the site and validating changes before rolling them out turned behavioral data into real gains in the experience, particularly during the highest-traffic stretches of the season.
Through behavioral analysis, structured experimentation, and gameday-aware rollouts, this initiative created an ongoing optimization process that has supported the partnership with Hawkeye Fan Shop and the University of Iowa Athletics Department since 2016.
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