Dairy Queen

Driving Digital Revenue Through Strategic, Insight-Led Experience Optimization


By leading a diverse set of research initiatives—from concept testing to real-world pilot programs—I helped shape features and experiences that were more aligned with user needs and better positioned to drive engagement and revenue.


Project Details

Duration: 18 months
Methods: Mixed methods (qual + quant), usability testing, card sorting, tree testing, surveys, diary studies, concept testing, pilot testing
Scope: Mobile app + website (end-to-end digital experience)

Over 18 months, I led a series of high-impact research initiatives to optimize Dairy Queen’s digital experience across web and mobile. By prioritizing research based on business impact and integrating insights across multiple methods, I helped identify and remove key UX barriers—driving improvements in digital ordering and supporting increased revenue.


Problem & Context:

Dairy Queen was investing in growing its digital ecosystem, but several friction points were limiting adoption and conversion.

Key challenges included:

  • Barriers in the digital ordering flow
  • Friction in core experiences like account creation and deal redemption
  • Opportunities to improve feature adoption and engagement
  • A need to better align digital experiences with user expectations and business goals

The opportunity: use UX research to directly influence product decisions and revenue outcomes.


Goals:

  • Increase digital sales and overall revenue
  • Reduce friction in core ordering flows
  • Improve feature usability and adoption
  • Identify and validate new feature opportunities
  • Ensure digital experiences aligned with user needs and business KPIs


My Role:

  • Led research strategy, prioritization, and execution across all initiatives
  • Defined and prioritized studies based on business impact and KPIs
  • Scoped and executed 12+ research initiatives end-to-end
  • Collaborated cross-functionally with design, analytics, and SEO teams
  • Synthesized insights into actionable, executive-ready recommendations
  • Presented findings to stakeholders and leadership


Improved key digital experiences to make ordering easier, faster, and more intuitive for users, increasing confidence and engagement across digital platforms.

Menu Navigation Optimization

Goal: Understand how users browse the menu and how structure impacts ordering behavior.


Approach:

  • Conducted card sorting and tree testing with 300+ participants (US & Canada)
  • Evaluated how users:
  • Group menu items
  • Navigate categories
  • Locate specific products


Key Insights:

  • Users relied on intuitive category groupings aligned with mental models
  • Existing structure made it difficult to quickly find items
  • Menu organization directly influenced ordering efficiency and success


Impact:

  • Informed a restructured menu architecture
  • Improved findability and browsing efficiency


Group Ordering Concept Testing

Goal: Evaluate a new feature concept enabling shared group ordering.


Approach:

  • Conducted qualitative interviews with 18 users across segments:
  • Families
  • Corporate orderers
  • Party planners
  • Tested wireframes and early concepts
  • Explored:
  • Feature expectations
  • Workflow preferences
  • Use case differences


Key Insights:

  • Different user groups had distinct needs and workflows
  • Corporate users prioritized efficiency and repeatability
  • Event planners needed flexibility and coordination tools
  • A single feature design would not serve all use cases effectively


Impact:

  • Recommended two distinct feature experiences:
  • A streamlined version for smaller, spontaneous group orders
  • A more robust flow for large, planned events
  • Helped ensure the feature would be more effective and scalable post-launch


Table Ordering Pilot Program

Goal: Evaluate a new QR-based table ordering feature before full rollout.


Approach:

  • Recruited users to test the feature in real restaurant environments
  • Collected feedback on:
  • Signage and discoverability
  • Messaging clarity
  • Ordering and checkout flow
  • Observed behavior in-context to understand real-world usage


Key Insights:

  • Feature was most valuable for:
  • Users avoiding lines
  • Convenience-focused customers
  • Success depended on:
  • Clear in-store communication
  • Simple, intuitive entry points into the experience


Impact:

  • Identified improvements to:
  • In-store signage and messaging
  • Checkout and flow clarity
  • Validated and refined the feature before full franchise rollout
  • Reduced risk and improved likelihood of successful adoption