The strategic goal was to transform the post-purchase experience into a moment of brand reinforcement, not frustration. The objectives are to:

• Provide real-time, intuitive order visibility
• Support expectation management via clear delivery timelines
• Design for both the happy path and exception cases (e.g., delays, cancellations, lost packages)
• Reduce WISMO ("Where is my order?") inquiries to customer service
• Increase customer satisfaction and NPS

This project followed a user-centered, data-informed design approach, grounded in both strategic intent and real-world feasibility. Working closely with a cross-functional team including the product owner, tech lead, content designer, and UX researcher was the key factor for success while ensuring alignment across business, design, and technology from day one.

Research and Discovery steps began by analyzing qualitative insights from user interviews, usability testing, and open-text feedback from customer service logs, alongside quantitative data from behavioral analytics and support ticket trends. With the help of AI-powered data analysis tools, this dual perspective helped to understand:

• Where and why users feel uncertainty after checkout
• Common confusion points around tracking process, delivery timelines, and edge-case scenarios
• Opportunities to reduce cognitive load and improve clarity in the post-purchase journey

User problem definition was the crucial stage for translating research findings into clear user needs and business goals, with the intention of prioritization of essential features and defining the MVP scope collaboratively. This included:

• Designing a visual tracker component with progressive disclosure of status
• Embedding expected delivery dates to manage anticipation
• Accounting for non-happy path states (delays, failed deliveries, cancellations, lost items)

Throughout this stage, refinement works are conducted hand-in-hand with tech leads to ensure technical feasibility, including API dependencies, data accuracy, and performance considerations.

Unmoderated tests to validate design decision was also beneficial to measure the balance of impact, effort, and user value—ensuring we shipped the most critical improvements first.

A major success factor in this project was the strong, ongoing collaboration between product, design, tech, and research. By fostering a shared understanding of both the customer journey and the business constraints, we were able to:

• Align around clear KPIs (reduction in support calls, NPS lift)
• De-risk technical complexity early
• Scale the solution globally without compromising user clarity

This collaborative, integrated workflow was key to delivering a globally scalable experience that meets real customer needs.

This experience was not just about visual polish—it delivered measurable business outcomes:

• Reduction in WISMO-related support tickets, freeing up customer service resources
• Increase in NPS attributed to improved post-purchase communication
• Strengthened adidas’ position as a customer-centric, digitally mature brand
• Created a scalable, global UX pattern that can be extended into future post-purchase innovations

That means:

• Designing for transparency isn’t just good UX—it’s good business.
• Anticipating and designing for exception cases builds trust during high-friction moments.
• Cross-functional alignment is essential when designing for complex backend processes like fulfillment and logistics.
• Even small interface improvements can drive large-scale operational efficiencies.

Interested in the full case study? This project is a strong example of how strategic UX design can drive both customer satisfaction and operational impact. The full story is ready to be shared in talks, workshops, and consulting sessions focused on e-commerce UX, post-purchase journeys, and designing for trust.
Looking to improve your own order tracking or fulfillment UX?
Contact us for walking through the case study in detail or explore how similar thinking can be applied to your organization.