Understanding User Shopping Behaviors

We began by gaining a clear understanding of how users browsed and searched for products on the London Drugs website. The platform served a wide range of shoppers—from tech-savvy customers searching for electronics to everyday users purchasing household items or personal care products.

Research activities included:

• Remotely moderated usability studies with desktop and mobile shoppers

• User interviews focused on shopping habits, frustrations, and brand perception

• Clickstream and search data analysis to identify common dead-ends and high-exit pages

• Collaboration with internal merchandising and marketing teams to understand business goals and constraints

Key insight:

Users frequently relied on the site’s navigation, not just search, to browse products—but found the category structures confusing, redundant, or inconsistent.

Deliverables:
User Journey Maps, Empathy Maps, Research Interview Notes, Stakeholder Alignment Deck

Identifying Structural Issues and Prioritizing Needs

From the research, we synthesized findings into clear problem statements and defined the core needs of both users and the business. The primary area of focus was the site's taxonomy and navigation model, which was not aligned with how users mentally organized product categories.

Core challenges identified:

• Redundant or overlapping product categories

• Unintuitive navigation labels, especially for newer product lines

• Poor support for cross-category browsing and exploratory shopping

• Lack of consistency between mobile and desktop experiences

Problem statement:

How might we redesign the site’s taxonomy and navigation to reflect real user behavior and expectations—improving product findability without disrupting internal merchandising logic?

Deliverables:
🟢 Problem Statements, Taxonomy Audit Report, User Needs Framework, Feature Gap Analysis

From the research, we synthesized findings into clear problem statements and defined the core needs of both users and the business. The primary area of focus was the site's taxonomy and navigation model, which was not aligned with how users mentally organized product categories.

Core challenges identified:

• Redundant or overlapping product categories

• Unintuitive navigation labels, especially for newer product lines

• Poor support for cross-category browsing and exploratory shopping

• Lack of consistency between mobile and desktop experiences

Problem statement:

How might we redesign the site’s taxonomy and navigation to reflect real user behavior and expectations—improving product findability without disrupting internal merchandising logic?

Deliverables:
Problem Statements, Taxonomy Audit Report, User Needs Framework, Feature Gap Analysis

Redesigning the Category Experience

With user pain points and business goals clearly defined, I facilitated ideation sessions with product owners, category managers, and UX designers to explore improved structures for the site’s IA and navigation model.

Key solutions explored:

• A revised, user-centered category taxonomy informed by card sorts

• Clearer hierarchy and labeling conventions across product groups

• Cross-linking between related categories to support broader shopping journeys

• Consistent filtering and navigation design across platforms

I also introduced content strategy principles to ensure labels were user-friendly, SEO-consistent, and scalable as inventory evolved.

Deliverables:
Concept Maps, IA Diagrams, Taxonomy Drafts, Workshop Outcomes

Prototype: Validating New Taxonomies with Tree Testing

To validate our revised taxonomy before committing to major redesign efforts, I designed and executed a detailed tree test using Optimal Sort. Participants were given common shopping tasks and asked to locate products using the proposed navigation structure.

Test structure:

• Tasks mirrored real-world user journeys (e.g., “Find a wireless phone charger” or “Shop for cold & flu medicine”)

• Sessions were run remotely, capturing both quantitative success rates and qualitative feedback

• Variants of the taxonomy were tested to evaluate label clarity and content grouping

The results clearly identified the strongest performing taxonomy structure and helped eliminate ambiguity around labels and category placement.

Deliverables:
Tree Test Report (Optimal Sort), Task Completion Data, Revised Navigation Schema, Recommendations Deck

Measuring Outcomes and Presenting to Leadership

Post-implementation, I monitored improvements through a combination of analytics tracking and user feedback. Product findability—as measured by successful category browsing paths and reduced bounce rates—increased by over 20%. I presented these insights, along with final recommendations, to C-suite executives in a virtual stakeholder session.

Final validations included:

• Improved time-to-product metrics across all major categories

• Higher mobile satisfaction scores from follow-up usability sessions

• Positive feedback from internal teams on taxonomy maintainability and clarity

Deliverables:
Executive Presentation Deck, Success Metrics Report, Annotated IA Documentation, Post-Launch Review Summary