New users
Orientation, guidance, simplified discovery, and clearer first paths into the ecosystem.
Redesigning Navigation & Taxonomy for an Enterprise-Scale Digital Ecosystem
A scalable information architecture strategy for 70,000+ pages, fragmented ownership, and overlapping product journeys.
"Transform structured chaos into something that can be easily managed by an organization."
Executive summary
The UX problem was also an operating model problem
A global technology company needed to make sense of a large digital ecosystem spanning more than 70,000 pages. Users struggled to find the right products, understand platform relationships, and move between related services without getting lost in internal terminology.
The work combined information architecture, stakeholder alignment, AI-assisted content clustering, and governance design. The goal was not simply to redesign menus. It was to create a system that could stay understandable as the organization continued to grow.
The challenge
Navigation had become a symptom of fragmented ownership
The ecosystem had expanded across products, departments, campaigns, and user journeys. Duplicate pages, inconsistent naming, and disconnected paths made it difficult for users to predict where information lived. Internally, different teams owned different parts of the experience and optimized for different priorities.
Manual restructuring was not realistic at this scale. The team needed a way to see patterns across the content, align stakeholders around shared principles, and define governance that would prevent the system from fragmenting again.
Strategic objectives
Create a navigation system that could scale with the business
- Unify the ecosystem: reduce disconnected paths and make product relationships easier to understand.
- Improve discoverability: help users orient quickly and reach relevant content with fewer dead ends.
- Clarify terminology: move away from internal language where it conflicted with user expectations.
- Support governance: give teams principles and decision rules for future navigation changes.
- Prepare for personalization: define experience layers that could evolve with user maturity and context.
Governance
Alignment had to be designed, not assumed
Different departments had different incentives: visibility, ownership, product priority, and campaign needs. A pure UX recommendation would not survive unless it also helped teams make repeatable decisions together.
We introduced a governance-oriented approach built around collaborative decision-making, measurable navigation performance, iterative refinement, and cross-functional ownership. Workshops helped turn competing priorities into shared navigation principles that teams could use after the redesign.
AI-assisted clustering
Using AI to interpret scale, not replace UX judgment
Traditional card sorting and manual content audits could not handle the full ecosystem efficiently. AI-assisted clustering helped reveal semantic relationships across large content sets, giving the team a faster way to identify patterns, duplicates, outdated pages, and potential taxonomy groupings.
- Transform webpage content into semantic embeddings.
- Group related content through clustering methods.
- Remove duplicate, deprecated, and irrelevant pages from the analysis.
- Translate technical clusters into meaningful navigation categories.
The AI layer improved decision quality by making complexity visible. Final taxonomy decisions still depended on human judgment, business context, and stakeholder validation.
Personalization framework
Navigation maturity became part of the strategy
The strategy also defined how navigation could adapt to different levels of user familiarity. This created a foundation for future personalization without forcing every user through the same experience.
Contextual users
Device-aware navigation, localization, accessibility adjustments, and contextual recommendations.
Known users
Personalized pathways, account-aware navigation, dynamic recommendations, and tailored calls to action.
My role
Turning complexity into shared decision material
My role focused on information architecture strategy, taxonomy structuring, stakeholder facilitation, AI-assisted clustering workflows, and concept visualization. I worked with UX teams, marketing stakeholders, department owners, and designers to make abstract structural decisions easier to discuss.
Visual prototypes and taxonomy models became alignment tools. They helped stakeholders compare options, understand trade-offs, and evaluate how navigation changes would affect users and internal teams.
Key challenges
- Organizational complexity: departments had competing expectations around ownership and visibility.
- Scale: the content volume made manual categorization impractical.
- Terminology: product and platform labels were inconsistent across journeys.
- Sustainability: the taxonomy needed to remain useful after the project ended.
Outcomes
A clearer structure and a stronger operating model
The work produced a scalable taxonomy structure, clearer navigation pathways, reduced duplicate and irrelevant content, and a governance framework for long-term maintainability. It also aligned with the organization's evolving CMS infrastructure, making content organization easier to manage over time.
The most valuable result was not only the navigation redesign. It was the creation of a repeatable decision-making framework for a complex organization.
Reflection
This project reinforced that enterprise UX often means designing around organizational reality as much as interface behavior. Governance, stakeholder facilitation, scalable systems thinking, and AI-assisted workflows all mattered because the problem was bigger than a menu structure.
This project was completed through Globant and GUT for a large enterprise technology client. Due to confidentiality agreements, specific company details, metrics, and proprietary assets have been omitted or anonymized.