Reimagining a complex enterprise payments platform by replacing fragmented, product-centric navigation with a scalable, user-centered information architecture that supports multiple personas, products, and future growth.

Visa Acceptance Platform

Information Architecture.

Content Strategy.

Content Design.

Workshop Facilitation.

Information Architecture. Content Strategy. Content Design. Workshop Facilitation.

Overview

As a Content Designer at Visa, I helped define a future-state information architecture and navigation model for the Visa Acceptance Platform. My work focused on IA strategy, terminology, navigation and settings governance, and aligning a large group of stakeholders around one shared structure.

Problem

The Acceptance Platform grew through many products, teams, and legacy systems. The result was a fragmented experience that was hard to navigate and hard to scale.

  • Navigation was organized around which team owned a product, not what users needed to do.

  • Terminology was inconsistent across products.

  • Similar workflows started from different entry points.

  • Capabilities were hard to discover.

  • Settings and configurations were scattered across the experience.

  • There was no shared governance model for adding new features.

In practice, users had to understand Visa's internal product structure just to get their work done.

The goal: create one cohesive platform vision, organized around merchant jobs and outcomes, that could scale across products, personas, and merchant maturity levels.

My role

Role

Content Designer (1 of 2)

Project type

Platform blue-sky vision work

Tools

Claude Code

GitHub

  • Defined IA principles, navigation criteria, and naming conventions

  • Ran current-state audits and mapped them to future-state models

  • Led navigation and settings mapping reviews

  • Helped decide where each capability should live in the platform

  • Built decision frameworks and governance guardrails for future growth

  • Synthesized stakeholder feedback and facilitated alignment discussions

  • Tracked gaps, risks, and open questions

Guiding principles

Before moving anything, we agreed on the principles every decision would be measured against.

  • Users over products. Organize around user jobs and workflows, not internal product ownership.

  • Stable architecture, flexible experiences. Keep one governable IA, and adapt what each persona sees.

  • Clear separation of concerns. Treat where something lives, how people reach it, what it's called, and how it behaves as four separate decisions.

  • Scalability. New products, personas, and capabilities should fit in without a major reorganization.

  • Governance. Future teams should be able to make consistent decisions using shared frameworks.

Key decisions

  • We organized the experience around merchant jobs, workflows, and lifecycle moments. Research and stakeholder feedback consistently showed that users think in outcomes, not product boundaries.

  • Merchants, enterprise merchants, acquirers, resellers, and tech partners need very different capabilities. Separate architectures for each would have been impossible to govern, so we built one shared structure and controlled what each persona sees.

  • We kept Transactions in the top-level navigation instead of nesting it under Payments. Some personas need to see transactions without managing payment functionality.

  • We sorted settings into three levels: product, domain, and platform-wide. This helps users understand the impact of a change and keeps global settings from becoming a catch-all.

  • We scoped reviews to navigation structure, groupings, labels, settings, constraints, and technical dependencies. Validating the architecture came before page-level feedback.

Working with Claude Code

Claude Code was part of our team's workflow from research through prototyping. It helped us move faster on the heavy lifting, so we could spend our time on the decisions that needed human judgment.

  • Gathering stakeholder research: We used Claude Code to collect and organize research and input from stakeholders across product, engineering, and partner teams.

  • Building custom skills: We turned that research into a reusable Claude skill, so the context about our users, products, and constraints was available every time we worked.

  • Mapping current state to future state: With that skill, Claude Code helped us map the current navigation to the future-state IA, showing where each capability lived today and where it should live in the new model.

  • Building the prototype: Claude Code helped us build the clickable prototype stakeholders used to review the architecture, without fully designing every page.

AI handled speed and exploration. Governance, final naming decisions, and the reasoning behind each choice stayed with the team.

Impact: IA mapping that would have taken weeks took days. We could send updated maps and prototypes to stakeholders quickly, gather feedback, and iterate in tight cycles. Leadership also saw the AI-assisted workflow as an example of a new way of working.

Outcomes and impact

The work shifted the conversation from product-centric navigation to platform-level architecture, and gave teams shared frameworks for future decisions. We:

  • Aligned stakeholders across product, engineering, risk, and partner teams around one shared structure.

  • Established persona-based navigation on a single IA foundation.

  • Improved consistency in terminology, organization, and categorization.

  • Created governance models and decision frameworks to support future platform growth.

  • Made the design process more transparent through mapping, documented rationale, and feedback loops.

Leadership responded strongly to the prototype and the interactive vision site, especially to tangible artifacts in place of traditional slide decks. They recognized the project both as a product vision and as an example of a new way of working.