IA is strategy. Navigation is mental model architecture. AI can reduce human mediation when applied intentionally.
1. The Organizational Context
The company was building features. We weren't designing the system.
When I joined:
- No formal UX Research practice
- Product complexity increasing
- Enterprise churn rising
- Navigation and workflows had drifted
- Customer Success compensating for friction
The product wasn't weak — but the system lacked coherence. My role as VP Product Design: introduce structured UX Research into the organization.
2. Establishing UX Research
Before changing the product, we needed to understand the lifecycle. I introduced structured UX Research:
- 21 in-depth enterprise interviews
- Win/loss analysis
- Usage behavior synthesis
- Cross-functional workshops
This reframed the churn conversation from "Why are customers leaving?" to "How is value delivered across the lifecycle?"
3. The Core Insight
Value delivery relied too heavily on human mediation.
- The platform was powerful but cognitively heavy
- Navigation did not reflect user mental models
- Reporting required interpretation
- Insights required translation
- Customers expected automation and clarity
4. Structural Diagnosis: Information Architecture Drift
The platform had grown organically — not intentionally.
Before:
- Fragmented Discover / Measure separation
- Redundant pathways
- Overlapping conceptual models
- Feature-based grouping vs. task-based grouping
- Siloed workflows
After:
- Three core pillars: Insights, Reporting, Activation
- Clear mental model
- Workflow alignment
- Reduced duplication
- Logical hierarchy
This wasn't a cosmetic update. It was a platform restructuring.
5. Navigation Simplification
We redesigned navigation around user intent.
Before: Feature taxonomy
After: Outcome taxonomy
- Insights — understand
- Reporting — communicate
- Activation — act
We moved from tool-first thinking to user-intent-first thinking.
6. Product Responses Influenced by Research
a) AI as Interpretation Layer
Research showed customers wanted strategic answers, not dashboards. AI was introduced as a guidance layer, a friction reducer, and a scalable substitute for human mediation.
b) Customizable, Executive-Ready Reporting
We made insight storytelling self-serve:
- Flexible metric comparison
- Clear visualization controls
- Executive-friendly configuration
This reduced reliance on CSMs for report crafting.
c) Structured Insight Workflows
We shifted from data surfaces to guided workflows. Instead of exposing raw capabilities, we structured market share reporting, competitive tracking, and content gap discovery into guided intelligence flows.
7. Platform Coherence
Post-research, the product became clearer because the system became clearer:
- Simplified hierarchy
- Clear mental model
- Reduced duplication
- Scalable insight delivery
- Balanced product vs. human contribution
The UI reflects structural clarity.
8. Organizational Impact
At my level, impact wasn't pixel-based. It included:
- Established UX Research as a core discipline
- Influenced roadmap toward guidance and clarity
- Realigned product around lifecycle thinking
- Reduced navigation complexity
- Elevated UX to platform strategy
Leadership POV
UX and Product Design are not interface layers. They are systems of expectation, clarity, and value delivery. This work reinforced that platform thinking drives scalable value — and that research-led design is the most durable competitive advantage available to a product organization.