Lead UX Designer User Research IA & Wireframing Stakeholder Facilitation

From user pain
to product clarity

A few months ago, after long negotiations with the leadership group, we made a decision: build a new face and a new experience for the main product, from scratch, with almost no constraints. No compromises for legacy code. No shortcuts because of infrastructure debt. The development team and I knew the product well, its friction points and its red flags, but we wanted something fresh. While Christian, the lead developer, analysed what the platform could technically support, I had one job: start from the user and work forward.

I started with structured user interviews and feedback sessions. What came back was rich and messy. Overlapping needs, contradicting mental models, and a long list of frustrations buried in workarounds.

That's where AI entered the process, not as a shortcut, but as a thinking partner. I used it to translate and group feedback across formats and languages, audit my UX pillars against the real data, and co-build personas grounded in behaviour patterns rather than assumption.

When it came to wireframes, everything was kept deliberately grey. Stakeholder reviews need to stay focused on flows, content, and journeys, not colour. It's the fastest way to get the right feedback at the right time, and avoid the "I don't like this blue" conversation.

Good design
starts with
better questions

Laptop mockup

Fieldwork is a platform built for professionals navigating complex, multi-step workflows every day. People who need tools that reduce friction, not add to it.

The research phase surfaced a handful of recurring frustrations, the kind buried in workarounds people had stopped noticing.

By the time wireframes began, every element on screen had a reason. Traced back to interviews, shaped by pillars, validated by AI, and agreed on with the team. That's what a grounded design process looks like.

The Problem

Four frustrations we kept hearing

01

Unclear status tracking

People couldn't tell where things stood, or what had changed since they last looked.

02

Steep onboarding

New team members needed days to get comfortable with flows built for veterans.

03

No real mobile flows

Most of the work happened in the field, but the product still assumed a desk.

04

Storage over decisions

The structure was built to hold data, not to help people act on it.

Opportunity

A rare chance to rebuild around the user, not the legacy code. How might we turn a product people tolerated into one that follows them into the field?

24 user interviews
6 user types identified
4 core pain points
3 AI-built personas

Research & discovery phase

My role

Lead UX Designer

End-to-end ownership, from running interviews and synthesising research to defining the product direction, facilitating stakeholder reviews, and delivering validated wireframes ready for development handoff.

User Interviews
Research Synthesis
AI-assisted Analysis
Persona Creation
UX Pillars
Feature Definition
Information Architecture
Greyscale Wireframes
Stakeholder Facilitation
AI-assisted process

Where AI entered
my process

  • Translated and grouped raw user feedback across languages and session formats, cutting weeks of manual synthesis down to days
  • Audited UX pillars against interview data to surface gaps, blind spots, and overlapping assumptions
  • Co-created user personas grounded in real behaviour patterns, not gut feel or educated guesses

UX Pillars

01

Clarity over features

Every screen should answer one question at a time. No information overload, no hidden complexity.

02

Trust through transparency

Users need to know where they are, what changed, and what to do next, at every step of the journey.

03

Speed for power users

Experienced users shouldn't be slowed down by onboarding flows designed for newcomers.

04

Mobile-first workflows

Most fieldwork happens on the go. The product had to follow the user, not the other way around.

Wireframes

Grey by design

Greyscale wireframes focus stakeholder reviews on what actually matters: flows, content hierarchy, and user journeys. No colour means no distraction. It's how you get the right feedback at the right stage, and keep conversations on the work that moves the product forward.

Iteration 01 · Initial flows
Wireframe — overview
Full flow overview
Wireframe — homepage
Homepage
Wireframe — dashboard
Dashboard
Wireframe — detail view
Detail view
Wireframe — list view
List view

Stakeholder review

What round one taught us

The first review gave us a clear direction: the dashboard needed to lead with business numbers and savings, spend, contract performance, and less marketing content. Cross-selling and upselling modules had value, but they needed their own space. Mixing them into the core flow was creating noise where users needed signal. We restructured the IA around that distinction and went back to the board.

Iteration 02 · Revised structure
Wireframe — revised nav
Travel search module
Wireframe — simplified dashboard
Simplified dashboard
Wireframe — revised full flow
Revised flow, stakeholder review v2
Outcome

Key Decisions

01

Lead with the numbers that matter

The dashboard opens on savings, spend, and contract performance, not marketing content.

02

Give cross-sell its own space

Upsell and cross-sell had value, but mixing them into the core flow created noise where users needed signal.

03

Restructure the IA around signal

We split decision-making content from everything else and rebuilt the navigation around that line.

04

Stay grey until the flows were right

Colour waited so every review stayed about structure, content, and journeys.

What it produced

A validated blueprint, ready to build

  • A full set of greyscale wireframes, signed off by the leadership group across two review rounds.
  • An information architecture restructured around decision-making, not data storage.
  • Personas and UX pillars grounded in 24 real interviews, something the whole team could design against.
  • A clean handoff to development, with every screen traceable back to a real user need.

Reflection

The hardest part was never drawing the screens. It was asking better questions first, and trusting the research enough to let it reshape what we thought we already knew.