Back to Work Web Platform · Information Architecture

The site was organized like the company. Patients aren’t.

Invisalign.com had grown department by department until finding a basic answer meant knowing the org chart. I rebuilt its information architecture around what patients were actually trying to do across 90+ markets. Task success climbed from 67% to 94%.

Role UX/UI Engineer
Stage 1→n · IA restructure
Timeline 2020 - 2021
Team 4 Designers, 8 Engineers
Live Project View Website
Due to my NDA with Align Technology, I cannot disclose detailed designs from this project. The information below focuses on process, outcomes, and learnings while protecting confidential work.

The stakes: one in three visitors couldn’t finish what they came for

A prospective patient could arrive with a simple question about treatment time, insurance, or finding a provider and leave without an answer. Usability testing showed that only 67% of visitors could complete these core tasks. Years of organic growth had turned the navigation into a record of the company's structure instead of the patient's journey.

I was asked to restructure the full experience without sacrificing its search equity, while keeping the model flexible enough for more than 90 markets with different regulatory requirements.

"I clicked on 'For Doctors' by accident and got completely lost. I'm just trying to find out if my insurance covers this."
Patient participant

A site that outgrew its own map

The site had become an ecosystem for patients, parents researching for teens, and dental providers. Each audience brought different questions and every market brought different rules. The old structure made those paths cross too early, burying critical content four or five clicks deep and sending visitors into sections meant for someone else.

The Scale of the Problem

Task Failure Rate 33%
Mobile Traffic (desktop-optimized flows) 60%
Critical Content Depth 4-5 clicks
300+
pages across 90+ markets, each with different regulatory requirements

Where Users Got Lost

Session analysis showed exactly where the structure broke down: the main menu blurred audiences, the provider finder lost people before results, and treatment answers sat too deep in the tree.

41%
Navigation Menu
Patient vs. provider confusion
34%
Provider Finder
Abandoned before results
25%
Treatment Info
Couldn't find answers

The discovery: patients sort by goal, not by business unit

I separated the company's content model from the visitor's mental model. A 300-page audit exposed duplication and drift. Card sorting with patients, parents, and providers revealed how people grouped questions. Tree testing then showed whether the new language held up under real tasks.

Content Audit

Inventoried all pages across markets, identifying redundancies, gaps, and content that had drifted from user needs.

300+ Pages Audited

Card Sorting

Open and closed card sorts with patients, parents, and providers to understand mental models across user types.

200+ Participants

Tree Testing

Validated proposed taxonomy with task-based tree testing before committing to development resources.

15 Task Scenarios

Key Insights

The evidence converged on one idea: visitors organized the experience by goal, not by department. They wanted to understand treatment, judge fit, find a provider, or get help. The navigation had to begin there.

1

Navigation Confusion

"I clicked on 'For Doctors' by accident and got completely lost. I'm just trying to find out if my insurance covers this.", Patient participant

2

Content Depth

"I gave up after clicking through five pages trying to find treatment time information. Why is this so hard?", Parent participant

3

Mobile Experience

"The menu takes up my whole screen and I still can't find what I need. I'll just call my dentist instead.", Mobile user participant

The turn: rebuilding the map around patient tasks

The turning point was rejecting another layer of labels on the old tree. We rebuilt the information architecture from the ground up, using the card-sort language to create a task-first taxonomy that could scale across audiences and markets.

Three Design Principles

The solution was grounded in three core principles that directly addressed the research findings:

Task-First Navigation

Reorganize around user tasks ("Find a doctor", "Learn about treatment") rather than business units. Clear audience separation with persistent wayfinding so users always know where they are.

Addresses: Navigation Confusion

Progressive Disclosure

Surface key information upfront with clear paths to detail. Reduce maximum depth from 5 clicks to 3 for critical content while maintaining comprehensive information for those who want it.

Addresses: Content Depth

Mobile-First Redesign

Design for the 60% first. Simplified navigation patterns, thumb-friendly tap targets, and streamlined provider finder optimized for on-the-go research.

Addresses: Mobile Experience

Implementation Process

1

Content Audit

Inventory and gap analysis

→
2

Card Sorting

User mental model mapping

→
3

Tree Testing

Validate new taxonomy

→
4

Global Rollout

Phased deployment

The proof: task success from 67% to 94%

The redesigned site was rolled out over six months with continuous measurement against baseline metrics. Results exceeded targets across all key performance indicators.

Rollout Strategy

6
Month phased rollout
90+
Markets launched
0
SEO ranking drops

Measured Impact

Task Success Rate ↑ 40% improvement
Before 67%
→
After 94%
Bounce Rate ↓ 35% reduction
Before 58%
→
After 38%
Provider Finder Conversions ↑ 42% increase
1x
Before
→
1.42x
After

2x Site Traffic Growth

Better UX improved engagement metrics that search engines reward. SEO and UX aligned to drive organic growth without paid acquisition.

What it taught me

  • IA is the Foundation

    No amount of visual polish can fix broken information architecture. Getting the structure right enabled every other improvement.

  • SEO and UX Can Align

    The fear was that restructuring would hurt search rankings. In reality, better UX improved engagement metrics that search engines reward.

  • Global Requires Local

    A structure that works in the US may fail in markets with different healthcare regulations. We built flexibility into the IA from the start.

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