AT&T

UX Research & Design Strategy Lead

Organizing support around the language customers already used.

Customers had clearer paths to answers when support content was structured around the words they used, not internal categories. As research lead and design strategist, I led discovery, taxonomy redesign, and content strategy for AT&T's primary consumer support destination — improving CSAT by 20%, reducing support calls by 5–12%, and increasing monthly visitors by 5M.

Outcomes

Less calling. More solving.

Measurable improvement across every metric that matters for self-service — satisfaction, call deflection, traffic, and time-to-answer.

Customer Satisfaction
+20%

ForeSee CSAT improvement post-launch.

Call Deflection
5–12%

Fewer inbound support calls as customers resolved issues online.

Monthly Visitors
+5M

Increase in unique monthly visitors following launch.

Time to Answer
−10–15s

Reduced dwell on upper-level pages — customers finding answers faster.

The Insight

Customers had clearer paths to answers when support was organized around their language.

AT&T's support content was organized around internal categories. Customers arrived with problems in their own words — "reset my password," "fix my bill," "why is my service not working?" The redesign started by mapping customer vocabulary to the business structure, not the other way around.

The content existed. The opportunity was making it findable.

Click analysis showing navigation patterns vs. expected paths

Click analysis — the gap between where customers navigated and where AT&T expected them to go. The misalignment was structural, not random.

What We Changed

From internal categories to customer-language taxonomy.

Before
Internal taxonomy and technical labels
Duplicate and overlapping articles
Long paths between question and answer
Pages designed for reading, not scanning
After
Customer-language taxonomy
Search-optimized, deduplicated content
Common tasks surfaced earlier
KMS governance to maintain quality over time
Research & Discovery

Four methods. Every one pointed to the same root cause.

Customer Interviews
Heard problems in customers' own words — vocabulary AT&T's labels didn't match
Treejack Study
Tested findability in the existing IA without visual design as a cue
Content Audit
Mapped duplicates, gaps, and mislabeled categories across thousands of articles
Path Analysis
Showed where customers actually went vs. where the IA assumed they would
Design

Taxonomy first. Pages second.

We didn't start by polishing page templates. We rebuilt the taxonomy around the words customers used, then redesigned support pages around scanning, task priority, and clear paths to answers.

Content structure optimized for scanning and SEO

Content structure — reformatted for scanning with clear hierarchy, short paragraphs, and the terms customers actually use when searching.

Final comps and redlines

Final comps and redlines — handed to engineering with complete specifications for the redesigned experience.

Design artifacts

Validation

Task success nearly doubled. Twice.

We tested iteratively — labels, page structure, CTA visibility, scroll behavior, and task completion — before each build cycle.

Test Round Before After Gain
Round 1 — Taxonomy labels 36% 46% +10 points
Round 2 — Page structure 29% 56% +27 points
Taxonomy validation study showing category match rates

Taxonomy validation — confirming new category labels matched how customers actually searched, before committing to full content migration.

Before and after — att.com support redesign

Before & after — the redesigned AT&T support experience.

What This Changed

Rebuilding support around customer language made answers easier to find at scale. Customers found clearer paths to common tasks, support pages became easier to scan, and the experience reduced pressure on assisted support channels.