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Case Study · CNET / Ziff Davis · 2025

AI Atlas Redesign

Redesigning CNET’s AI content destination to improve discoverability, deepen engagement and unlock sponsorship value, all under real engineering constraints.

Role
Product Designer
Team
CNET / Ziff Davis
Timeline
2025
Focus
Product Strategy, Content Discovery, Cross-functional, Information Architecture
See AI Atlas live on CNET ↗
01 · Overview

A new destination for AI content

AI Atlas is a CNET initiative that pulls all of our AI coverage into one destination and creates a high-value surface for sponsorship. Early performance showed strong traffic, but content discovery was weak and engagement was shallow, which limited both the value to users and the sponsorship potential.

Original AI Atlas page before the redesign, with shallow content rivers and low-engagement navigation
Original AI Atlas, before the redesign
02 · Problem

Strong traffic, shallow engagement

The data told a clear story. Users arrived, skimmed the surface and left. For a property built around editorial depth and credibility, that was a UX failure and a business risk to the sponsorship model.

Almost all engagement landed on the content rivers, while the navigation that was meant to guide users, so jump links, FAQs and the glossary, saw close to zero interaction.

92%
of clicks landed on content rivers, so the layout was misaligned with behaviour
6%
jump-link interaction, so the core navigation was effectively invisible
53%
of traffic was mobile, so the redesign had to work device-agnostically rather than desktop-first
03 · My Role

Product Design

I led the redesign across research, editorial, sales and engineering. Alongside the visual work, I synthesised the research into product opportunities, defined the information architecture and turned competing stakeholder priorities into one coherent direction.

Research synthesis Information architecture UX & prototyping Stakeholder alignment
04 · Insights → Decisions

What the data told us, and what we did about it

I paired six months of page analytics with 12 unmoderated sessions on Userlytics, run as two six-person cohorts, one actively looking for AI content and one just likely to come across it. The patterns were consistent, and each one mapped directly to a product decision.

Insight
Users engage with content rivers instead of structured navigation
Decision
Move content rivers to the top instead of fighting the behaviour
Insight
High-intent users want a fast path to a specific content type
Decision
Add a filterable directory built for retrieval
Insight
Jump links and FAQ modules were ignored across sessions
Decision
Make navigation persistent and contextually visible
Insight
Editorial credibility drove trust in AI content
Decision
Give authors and their expertise a proper place in the UI
Insight
A majority of traffic was mobile, but the page was built desktop-first
Decision
Rebuild the core navigation to be persistent and device-agnostic, with sticky jump links and a filterable directory that hold up on small screens
05 · Visual Direction

Making the brand feel more human

Testing surfaced two brand problems. Users felt overstimulated by the page’s colours and visuals, and the palette read as overly feminine for the broader audience we needed to reach. This was the first project where I owned branding end to end, and I anchored the refresh in three moves.

01 · Palette

Pull back the colour

Removed the light purple and pulled back the overall colour, so the brand reads as more sophisticated and digital, and a lot less overstimulating.

02 · Imagery

Add human imagery

More people and fewer abstractions, so users can picture themselves using AI and the page feels relatable.

03 · Motion

Lean into animation

Motion graphics (built with our motion design team) make the hub feel modern and guide users down the page.

06 · Product Strategy

One destination, two surfaces

The core insight was that AI Atlas was serving two user modes from one experience, passive browsing and active search, and doing neither of them well. I split it into a dual-surface architecture that separated the two modes while keeping the destination together.

Redesigned AI Atlas hub as shipped at cnet.com/ai-atlas, with content rivers prioritized above persistent navigation and author credibility elevated
AI Atlas Hub. The redesigned discovery surface, live at cnet.com/ai-atlas
Redesigned AI Atlas directory, filterable by topic, type, and author for high-intent search
AI Atlas Directory. The filterable intent surface

AI Atlas Hub

Discovery · passive browsing
Content rivers ordered by engagement data
Persistent navigation across sections
Video and social woven in to grow dwell time
Author credibility elevated throughout

AI Atlas Directory

Intent · active search
Filterable by topic, type, and author
Simplified layout tuned for retrieval
Clear pathways back into the hub
Structured to scale as coverage grows
07 · Tradeoffs & Execution

Phasing the launch under constraints

Engineering capacity meant we couldn’t ship both surfaces at once. Instead of delaying the whole redesign, I phased it and shipped the Hub first so we could start getting real signal, with the Directory following after.

V1 · Shipped

Hub experience

The full hub redesign, with rivers prioritised, persistent navigation and editorial credibility brought forward.

V2 · Shipped later

Directory

Filterable directory with cross-surface navigation. Both surfaces now live at cnet.com/ai-atlas.

08 · Impact

What shipped, and what it moved

Jump-link usage 6% → 20%
Navigation engagement more than tripled after the Hub launched.
Time on site up ~10%
Dwell time grew within six months of launch.
2 sponsorships pre-launch
Both closed on prototypes, before any code shipped.
Both surfaces live
The full dual-surface experience is live.
cnet.com/ai-atlas →
09 · Reflection

What I’d do differently

The biggest gap was going in without explicit, measurable success metrics attached to each decision. We had clear qualitative goals but not the quantitative targets that make a post-launch evaluation rigorous. It’s a PM habit I’ve picked up since.

I’d also instrument prototypes earlier. Two sponsorships closing on the prototypes alone told us there was more commercial demand than we realised, and testing with sales sooner could have shaped the strategy from the start.