Pillar4 Media
How Experimentation Design Generated $25M+ Across a 20+ Brand Portfolio
I lead the design function at Pillar4, a media and commerce company, across 10+ brands at a time within a 20+ brand portfolio. I manage a product design team of two product designers and a visual designer, and I stay hands-on in Figma every day. Over three years, the experimentation program I lead design on has run 400+ structured tests, produced 100+ wins, and generated $25M+ in measurable revenue. Every test starts from a real user friction, and the revenue follows from fixing it.
Measurable Results
Incremental revenue across owned and partner brands.
Across major experimentation initiatives.
Across the testing program.
Highest-performing conversion win (quiz redesign).
Business Landscape
Pillar4 operates a portfolio of high-traffic consumer brands alongside strategic publishing partnerships. Performance across this portfolio depended on consistent UX standards, experimentation frameworks, and product systems that hold up across many brands and audiences.
Pillar4’s owned brands generate revenue through high-intent organic traffic and affiliate commerce. Improving performance required aligning UX structure, experimentation, and product discovery across multiple sites.
- Sleepopolis
- Garage Gym Reviews
- BarBend
- Swolverine
- Mattress Nerd
- Mattress Clarity
- Morning Chalk Up
- Aging In Place
- Sleep Advisor
- Breaking Muscle
Pillar4 also collaborates with major publishing and consumer brands, supporting UX improvements that strengthen product discovery and monetization while maintaining each partner’s brand standards.
- Self
- Fortune
- AARP
- NCOA
- Help Guide
- Eargo
- Yes Hearing
- Audien Hearing
- Medical Guardian
- Sports Illustrated
How UX Connects to Revenue
Over three years, design work tied directly to revenue planning, experimentation, and measurable outcomes. Each test starts from where a user gets stuck, then ties the fix to a number we can measure.
When I joined, UX was largely a support function. Design happened downstream of decisions that had already been made. I worked with product leadership to change that, putting UX into revenue strategy and experimentation planning from the start. Over three years, this shift contributed to $25M+ in incremental revenue across organic and paid initiatives.
Working across 20+ brands meant I couldn’t design one-off solutions for every site. I built shared design patterns, standardized CTA hierarchy and monetization placement across templates, and rebuilt parts of the design workflow around Claude and Claude Code so the team could move faster on every test. The goal was to make performance improvements repeatable across the portfolio.
Every UX decision tied back to a measurable outcome. Conversion rates, take rates, revenue per visit, and experimentation velocity all became part of how we evaluated design work. The metrics at the top of this page are the result of that shift in how we measured success.
Leading the Design Function
The experimentation work is one part of the job. I also lead design across the portfolio. I manage a product design team of two product designers and a visual designer, own hiring and design reviews, set the design roadmap, and hold the craft bar for the whole team. I set the standard and stay in the work: I’m in Figma every day, designing alongside the people I manage.
Working Across Teams
Tighter coordination across product, paid media, and SEO teams turned individual test wins into portfolio-wide revenue gains.
Partnered with product managers and engineers to translate experimentation insights into scalable product improvements.
- Influenced backlog prioritization using experimentation data, shifting engineering investment toward the highest-revenue opportunities
- Reduced iteration cycles by formalizing testing workflows
- Cut design-to-code delivery time using Claude Code, shipping prototypes and test variants without a dev dependency
Collaborated with paid media teams to optimize landing experiences and improve conversion performance.
- Designed and optimized paid landing templates tied directly to return-on-spend targets
- Standardized monetization hierarchy across paid experiences to reduce friction between ad intent and on-page content
- Improved revenue per visit through structural landing page improvements
Worked closely with SEO and editorial teams to ensure UX improvements supported both ranking performance and user intent.
- Ensured monetization elements didn't disrupt search intent or ranking performance
- Refined comparison and review templates to balance editorial trust with revenue clarity
- Used behavioral data to inform layout changes on the highest-traffic organic pages
AI in the Design Workflow
AI is how I actually design now. Over the last year I’ve rebuilt pieces of my workflow around Claude and Claude Code, from pre-design research through post-design handoff. The work gets done faster and the team’s baseline output has moved up. Here’s where it shows up in practice.
AI shortens every phase of the design process.
- Pre-design research, competitor analysis, and strategy alignment built from structured prompting
- UX writing, marketing copy, and content variation generated and iterated in hours, not days
- Information architecture and user flow drafts produced with Claude, refined with the team
- Design generation through Figma MCP, turning prompts directly into editable Figma artifacts
AI has changed what design can deliver before engineering gets involved.
- Code generation for testing platform experiments, letting the team ship A/B tests without a dev dependency
- Production-ready prototypes used for stakeholder sign-off before handoff
- UI kit creation from live sites into Figma, cutting what used to be multi-day audits down to a few hours
- Design token generation and export automated into the dev handoff, reducing manual CSS work for engineering
The biggest gains come from AI as a team practice.
- Weekly AI working sessions with the design team to share workflows, prompts, and what's working
- Pushing AI adoption into product management and engineering so the whole team moves at the new pace
- Partnering with engineering on tokenization and block-level build patterns to reduce manual CSS across the site portfolio
- Treating prompt engineering as a shared craft, documented and iterated like any other part of the design system
A Tradeoff: Speed Over Polish
The AI workflow lets me ship test variants fast, and I made a deliberate call to use that speed. For most experiments I’d rather run a rougher variant this week than a polished one next month. More shots on goal means we learn faster, and a losing test that returns real data in days is worth more than a perfect mockup stuck in review.
I hold one line on it. Speed is for test variants. Anything that wins gets the full craft pass before it ships to users. We stay rough while we’re learning, and we finish the work before it reaches someone’s screen. That’s the balance: move fast enough to learn, slow down enough to respect the person on the other end.
What It Changed
The experimentation revenue is the headline. The change I’m most proud of is quieter: the workflow behind it outlived any single test. I rebuilt the design-to-dev pipeline around Claude, Claude Code, and Figma MCP, and it’s now moving past design. Product managers and engineers are picking up the same tools and the same pace. My bet is that within a couple of years, AI fluency will matter more than tool fluency, and a team already working this way has a head start.
Portfolio-Wide Applications
The strategic framework was applied across multiple brands, adapting UX systems to different audiences and monetization models.
Designed an internal platform used across Pillar4 brands to manage and distribute affiliate links across high-traffic content and commerce experiences.
Led UX strategy and experimentation for a high-traffic affiliate platform, aligning search intent, content structure, and monetization pathways to drive sustained revenue growth.
Led UX direction across Garage Gym Reviews, improving mobile usability, product discovery, and purchase decision clarity through structured experimentation and UX optimization.
Conducted a full UX audit and led a redesign of the Swolverine ecommerce experience to improve product discovery, supplement education, and mobile usability.
Sleepopolis
Garage Gym Reviews
Swolverine
