When most people think of Carhartt, they picture rugged workwear built to last: a bib overalls that farmers, ranchers, and tradespeople trust every day. But what's less obvious is that the company's digital presence reflects the same attention to durability and precision.
Behind the scenes, Carhartt's UX team is transforming how design decisions are made, leveraging behavioral data not just to improve experience, but to forecast revenue before a homepage is even built.
Bruce Shields, Director of UX and Digital Strategy at Carhartt, leads a team that spans nine time zones and encompasses front-end development, UX design, personalization, and optimization.
Their mission? To ensure that every digital interaction drives measurable business outcomes.
As Bruce explained on a new episode of The Frictionless Experience.
"There's a lot that goes into that revenue number. Time of year, seasonality, and what else was happening in the market. So in a perfect world, data comes before design. And that's really where we're moving now, is to get that data as far up in that process as we possibly can."
That shift (moving data upstream) marks a big change from where Carhartt’s UX team started.
When Bruce first arrived at Carhartt, the UX function was relatively low in maturity. Design decisions often relied on gut instinct or what had "worked in the past," rather than behavioral data.
He reflected:
Today, Carhartt's team collects and analyzes behavioral metrics—such as click-through rates, scroll depth, and conversion funnels—to inform their decisions. Even the most experienced designers and marketers must use data to inform their intuition.
"Most people come to work wanting to do good work. They want their work to matter. You just have to show them that by testing, you're helping them do that," Bruce said.
The shift from intuition-based design to a data-driven approach didn't happen overnight. Early on, confirmation bias was a real challenge: teams would test ideas only to prove what they already believed. Carhartt overcame this by establishing a culture that celebrates learning from every test outcome.
"We always say, we don't have winners and losers. We have winners and learners," Nick Paladino, my co-host, emphasized.
That culture of learning also shaped how the team approached another challenge: the very different needs of B2B vs. B2C users.
A key factor in Carhartt's UX approach is understanding the difference between B2C and B2B users. While consumer purchases are often personal and direct, B2B buyers make decisions on behalf of many others, which changes both the stakes and the journey.
The UX team must consider variables such as size conversions, multi-product orders, and the efficiency of repeat purchases for businesses. For example, a B2B buyer might need to order men's t-shirts for women on their team, which requires nuanced personalization and thoughtful design.
With that foundation in place, Bruce’s team began building a systematic process to forecast outcomes.
One of Carhartt's most innovative initiatives involves leveraging two years of homepage performance data to predict the revenue impact of design changes. Bruce explains that this process has two main steps, which the team applies rigorously to guide UX design and strategy.
Josh, Bruce's optimization specialist, led the effort to establish benchmarks for every type of homepage component.
1. Collect historical performance data: Two years of interaction data, including clicks and scroll depth on both desktop and mobile, were gathered.
2. Segment by component type: Hero images, banners, product packs, and other elements were categorized to analyze performance individually.
3. Account for context: Metrics were normalized for seasonality (holiday vs. non-holiday periods) and promotional campaigns.
4. Calculate interaction rates:"We created a calculated statistic called the interaction rate. It's the number of people who clicked on that component divided by the number of people who actually saw it," Bruce explained.
5. Identify patterns: Some components consistently performed well, regardless of placement, while others required precise positioning on the page.
6. Establish benchmarks: For each component type and position, the team defined expected visibility, clicks, conversions, and interaction rates.
This benchmarking step allows Carhartt to evaluate each new homepage or component launch against historical expectations, providing immediate insight into underperformance or opportunities for improvement.
Once benchmarks were established, the team moved into predictive modeling to forecast the financial impact of homepage changes.
1. Estimate future traffic: Using historical traffic patterns, the team models the expected number of visitors for upcoming periods.
2. Combine traffic with benchmarks: By applying interaction rate benchmarks to projected traffic, the team can estimate revenue for specific components before any design is finalized.
3. Integrate into wireframing:"For every wireframe, my designer, Steve, and Josh sit down together. Steve will say, 'These are the components I'm thinking about. 'Josh will model out that revenue. Before anything has been decided upon creatively, we can say this will either hit that number or it won't," Bruce said.
4. Enable real-time pivots: After launch, weekly comparisons against benchmarks allow the team to adjust component placement or remove underperforming elements.
5. Plan go-to-market strategy: Eventually, the team aims to use predictive data for broader planning—such as evaluating whether brand campaigns will cannibalize revenue from other initiatives.
Bruce noted:
One insight that came from this rigorous testing is that fewer clicks don’t always equal a better experience.
A common misconception in UX is that fewer clicks always equals a better experience. Bruce and his team have found that adding an extra step can actually improve clarity and decision-making.
"Sometimes the best experience isn't the fewest clicks—it's the clearest path," Bruce noted.
He recalls examples where reducing clicks would have decreased engagement or even caused confusion. In one instance, a mini-cart pop-up allowed users to continue shopping, increasing overall revenue. Sending users directly to checkout might have reduced friction in the short term, but it has hurt long-term metrics.
"There is always nuance. A new user who knows nothing about your site is very different than somebody who's been on your site a hundred times," Bruce explained.
Just as clarity can outweigh click minimization, channel context also shapes what ‘best experience’ means.
Carhartt tracks journeys across multiple channels to ensure they optimize the experience for new and returning users. They discovered that first-time visitors respond best when landing on the homepage, which provides context and navigation options. Landing them directly on a product detail page often results in high bounce rates.
"One of the more effective places that you can land people if they're new to the carhartt.com experience is on the homepage. It gives them options to drill down," Bruce said.
The team also runs rigorous control-group split tests to determine the optimal experience for different user segments.
Every UX decision at Carhartt ties back to measurable business outcomes. By tracking conversion rates between product listing pages and product detail pages, the team can identify serious buyers and optimize the funnel accordingly.
"The product listing page is where you're trying to decide: is any of this relevant to me and my needs? The product detail page is where you're trying to figure out if this one is relevant," Bruce explains.
This rigorous, data-driven approach enables Carhartt to accurately predict revenue, validate design hypotheses, and create digital experiences that are both frictionless and commercially effective.
Bruce noted:
Carhartt demonstrates that great UX isn't just about aesthetic or functional polish—it's about data, testing, and alignment with business objectives. By embracing benchmarking, predictive modeling, and a culture of continuous learning, Bruce and his team ensure that every design decision contributes to both revenue and customer satisfaction.
"The predictive modeling gives us confidence to say: this design isn't just cleaner, it's going to drive more business," Bruce concluded.
Whether targeting B2C or B2B audiences, new or returning users, Carhartt's approach demonstrates that a thoughtful, data-informed UX strategy can transform digital friction into a strategic advantage.