『What Carhartt Knows About Customers That You Don’t with Bruce Shields』のカバーアート

What Carhartt Knows About Customers That You Don’t with Bruce Shields

What Carhartt Knows About Customers That You Don’t with Bruce Shields

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 While most UX teams obsess over reducing clicks, Carhartt discovered that fewer clicks can actually hurt revenue and customer satisfaction.

Join hosts Chuck Moxley and Nick Paladino as they talk with Bruce Shields, who leads digital experience optimization at Carhartt.

Carhartt has been making durable workwear since 1889—but their digital experience team is just as focused on longevity and performance. In this episode, Bruce Shields, head of Carhartt’s Global UX team, shares how his team uses two years of homepage interaction data to build predictive models, benchmark creative assets, and shift decisions from gut feel to data-led.

Key Actionable Takeaways:
  1. Move from gut feelings to data-first design decisions - Create a culture where "Have we tested that?" becomes the standard question in every design discussion
  2. Build predictive models from interaction data - Use click and scroll data to create benchmarks that can forecast component performance before launch
  3. Segment B2B and B2C user experiences differently - B2B buyers have fundamentally different motivations since they're purchasing for others, not themselves
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Download the Black Friday/Cyber Monday eBook: http://bluetriangle.com/ebook

Bruce Shield's LinkedIn: https://www.linkedin.com/in/bruceshields/
Nick Paladino's LinkedIn: https://linkedin.com/in/npaladino
Chuck Moxley's LinkedIn: https://linkedin.com/in/chuck-moxley

Chapters:
(00:00) Introduction
(03:00) Team structure across nine time zones and specializations
(06:00) Moving from design intuition to data-first decisions
(08:26) Preventing confirmation bias in testing culture
(11:22) Grid ordering system case study - When leadership was wrong
(16:59) Two years of homepage data creates predictive models
(18:22) Building interaction rate benchmarks by component position
(23:03) Moving predictive analytics into wireframing stage
(26:49) Most reliable performance predictors - PLP to PDP conversion
(30:18) Why fewer clicks isn't always better - The journey optimization debate
(34:30) Conclusion
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