What makes a beauty brand truly memorable? In this 40-minute episode, verbal identity strategist Taylor de Diego shares how she helps brands uncover their whitespace and build a voice that’s unmistakably theirs.Taylor shares her journey from working at L'Oréal and MAC Cosmetics to launching her own company after experiencing firsthand the frustration of finding the right foundation shade.The conversation explores how AI and computer vision are transforming the beauty industry, the challenges of building accurate shade-matching technology that works across diverse skin tones, and the complex relationship between online and in-store beauty shopping. Taylor discusses the technical hurdles of training AI models with limited diverse data, why personalization in beauty goes far beyond just matching your skin tone, and her vision for using technology to make beauty more accessible and inclusive while maintaining the joy and discovery that makes cosmetics shopping special.Takeaways:• AI Shade Matching Requires Diverse, Quality Training Data: Building accurate shade-matching technology is challenging because historical beauty datasets lack diversity in skin tones and undertones. Training AI models requires extensive data collection across different lighting conditions, skin types, and product formulations, with particular attention to ensuring accuracy for deeper skin tones that have been historically underserved by the beauty industry.• True Personalization Goes Beyond Skin Tone: Effective beauty recommendations require understanding multiple factors including skin type, concerns, preferences, budget, and values like clean beauty or sustainability. Just matching foundation shade isn't enough – the technology must consider finish preferences, coverage needs, ingredient sensitivities, and even shopping behaviors to create truly personalized experiences.• Online Beauty Shopping Presents Unique Challenges: The biggest barrier to online cosmetics purchasing is confidence in shade matching and product suitability. While technology can help bridge this gap, the sensory experience of testing textures, seeing shimmer, and discovering products in-store remains valuable. The future likely involves hybrid experiences that combine digital convenience with tactile discovery.• Computer Vision Technology Must Adapt to Real-World Conditions: Developing shade-matching technology that works accurately across different lighting conditions, phone cameras, and environments is extremely complex. Variables like natural versus artificial light, camera quality, and even how users position their phones all impact accuracy, requiring sophisticated algorithms that can normalize and adjust for these factors.• Building for Inclusion Requires Intentional Design from Day One: Creating technology that works equitably for all skin tones can't be an afterthought. It requires intentionally seeking out diverse perspectives, testing extensively with underrepresented groups, and making conscious decisions about data collection and algorithm training that prioritize accuracy across the full spectrum of skin tones rather than optimizing for the majority.