A new report by Revieve urges beauty brands to prioritize inclusivity and hyperpersonalization as consumer expectations evolve. The report, titled “Human-Centered Beauty: Wellness, Inclusion & Hyperpersonalisation”, is the third installment in Revieve’s “The Future Face of Beauty” series.
According to the report, AI-led beauty guidance must become more inclusive, addressing a wider range of skin tones, undertones, and ethnicities. It highlights the need for AI shade-matching and skin-tone recognition tools to use more diverse datasets, alongside guidance for different hair textures and the specific needs of melanin-rich skin.
Revieve’s research found that 73% of Gen Z consumers are more likely to buy from brands that actively represent diverse identities. Additionally, nearly 60% have switched brands or stopped supporting those that failed to reflect their values. This shows the importance of inclusive data in powering personalization tools and embedding cultural intelligence into R&D and marketing.
The report suggests that recommendations should factor in climate, lighting, weather, and cultural context to ensure skin analysis aligns with consumers’ real-world environments. It also explores how personalization should span from discovery to post-purchase support, incorporating elements like browsing patterns, self-care goals, and environmental conditions.
As the beauty industry evolves, brands may need to reassess their AI-driven guidance, ensuring it is both inclusive and contextually aware. This could involve integrating cultural intelligence into product development and marketing strategies, ultimately creating a more personalized and relevant consumer experience.
Revieve stresses the importance of blending automation with empathy, allowing AI to anticipate consumer needs while preserving human connection. The report cites The Inkey List as an example, which uses diagnostic tools to streamline skincare routines and offer customized solutions.
To ensure a seamless experience, the report highlights the need for improved integration between systems, enabling customers to transition between touchpoints without repetitive interactions. This includes linking personalization tools with social and CRM data, providing customer service with access to diagnostic information, and connecting in-store and online profiles.
