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Future Proofing Beauty: Digital Transformation

11th November 2024

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Maximising value through digital transformation in beauty companies.

Innovation is the key to sustained growth in the beauty industry. As consumer expectations evolve and market environments become more dynamic, the ability to innovate quickly and effectively has never been more crucial. At Skarbek, we understand the need for companies to enhance their innovation capabilities, which is why we have developed the Innovation Fitness Index (IFI), a comprehensive diagnostic tool that helps organisations assess their readiness to innovate across various dimensions [1]. Digital and AI technologies are core components of the IFI, as they enable companies to drive speed, agility, excellence in their innovation processes and offer new potential in augmented consumer innovation.

In 2023, the global beauty market’s retail sales grew to $446 billion, a 10% increase from 2022 [2]. This growth was primarily driven by price increases rather than volume gains due to macroeconomic factors, low consumer confidence, and widespread discounting. Digital transformation is becoming a strategic imperative for beauty companies to sustain their growth and remain competitive.

65% of organisations are now using generative AI in at least one business function, and this number continues to rise [3]. Digital transformation is reshaping every aspect of this sector, from product development to consumer engagement. For beauty companies, adopting digital tools such as AI and machine learning is critical for improving customer engagement, product development, operational efficiency, and team efficiency.

10%

increase from 2022

In 2023, the global beauty market's retail sales grew to $446 billion...

65%

of organisations

are now using generative AI in at least one business function...

Digitally Enhanced Customer Experience & Engagement.

Digital transformation has had a profound impact on the beauty sector, particularly in customer experience and engagement. With beauty companies already enjoying a unique relationship with consumers, direct-to-consumer value streams have become central.

These technologies enable companies to collect and analyse vast datasets, empowering them to customise product offerings and enhance customer experiences more effectively.

Nowadays consumers expect products and services tailored to their unique preferences, and AI-driven personalisation tools allow companies to meet this demand. AI and Machine Learning algorithms analyse consumer data such as skin type, hair condition, or buying habits to provide tailored beauty routines and product recommendations.

Kiehl’s Derma-Reader allows consumers to perform a comprehensive skin diagnosis using just a smartphone photo. Leveraging advanced clinical imaging technology, it analyses over 16,000 clinical images and 11 key skin characteristics [4].

Based on this analysis, a customised list of product recommendations, expert advice, and a bespoke beauty routine is provided.

AI-powered virtual try-on tools enable beauty customers to visualise how makeup or hair colour products will look on their skin before purchasing [9]. This not only enhances engagement but also increases conversion rates by giving consumers more confidence in their choices.

To help visually impaired individuals use its products independently, without needing assistance, the Estée Lauder Companies (ELC) has developed a voice-activated makeup assistant (VMA). The VMA mobile app is based on AI and augmented reality and guides the user through voice. In this context, the mobile app utilises the preferences set by the user on their device, but it also offers them the option to alter the type of voice and speech rate.

AI can also significantly enhance the efficiency and effectiveness of marketing content generation for beauty companies by automating and personalising content generation.

L’Oréal’s CREAITECH lab has developed a brand custom AI model, specifically trained with the core codes of L’Oréal’s brands, to generate brand-compliant content [5;6]. This AI system produces localised, brand-specific content, focusing on creating tailored marketing materials that resonate with diverse consumer audiences. To build this solution, L’Oréal leveraged a WPP-Nvidia engine, along with multiple Large Language Models (LLMs) and distribution models.

Gabin Vic
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