The beauty industry has always focused on personalization. When in-store experiences dominated retail, beauty sales relied on tête-à-têtes with knowledgeable shop assistants who enabled insightful recommendations and unique experiences for every customer.
Now, every element of the beauty industry is increasingly online. New digital-only storefronts like Glossier dominate the market along with an ever-growing culture of beauty influencers on social media and YouTube.
This shift has forced brands to adapt their operating models and explore how to continue offering personalized experiences in a digital space. For many, data science is the answer.
Beauty Products Shaped by Data
Innovative beauty brands are using data science to guide every step of a product journey from manufacturing to distribution.
Using data science, manufacturers generate granular insights to drive personalization at scale, from identifying popular fragrance combinations without the need for testing to finding the right pigment for every skin tone.
French cosmetics giant L’Oréal processes more than 50 million pieces of data per day to generate valuable information for its Research and Innovation (R&I) department. Their data covers characterizing and defining the physicochemical properties of formulas and raw materials, as well as understanding consumer perceptions of products. This enables the R&I team to closely tailor innovations to the needs and desires of its customers worldwide.
Other brands, such as Charlotte Tilbury, are using big data and cloud analytics to better understand customer behavior. They are gathering crucial business intelligence to drive their omni-channel strategy across stores, whether physical or digital, for optimized customer experiences. By sharing insights across the organization, Charlotte Tilbury also enhances its supply chain efficiency to meet fluctuating demand and emerging trends.
Beyond operational optimization, brands are now leveraging Artificial Intelligence (AI) models to engage customers with hyperpersonalized products and services.
One-of-a-Kind Products Delivered with AI and Data Science
At first, the use of AI and data science in the beauty industry was limited to luxury brands and products.
The Opte Precision System handheld makeup printer was one of the first AI-based products to make headlines. Priced at USD 600, the product employed a blue LED light to pick up post-inflammatory hyperpigmentation, age spots and sun damage on a user’s face, process the data using an intelligent AI model and print a serum that claimed to perfectly match the user’s skin tone, delivering skincare and makeup in one product.
The high price tag naturally limited the number of consumers for this product. However, since its launch, AI has become far more commonplace in the beauty industry – with consumer brands using the same technology to create more affordable yet equally innovative services.
One of the best examples is No7’s AI-powered Digital Beauty Advisor. The service asks the user to upload a selfie and leverages AI modeling to analyze facial data such as radiance, wrinkles and dark spots. Using this information, the service generates personalized advice and recommendations for No7 products.
Other consumer brands have even based their entire operating models on AI-powered personalization. DCYPHER is a digital cosmetics brand that offers ”mixed-to-measure” foundations for users’ unique skin tones and types – all based on data gathered by AI-powered video analysis.
Life-saving Data Science Innovations
While some brands have been using data science and AI to create personalized skincare routines, Google has taken the technology a step further, creating an app to identify users’ skin conditions.
DermAssist prompts users to capture three images of any problematic skin condition. These are analyzed and cross-referenced with a database of 288 skin conditions to create a list of potential matches. Armed with this information, users can pursue a more informed medical diagnosis or appropriate treatment. A similar innovation is L’Oréal’s My UV Patch. This adhesive sensor is worn on the skin and uses photosensitive dyes to capture data about users’ UV exposure. The information can be accessed via a companion app, which also recommends lifestyle changes and products to help users stay safe in the sun.
As data science becomes increasingly integral to the beauty industry, innovations like these will continue to evolve. The ultimate beneficiaries will be consumers, who will gain access to highly personalized products and tools that not only enhance their beauty experience but also contribute to early detection and prevention of serious health conditions.
For more fascinating insights into the role data, analytics and AI play in managing real-world problems, check out our perspectives here or talk to our experts.