Data Analytics in the Beauty Industry

Illustration by Autumn Qiu for Girls For Business

With the rise of data analytics in all fields of business, it is no surprise that the beauty industry is also jumping onto the big data bandwagon. From targeted campaigns to personalized products, the process of data analytics has allowed cosmetics companies to create unique innovations that reflect their diverse range of consumers. 

The beauty industry has grown tremendously in the past year, especially with the rapid increase in online sales. Currently, it generates over $100 billion in revenue worldwide, with North Asia representing around 35% of the global beauty market. Additionally, it is projected that online sales will make up 48% of total sales of beauty products by 2023. Thus, this growing demand has pushed companies to explore new methods of marketing and product development, with strategies beginning to revolve around big data.

Data analytics is the process of analyzing raw data sets in order to draw conclusions and evaluate trends. This allows companies to optimize their performance through the insights that the data offers. Specifically, big data analytics involves the use of advanced analytics techniques to extract information from large data sets that can be structured or unstructured. 

Data science, especially predictive analytics and customer analytics, is integral in helping cosmetics companies decide on their marketing campaigns and improving the customer experience. Beauty apps and smart technology are becoming increasingly common, with almost all notable brands pairing with new 

Currently, the demand for customized products is higher than ever. In fact, a study by Forrester reports that “77% of consumers have chosen, recommended, or paid more for a brand that provides a personalized service or experience.” Through the use of big data analytics, companies can assist customers in finding products that perfectly suit their personal preferences without the trouble of long testing phases. For example, the Sephora Visual Artist is able to analyze customer characteristics to recommend color shades that match their features. Additionally, Fenty Beauty, a company that prides itself on its inclusivity, offers recommendations through their Shade Finder Quiz by asking customers to identify models with similar skin tones as theirs. HelloAva’s chat bot also uses consumer feedback to curate personalized skincare routines for customers.

L’Oréal, the world’s largest cosmetics company based in France, has taken the process a step further, using cloud data integration in their product development process. Its platform incorporates direct data from application programming interfaces and bulk data from integrations Its research and innovation (R&I) department is in direct partnership with Talend, a cloud data integration company based in California, and currently processes 50 million pieces of data per day. Philippe Benivay, IS Experimental Data Intelligence at L’Oréal, stated that “data and AI allow us to move faster to create cosmetic products that meet the infinite diversity of beauty needs and desires of consumers around the world.”