top of page
  • Vatsal Gupta

Big Data & It's Effects On Cosmetic Industry

In today’s beauty and personal care industry, new product development and innovation are happening as fast as consumers are posting about their beauty routines online. The industry has shown tremendous growth, with a projected market value of $805.51 billion in sales by 2023. One reason for such rapid growth? Cosmetics consumption and new innovation ideas are now born out of digital-first spaces.

Big data and artificial intelligence (AI) are used to develop alternative or totally new products as demanded by customers. In fact, the beauty industry created history by becoming the first commercial entity to gather and protect the power of data on a large scale, and to use analytics to uniquely respond to customer requirements.

Big Data

Therefore, it is not surprising that the global beauty industry is a thriving $532 billion business today. Moreover, the U.S. is the world’s biggest market for beauty products, with about 20% market share; China comes second with 13%, and Japan third with 8%. It is, therefore, quite probable that the beauty industry will exceed $800 billion by 2025, as projected.

Then again, the beauty industry, as every other industry, is challenged by the unique perspective of Millennials, and more so, of Gen Zers, who primarily define themselves as being individualistic, and not stereotypical. In defense of this perspective, popular actress Emma Watson, said, “There’s nothing interesting about looking perfect – you lose the point. You want what you’re wearing to say something about you, about who you are.”

Gen Z Survey

This has led the beauty industry to refresh its own perspective of what contemporary women seek to enhance their looks, and adapt their products, including collagen serum, to fit the exclusive expectations of the younger generations, by personalizing everything from ingredients to packaging. This is especially apparent in the companies ranked as the world’s most valuable cosmetic companies, of which the top five in order of priority are L’Oréal, Gillette, Nivea, Estée Lauder, and Clinique.

Cosmetic Research

Gone are the days of testing products in small markets and slowly launching globally. When consumer trends can be collected and marketed using digital channels, products can be globalized from the start. In 2018, over half of the net sales of popular Japanese brand Shiseido came from non-Japanese markets. Major brand acquisitions like Natura’s purchase of Avon demonstrate this move toward global, multi-brand product lines.


In personalising beauty products, information relating to skincare, makeup and or perfumes, blend gigantic databases, and evaluate billions of formulations saved in compelling algorithms, to create a customised product for someone. Therefore, big data is critical in personalising products and services. Moreover, 77% of consumers select products that provide a personalised service, do not mind paying more, and, in addition, recommend it to others.


For instance, L’Oréal’s commitment to research, innovation, and technology led to its setting up a technology incubator. A multitude of creative business ideas keep flowing from this incubator, such as the mobile app Makeup Genius, which allows customers to upload a photo or use the computer camera to try out different cosmetics and hair color, to see which combination creates the best look.

L’Oréal’s Commitment To Research

Consumers no longer need to head to their local makeup counter to find new products. Beauty apps and subscriptions offer individualised care routines and products. Social media and influencer campaigns offer brands with new options for direct-to-consumer sales online. When consumers visit a store, the experience is high-tech too, with facial recognition displays, VR experiences and digital loyalty programs all continuously gathering personalised data.

Furthermore, an AI-powered computer that can analyse a human face is useful to test combinations of products for customers to choose what is best for them. In earlier times, it was almost unthinkable to know how a new beauty product would look like on an individual, short of trying it physically. However, today, the AI systems can check the appearance of a product on a person without physically trying it. Philippe Benivay, Experimental Data Intelligence at L’Oréal, said, “Data and artificial intelligence allow us to move faster to create cosmetic products that meet the infinite diversity of beauty needs and desires of consumers around the world.”

As the beauty industry becomes more tech-enabled, opportunities for big tech companies to monetize their data, platforms, and devices will only increase — but, even as partnerships abound, they may eventually find themselves competing more directly with increasingly tech-savvy beauty incumbents.

With more educated and engaged consumers now than ever before, companies should consider how they are using big data to optimize their products and services to compete for market share and build a positive brand image supported by the use of new technology and personalisation techniques.

Thank you for reading, we hope you find our article interesting!

If you want to integrate data insights in your business then contact us here -


Vatsal - Hotelier by heart, has worked in B2B sales for over 2 years in US-markets. Currently pursuing Digital Marketing with Dublin Business School.

Recent Posts

See All


Post: Blog2_Post
bottom of page