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Transforming the Beauty Industry with Data and Analytics

Valued to exceed $500 billion in 2020, the beauty industry is growing rapidly. This industry growth has taken place both online and in physical retail locations, especially as more and more traditional retailers begin to launch their own beauty brands. One important recent trend within this industry has been an increase in customer willingness to try out new beauty brands as they search for the perfect products. This trend has been fueled by beauty companies’ use of big data and personalization to best understand and reshape to their consumers’ needs.

As a leader in the consumer products industry in data gathering and analytics, beauty brands have been able to adjust to consumer demand more effectively than ever before. Big data, along with artificial intelligence technology, can be used to develop alternative or completely new product offerings for consumers. Data is also used to develop targeted pricing strategies to serve emerging target demographics. Companies such as Estée Lauder, L’Oréal, and Procter & Gamble have noticed the impact that big data can make, and have invested in technologies to implement its powerful findings. Trends of consumer interest in ingredient transparency and sustainability are supported by companies’ uses of data analytics to understand the behavior of their customers. Using big data has allowed companies to continue research and innovation to protect product safety and quality.

Why Big Data is Important

Big data has proven its ability to help beauty brands optimize a variety of processes. From package and formula design, marketing and sampling campaigns, and strategic plan development, big data can provide access to analyses of consumer behavior and wants, especially for companies that are interested in targeting Gen Z buyers. To reach a diverse range of customer needs, asking questions about consumer issues can be combined with big data from databases, lab results, and other raw data sources such as imaging or robotic measurement. This helps beauty companies obtain accurate information that is not susceptible to bias or hidden by subconscious human interests. It also helps speed up the process of product development, audience targeting, and opportunity analysis, so that companies can make operations and utilization decisions to provide a diverse range of products with optimized margins.

Many companies are using big data in creative ways to improve their outcomes. Charlotte Tillbury tracks international demand for products using big data, as well as analysis of e-commerce. L’Oréal has started to use cloud data integration across functions to develop innovative products. Niche brands can purpose artificial intelligence for analysis of product reviews, developing ingredient libraries, and reviewing research to develop beauty regimen for their customers. Many brands are also using The Joy app to access information about demand and trends in the industry, using the findings to then redesign their products and services.


One beauty industry trend that big data has been able to provide valuable information for is product and service personalization. Because of advances in manufacturing and the direct-to-consumer business model, 77% of consumers have chosen, recommended, or paid more for a brand that provides a personalized service or experience- and personalization can increase a company’s revenue. With revolutionary data capabilities and technology, consumers are now able to participate in developing their own perfect products, making the purchase decision much simpler.

Consumers appreciate this luxurious opportunity to choose products that they feel best helps them achieves their beauty goals, and product customization options and tailored services make their lives easier by mitigating frustrations along the buying journey. However, consumers need to be aware of their own needs to provide the proper data to help algorithms give the best options, whether that needs to be informed by a consumer’s ingredient sensitivities, ethical preferences, or other specialized aspects. Especially for skincare and haircare products, targeted product recommendations need to provide perfect color matches to satisfy customers. Beauty brands can use data and analytics to optimize this process by collecting information to determine underlying factors and design solutions.

How Tech is Making Its Mark in the Beauty Industry

Using Algorithms and Machine Learning from Consumer Input

Working with big data, algorithms can be designed in a variety of ways to optimize product personalization for consumers. By analyzing customer physical characteristics, beauty brands can determine the current state of a person’s skin or hair. Data from consumers can be used to develop high quality, perfected skincare, makeup, perfume, and haircare product formulas for each individual customer.  Matching engine algorithms can also recommend or categorize the suitability of pre-existing products, and chatbots use data to provide personalized, relevant content throughout the sales funnel.

Brands need consumer input to make these processes work. For example, FOREO’s LUNA fofo uses sensors to generate massage routines for users, paired to an app that saves the consumer data to adjust for each use. Additionally, smart serums can use data to learn more about skin conditions after each use and adjust the formula to maintain optimization. Curology is one brand combatting acne issues with machine learning and AI.

The HelloAva chatbot is another example of how companies can adjust based on customer data and feedback – their algorithms help the customer design a personalized skincare routine and select products. The Sephora Visual Artist is also able to use customer characteristics to recommend tailored color shades. These examples show just a few of the ways that customers interact with brands personalization has spread throughout the industry, but newly developing types of technologies can use data in other ways as well.

Other Forthcoming Technologies that use Data & Analytics

Using technology and data has enabled beauty brands to develop billions of ingredient formulations, utilizing computer systems, algorithms, and databases to make products based on shopper preferences within minutes. However, one more recent technology can also use consumer data to change the way beauty industry products are bought and consumed – 3D printing. With the ability to scan and print face masks, print specialized makeup at home, or even print foundation makeup directly onto the consumer’s face, 3D printing’s capabilities paired with beauty industry products and services could change the way that consumers consider purchase habits.

With microbiome research for skin health already in play, DNA data may also be collected in the future to help predict aging and design preventative measures using certain skincare products. For example, UV ray triggers could be used to deploy smart sunscreen that lasts longer and works better. L’Oréal is one company already looking at solutions for this problem by developing wearable sensors to monitor sun damage and the pH levels of skin.

Providing digital content, tutorials, and virtual try-ons can help companies use data and analytics to display transparency, consider product ingredients, and educate consumers.  Smart mirrors that give advice about beauty regimen and other smart home devices can help gather and utilize data to improve the service capabilities of beauty brands. Developing apps to create connected, integrated beauty systems can support personalization while also collecting data about consumer behavior and characteristics to improve product quality.

Future Trends in the Beauty Industry

For beauty brands, key trends should be considered in partnership with data and analytics opportunities when contemplating R&D investment for new technologies, especially as younger, indie brands become increasingly creative and big brands make acquisition deals. Diverse, inclusive products can be designed in the spirit of personalization- using algorithms to process customer data and providing a unique service component can grow engagement and attract new consumers. Companies can also use data to address inconsistencies in the way customers maintain beauty regimens, perhaps by implementing loyalty program options. Looking at data trends can also inform brands about new demographic interests, such the growing markets in male personal care, child-focused products, representation for aging populations, and opportunities in China. 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 personalization techniques.

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Contributions by Courtney Loughran

Tags: Consumer Products Trends, Data & Analytics