Beauty, Fashion, Data Science and Consumer Research: Some of Our Clients and How We Can Help
The beauty industry is changing. To stay competitive, you need to understand how and why. Beauty brands are using everything from artificial intelligence (AI) to augmented reality (AR) to keep up with customer needs and expectations. This move also generates a massive amount of data, customer input and consumer centricity through profiling.
The fashion industry has already changed due to consumer data – consumers, not brands are now dictating what they want to wear, shopping online, and feeding AI engines their complete body dimensions.
Horizon Consumer Science works with companies in the beauty and fashion industries to understand and use the data they collect. Data science is already proving that return and exchange rates on clothing can be reduced considerably – a win-win for brands and consumers.
Predictive algorithms can analyze data about skincare, cosmetic and fragrance use, for example, to create tailored products, targeted marketing strategies, and an enhanced consumer experience. Data analytics and meaningful research can help beauty companies better understand the behavior of their customers, evaluate their own performance in the market, and chart a course for future success.
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Beauty and Fashion: Questions Data Science and Consumer Research Can Answer
Fashion is all about customer centricity. How can we use customer profiles and product preferences to apply prescriptive AI and reduce clothing return rates?
Do skincare and cosmetics buyers differ from fragrance buyers in meaningful ways?
How are millennials engaging in the beauty industry? What are they buying? What kind of consumer experience are they expecting? Gen Z buyers are now between 18 and 25, what are their preferences and how do they want to buy their beauty products?
Is there a trend toward locally made, artisanal, natural products? Are clean beauty products here to stay? If so, how can big beauty brands compete?
As fashion becomes more and more customer centric and curated boxes are delivered straight to consumers’ doors, what will be next for Generation Z? How can we use customer profile data and brand preferences to efficiently get consumers of many different sizes and shapes the clothing they prefer?