Beauty Brands using Facial Recognition


“Wow, this looks very good on you!” might the advice from the lady in the make-up store be. You spotted a beautiful lipstick in the store, but did not dare to buy the product without trying it. However, trying make-up takes a long time in the shop. Afterwards it  has to be removed, which also vanishes your other make-up. A lot of girls will recognize the frustrating situation.

However fitting clothes digitally has become known under the large audience, “fitting” make-up via online applications is relatively unkknown. The increasing possibilities with photographing and mobile phones allow make-up brands to create virtual applications for this. Some beauty applications use techniques technique that are comparable to facial recognition applications (used for security goals), which is not strange: the same technique is used in both branches (Gibb, 2013)

For example, Mabelline New York launched the Make-Up Express; a mobile application that allows you to watch tutorials, shop make-up trends and (most relevant for this topic) make a photo of your wrist in order to learn which shade of foundation is best. In this way Mabelline New York is able to give personal advice, even when the customer is not in-store (Gibb, 2013).

Also competitors of Mabelline New York started launching this type of applications: Sephora to go, the mobile application of Sephora, allows customers to scan products in-store and check the reviews and recommendations on that product. In this way, customers are able to interact with each other and base their purchase on consumer satisfaction (Sephora, 2016).

In Japan, Vogue introduced the Vogue Make-up Simulation Application. This application is a bit more advanced, since it gives customers the opportunity to upload a photo and view products of underlying brands on their own face. This gives customers a bit of a view on which look to buy (Aarabi, 2013)

Probably the most extensive application is the one from L’oreál: Make-up Genius. This application takes facial recognition a step further; the application registrates the face of the customer and captures emotions and facial movements digitally. In this way, consumers can check the look of a combination of make-up from different angles and perspectives online. Besides that, L’oreál effectively integrated social media; photo’s can be shared on several social media platforms. Similar to the Mabelline New York application, this application has the option to scan items. However, with this application scanning creates the opportunity to try the preferred product on the digital animation of your face (L’oreál Paris, 2016)


(L’oreál Paris, 2016)

So, besides the increased online interaction between beauty companies and customers (vloggers, video’s, reviews), the business models of beauty companies become more customer centric, in the sense that customers gain more personal insight on the possibilities of make-up. What does that mean for traditional way of shopping, with the advisers in department stores? Will they become unnessecary, since the make-up branch becomes more and more digital? The future will tell us.

References:

Aarabi, P. (2013) How brands are using facial recognition to transform marketing. Available at: http://venturebeat.com/2013/04/13/marketing-facial-recognition/ Visited: March 10, 2016.

Gibb, S. (2013) Introducing Make-up Express: the new way to enjoy the world of beauty. Available at: http://www.shannonwashington.net/maybelline-new-york-makeup-express-mobile-app/ Visited: March 11, 2016.

L’Oreál Paris (2013) Make-up Genius. Available at: http://www.lorealparisusa.com/en/brands/makeup/makeup-genius-virtual-makeup-tool.aspx Visited: March 10, 2016.

Sephora (2016) Beauty goes Mobile. Available at: http://www.sephora.com/mobile Visited: March 11, 2016.

Image: Posted by Loesch, S. Available at: http://sites.psu.edu/siowfa15/wp-content/uploads/sites/29639/2015/09/makeup.jpg Visited: March 11, 2016.

 

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