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Kristina Kosenko, Data Scientist and Founder & CEO of SKINFAIR talks AI, Data Science and Beauty.

IWD: Can you tell us more about your background and the SKINFAIR project? 


Kristina: I've been a data scientist for almost 9 years now and I've been working with companies from healthtech to retail and more. But now I decided to work on something of my own and that is the project SKINFAIR. Because I am a data scientist by day but a huge skincare addict by night I thought why not combine the 2 things?! Basically SKINFAIR is shaping to be a discovery platform which includes a skincare recommander, a tracker and a testing area that contains detailed information on products.

IWD: Is SKINFAIR going to be selling your products or other brand’s products ?

Kristina: We are basically going to try and match a person with an already existing product that is the most suitable for their concerns, in the right price range, location, etc. That is the first version of SKINFAIR and, in the future, with version 2 we will try and formulate our own products that are specific to each individual's skin concerns.


IWD: Do you see the future of retail beauty as e-commerce only or that physical stores will remain the place of product testing, and place of the brand image?

Kristina: I think a lot of things are moving to the digital space right now and it also applies to beauty’s shopping experience. I do think there is still a need for physical interaction when it comes to trying and testing products, I think people are missing that at the moment. That being said, a lot of the preliminary discovery and research on products is done online. Very few people go to stores and have no idea what they want to buy, they usually have some idea of which product they will purchase. 


IWD: With your experience in analytics and machine learning for clients in retail, what tech innovations do you see as feasible in the brick and mortar sector of the beauty industry? For example, could an AI device, such as SKINFAIR, be oriented to a physical store application? 

Kristina: Yes, I think that SKINFAIR could totally be feasible as an in-store helper,  recommending a specific product based on the data from that specific store and customer. In general when it comes to retail and in-store tech, it's not so much about the AI per-se but more about the analytical part and customer profiling. 


IWD: In a beauty and skincare market that is oversaturated with the diversity of products claiming to be THE ONE, how would you approach using technology to instil trust when consumers are in store shopping?

Kristina: This is actually one of the first points why I thought of SKINFAIR because it's very difficult and time consuming for us, as consumers, to research the ingredients and how they impact our skin, whether the reviews are real or paid for. This is exactly where my AI knowledge comes into play because I extract all the data from the real customer product reviews platforms and filter it from what is sentiment and what is practical. This kind of tech can be adapted for an in-store experience that allows fast filtering for undecided customers. It can be in the form of a machine that provides you with a match percentage between your preferred product and your skin needs while giving you detailed information based on other user's experiences, and tell you how well the ingredients interact with your specific skin type. All in all I would say this could be useful in, not only reducing consumer time, but also changing the interaction with store employees.


IWD: Thank you so much for talking with us and sharing your expertise and we are looking forward to seeing SKINFAIR live.


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