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The way we shop for beauty is constantly evolving, and one aspect that’s seen the most change is the relationship between the customer and the salesperson. Today, most beauty buyers know exactly what they want before they make a purchase. As a result, recommendations from sales associates have been replaced by recommendations from friends.
The problem, though, is that skincare is highly individualized, and an ingredient that’s effective for one person might trigger a reaction in another, or just flat-out not work. A product that works wonders for one of your friends might be a total disaster for you, and vice versa.
HelloAva, a new chatbot startup that launched this month, is betting on the combined power of personal recommendations and cold hard facts to sell beauty products. The idea is to give shoppers a more educated referral while still allowing them to make the final decision by themselves.
Here’s how it works: HelloAva connects with users via SMS and Facebook Messenger. To start, beauty shoppers answer a 12-question survey that will identify their individual skin type out of a possible 30. After taking the quiz, an algorithm generates product recommendations based on dermatologically-driven data. But before they’re sent to shoppers, Ava’s own estheticians narrow down the suggestions to tailor the list to each person. The system collects the final recommendations and sends them through; that information is then fed back into the system, which helps tighten the algorithm.
“We want to create a fully customized curation experience that puts the user’s interest first and personalizes a set of solutions,” says co-founder and CEO Siqi Mou. “We see the potential to bring analytics and personalization to skincare.”
So far, HelloAva’s brand list is small; the starting lineup includes niche labels (like Youth To The People, Leahlani, and Indie Lee), Korean beauty (Dr. Jart, Innisfree, and Too Cool For School), and a pilot program with L'Oréal. Mou says that one of her expansion priorities is an investment in natural beauty brands.
A couple weeks after a purchase is made, Ava automatically checks back to gather user feedback, which is sorted into the larger product database. As the sample size grows, that data will allow Ava to continually improve its algorithm and become smarter at recommending products over time.
Ava is still in beta, so you’ll need to request an invite from your future BFF to get started.