While attending Stanford Business School, I, like many MBA students today, was thinking about big ideas. What could I do or build that would leverage my personal experience while hitting on a marketing opportunity?
I revisited my personal struggles with skin conditions starting at age 15. It was a problem made worse by me choosing skincare products that didn’t work. It deeply affected my self-confidence and sense of security. Research and interviews have also shown that 73% of people are unable to describe their skin type accurately. Couple that with the haphazard way skincare products are marketed and consumed and you’ve got a problem—and a big opportunity.
So, a couple years after getting my MBA, my business partner, Kailu Guan, and I launched HelloAva, a web application that helps our users select skincare products based on their unique skin attributes and needs. We saw a big opportunity to use artificial intelligence (AI) to make the product selection process more clear-cut and personalized—because most people don’t know the right products for their needs.
“We saw a big opportunity to use AI to make the product selection process more clear-cut and personalized.”
Our goal is to become the Netflix of beauty. Think about it: When Netflix recommends movies, it breaks down a movie’s characteristics into granular data points and then makes a recommendation based on movies that you’ve watched before and other demographic factors. HelloAva is doing the same thing, only with skincare products.
We built our own recommendation system by creating data points around the characteristics of each skincare product in our database, as well as the information and preferences provided by our users.
Here’s how it works: Our customers fill out a quiz detailing their skin type (such as oily, dry or pigmented), their concerns (such as acne, dullness or redness) and other requirements (such as cruelty-free, organic or price range). HelloAva’s proprietary algorithms—using hundreds of data points—then match that unique customer to appropriate products from the 200-plus brands we partner with. Our service also includes a 10-to-15-minute video call with a licensed aesthetician. The $10 consulting fee is later applied to any product purchase.
Thanks to AI, our customer now has a highly accurate, personalized recommendation. And it doesn’t stop there. Skincare is a constant journey. Skin changes over time as you go through life stages like pregnancy or aging. Your skin may be oily in the summer and dry in the winter. Your skin is not going to be the same a year from now. That’s why customer feedback is so important.
Over time, the customer adds new information about the products they’ve used—what’s worked, what hasn’t and what’s changed. We track those data points on a dashboard so that the algorithm gets even smarter, using what’s called deep learning.
AI has always been the inspiration for HelloAva. Deep learning technology that replaces or augments work by humans has already disrupted the movie industry, dating apps, travel planning and more. Who’s to say the same can’t happen to the world of beauty?
Bringing AI to life
AI is an abstract concept, so we must work to bring it to life for our customers and get them to see its value. We give each customer a personalized card with their customized skin treatment plan. At the end of the day, what consumers care about most isn’t how fancy the AI is, but rather how great the skincare product recommendations are—and whether those products help them achieve radiant skin and overall feel more confident and empowered.
At the moment, we have more than 150,000 active users on our app, and it’s growing day by day. We also continue to add new products and brands. Each and every product is rated on a spectrum of more than 30 different parameters, ranging from ingredients to texture to smell. During the pandemic, our Instagram following has jumped from 30,000 to more than 315,000.
At HelloAva, we’re excited about scaling this to more customers. And none of it would be possible without the power of AI.Print this article