Why the women behind beauty startup Proven Skincare believe A.I. is the answer to flawless, age-defying skin

  • The U.S. facial skincare market is worth an estimated $7 billion and growing rapidly, according to research firm Mintel.
  • Yet despite the wealth of products and information available promising flawless, ageless skin, consumers are frustrated by the low success rate.
  • Start-up Proven Skincare believes that personalized products have a much higher efficacy level.
  • To determine the best ingredients for each individual, Proven is relying on AI, aggregating data from 8 million consumer reviews, 100,000 skincare products, 20,000 ingredients and 4,000 academic journals.
Proven aggregates data from 8 million consumer reviews, 100,000 skincare products, 20,000 ingredients and 4,000 academic journals to decipher what types of ingredients work well for specific individuals.
Proven Beauty
Proven aggregates data from 8 million consumer reviews, 100,000 skincare products, 20,000 ingredients and 4,000 academic journals to decipher what types of ingredients work well for specific individuals.

Every year, consumers spend billions on skincare products that promise to reduce lines instantly, fade brown spots, improve firmness and elasticity and more. Yet despite the wealth of products available today, consumers continue to be frustrated by manufacturers' inflated claims of smooth, silky, younger-looking skin.

Now beauty start-up Proven Skincare — launched in November by Harvard Business School grad Ming Zhao and computational physicist Amy Yuan — is aiming to curb all that frustration, rejecting the traditional one-size-fits-all miracle remedy and instead relying on artificial intelligence to develop data-driven skincare routines that are completely personalized and sent straight to your doorstep.

Proven's formulations are made in-house and based on an online questionnaire that asks about skin concerns, lifestyle and environment. Written to mimic a dermatologist visit, the skin quiz asks about visible genetic background, such as ethnicity and skin tone, to help determine which ingredients to use.

Using machine learning and natural-language processing, Proven's AI engine pores through the data to decipher what ingredients will work best for specific individuals and environments. Their Skin Genome Project, which aggregates data from 8 million consumer reviews, 100,000 skincare products, 20,000 ingredients and 4,000 academic journals, won a 2018 MIT AI Idol award.

Zhao and Yuan then work with dermatology experts to fill in knowledge gaps as they figure out the actual product formulations based on ingredients suggested by the data. For example, Zhao said, certain acids work particularly well for hyperpigmentation in African-American and Asian skin that has high melanin.

Proven's skincare evolution

Skincare products make up the largest part of the cosmetics market, at 37 percent, with the United States considered the most valuable beauty and personal-care market in the world, says market research firm Statista. Women — and a growing number of men — spent an estimated $7 billion on antiaging products in 2017, up from $6.4 billion in 2012.

Today thousands of beauty influencers are now on the scene, and millions of consumers have become addicted to skincare blogs and social media, with everyone from celebrities on Instagram to the nearly 800,000 subscribers celebrating self-care and soliciting advice on Reddit's Skincare Addiction site.

Yet it was Yuan and Zhao's struggle to find answers to their own skin problems that led to the idea for Proven Skincare in 2015. After years of trying a number of expensive products to no avail, Zhao finally turned to a skin expert, who created personalized products developed specifically to her skin type. Zhao soon saw great improvement.

"That was the first time I felt anything really had benefits," Zhao said. "The philosophy of using products that are specifically made with my particular situation, my particular skin profile, life situation and skin goals made so much sense to me. That was the first step in bringing personalized products to more people."

Around the same time, Yuan was addressing her own skin issues by using a data set that crawled online product reviews to figure out what would work best for her.

This database became the foundation for Proven, and it is now being leveraged to sell products that adapt to the needs of individual consumers.

"[Proven is] based on the belief that personalized products made with you in mind has a much higher efficacy level, especially when we combine the knowledge that's already out there," said Zhao.

Ming Zhao, co-founder of Proven Beauty
Proven Beauty
Ming Zhao, co-founder of Proven Beauty

Customers also share their screen usage so Proven can factor in Zip codes to take into account the surrounding environment, including UV exposure and water hardness. Knowing location also allows Proven to modify formulations depending on seasonal weather changes.

After completing the assessment, customers can opt to pay $145 for a three-product regimen that lasts two months and comes with a consultation.

"As our users and our customers and ourselves take the quiz and use the products and share that knowledge back with the database, it becomes stronger and more accurate as time goes on," Zhao said.

This personalized e-commerce model also allows Proven to appeal to demographics Zhao said have been underserved by the beauty industry, such as ethnic minorities, those living in rural areas and men.

"As our users and our customers and ourselves take the quiz and use the products and share that knowledge back with the database, it becomes stronger and more accurate as time goes on." -Ming Zhao, co-founder, Proven Skincare

Through the quiz, Proven is amassing intimate and potentially revealing data from its customers. Yet while companies have approached them about using the data, Zhao said they "never entertained any such idea."

"Our plan is to use data to serve our consumers, and it is purely an engine for better understanding and products for our consumers. We will not sell data," she said.

Personalization via tech is on the rise

Proven is not alone in catering to the individual needs of consumers in the facial skincare market. Industry giants such as Clinique and L'Oréal are exploring the use of camera technology and augmented reality to customize recommendations. Other start-ups are betting on skincare regimens based on DNA analysis and monthly test strips.

Zhao said Proven has evaluated such options, but they believe their data and questionnaire currently can achieve enough personalization without adding a customer's genome sequence or beauty camera technology.

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While DNA testing for beauty and skincare has been on the rise for a few years, there is a disconnect between getting the analysis and acting on it — often due to the premium cost for consumers, according to Mintel analyst Sarah Jindal.

Companies like Proven, which aims to take into account gene expression along with external lifestyle and environmental factors, are now connecting more dots for the consumer.

This aligns with the industry as a whole as companies find more ways to use technology to create individualized products with a more "integrated and holistic approach" in determining what impacts skin, Jindal said via email. "As consumers take a more well-rounded approach to beauty that encompasses health and wellness, they start to understand the relationship of all of these factors and how they impact them overall."