No doubt, we've entered the golden age of skincare. With customers spending billions of dollars a year on creams, serums, and cleansers that promise such miracles as wrinkle reduction, faded dark spots, improved elasticity, and beyond--you would think we'd be getting our fix. But even with a surfeit of products on the market, consumers are finding themselves increasingly frustrated with their unsolved skin struggles--and brands' broken promises. Founded by Harvard MBA Ming Zhao as well as Stanford PhD and computational physicist Amy Yuan, the up-and-coming beauty brand harnesses the power of science to transform the way we approach our skincare. With the understanding that no two people's skin is exactly the same, they set out to develop a data-driven model that delivers customized products made just for you, taking into account not only your skin type and skin concerns, but also your environment and your lifestyle.

Not all skin (or skincare) is created equal. One of the biggest challenges facing skincare consumers today is finding products that work for them--their unique skin type and the unique challenges they face with their skin. And, you won't find it on Google. The one-size-fits-all approach that most skincare and beauty companies take just doesn't deliver the unique skincare solutions consumers need to get their healthiest complexion. This doesn't give individuals the personalization they need.

Not all skin (or skincare) is created equal. One of the biggest challenges facing skincare consumers today is finding products that work for them--their unique skin type and the unique challenges they face with their skin. And, you won't find it on Google. The one-size-fits-all approach that most skincare and beauty companies take just doesn't deliver the unique skincare solutions consumers need to get their healthiest complexion. This doesn't give individuals the personalization they need.

Not all skin (or skincare) is created equal. One of the biggest challenges facing skincare consumers today is finding products that work for them--their unique skin type and the unique challenges they face with their skin. And, you won't find it on Google. The one-size-fits-all approach that most skincare and beauty companies take just doesn't deliver the unique skincare solutions consumers need to get their healthiest complexion. This doesn't give individuals the personalization they need.

Not all skin (or skincare) is created equal. One of the biggest challenges facing skincare consumers today is finding products that work for them--their unique skin type and the unique challenges they face with their skin. And, you won't find it on Google. The one-size-fits-all approach that most skincare and beauty companies take just doesn't deliver the unique skincare solutions consumers need to get their healthiest complexion. This doesn't give individuals the personalization they need.

Because big data gives feedback untainted by human agenda, it allows companies to identify an audience, mistakes and opportunities as accurately as possible. And it is also enabling companies to provide consumers with precise beauty services and products. Of courcse, large brands are no stranger to utilising insight gathered from analysing data. The Tmall Innovation Centre (TMIC), by the Alibaba Group, is dedicated to reverse engineer the process of developing products. By analysing data from Alibaba's massive e-commerce ecosystem, TMIC identifies new product opportunities for very specific Chinese demographics, letting the customer data determine the product should be developed.

These are all buzzwords that regularly crop up in the beauty industry, driving women (and men) all around the world to spend thousands of dollars on skincare products that they may or may not need. In fact, the global skincare industry is currently estimated to be worth around $130 billion by 2019 -- that's a lot of miracle cures. And we can only assume that the industry will snowball even further in this selfie-obsessed age. People want to look good -- fact. But with so many products to choose from, it can often be a quagmire of irrelevant creams and dissatisfying serums out there. One new startup sees itself as the beauty industry's knight in shining armor.

YC-backed startup Proven wants to make it suck less for women to find skincare that works for them. The co-founders are taking what they describe as a "rational, logic-based" approach to figuring out which ingredients might be most appropriate for each individual. As a TC Disrupt battlefield founder once memorably put it during her on-stage pitch, the beauty industry makes a whole lot of money from a whole lot of BS. And skincare falls squarely into the'full of it' category, with its expensively marketed pseudoscientific claims touting'miracle' fixes that most definitely aren't. Proven's co-founders, Ming Zhao and Amy Yuan, say frustration when battling with this BS via their own skincare issues ultimately led them to found the business together.

YC-backed startup Proven wants to make it suck less for women to find skincare that works for them. The co-founders are taking what they describe as a "rational, logic-based" approach to figuring out which ingredients might be most appropriate for each individual. As a TC Disrupt battlefield founder once memorably put it during her on-stage pitch, the beauty industry makes a whole lot of money from a whole lot of BS. And skincare falls squarely into the'full of it' category, with its expensively marketed pseudoscientific claims touting'miracle' fixes that most definitely aren't. Proven's co-founders, Ming Zhao and Amy Yuan, say frustration when battling with this BS via their own skincare issues ultimately led them to found the business together.

A new beauty startup, Proven, is using artificial intelligence to determine the best skincare routines for people based on their skin type and needs, and all of the products will be made in-house. Amy Yuan, one of Proven's co-founders, uses her computational physics background to build an "AI engine" that pores through reviews of various skincare products, reports TechCrunch. Proven claims the machine has analyzed 8 million reviews, 20,000 ingredients, and 100,000 products using fraud-detection algorithms to rule out fake reviews. By looking through a massive quantity of data, the machine can then determine trends and general patterns in what products are suitable for particular skin types. Proven suggests a skincare routine for you via a considerably detailed quiz that asks questions like where you live, whether your skin is oily or dry, and what skincare products you can't live without.