Problem: Every person’s skin is different and unique. However, most skincare brands adjust for these differences through massive selection of various products: a tedious task for consumers to sift through.
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Solution: A company that uses AI to customize skincare (similar to what Winc does with a survey that allows users to find the wine that they use through a subscription service). The business would be structured with 5 quick steps: (1) have all new customers take a survey about their skin (or in another iteration, they could send a graft of their skin in the mail to the company); (2) customers will receive a variety of products to use in the mail within 3-5 business days; (3) customers use the products while taking pictures of how their skin has changed and is reacting; (4) customers send back finished products to the company; (5) after looping through 2-4, the company could create a hyper-specific serum for the individual — “the Lisa serum” or “the Jackson serum” that is best used for that individual and that individual only. Through importing data and continuously exporting new tweaks to products, customers can go from being cookie-cutter to being the cookie.
One surprising business that already has an operating model like this is Starbucks (or should I say, “the Bank of Starbucks”). With almost $3 billion of cash loaded into loyalty cards, Starbucks has become a master of platforming users to experience their whole customer journey through the Starbucks app. Perhaps the most important part of this innovation is the fact that today Starbucks makes more than 170,000 customizations of beverages. While some are duds, many can be used to create entirely new flavors of drink in Starbucks’ in house research-and-development team. What if this same technology and skillset was applied to skincare where there can be more than 7 billion variations?
This idea is not necessarily new, but no company has yet broken into the space as a clear market leader. As described in Dezeen magazine,
Bespoke, smart and made-to-order is the new face of the skincare industry, where product designers are applying artificial intelligence and machine learning. Rima Sabina Aouf spotlights seven brands demonstrating this.
The last two years have seen the rise of several startups that combine data with dermatology. These companies typically share some common principles – new customers will provide detailed information about their needs and lifestyle, and an algorithm will choose the right ingredients and formula to suit.
The machine learning component also plays an important part, as feedback from users constantly provides more information from which the algorithm can hone the product further.
The 7 companies mentioned are (1) Atolla, (2) Proven, (3) Atypical, (4) HelloAva, (5) Curology, (6) Shiseido's Optune, and (7) Identité by Seymourpowell. These 7 companies are contributing to what Orbis describes as a global cosmetics products market that is expected to “reach $806 billion by 2023… Meanwhile, AI will reach $12 billion by 2023 in global spending by retailers, including beauty, up from an estimated $3.6 billion this year according to Juniper Research, a UK-based company.” Other research hypothesizes that “companies will increasingly sell products via eCommerce sites, revealing that orders via smartphone rose to $1.53 billion in 2017,” welcome news for a direct-to-consumer cosmetics business.
Monetization: Sales from these products or subscription to have a customized serum for you.
Contributed by: Michael Bervell (Billion Dollar Startup Ideas)