Data-driven skincare

In July 2019, Japanese personal care company Shiseido unveiled their new Optune skincare subscription, which uses an app to analyse users’ skin and produce daily skincare recommendations based on that day’s reading. The app takes into account the environment – including pollen count, temperature and pollution – as well as inputs like sleep, menstruation and even mood to calculate the optimal combination of five serums, all contained in the user’s at-home dispenser. With over 80,000 combinations possible, the serum cartridges are replaced on a monthly basis and cost 10,000 yen ($92) a month.

Optune was developed with ease and simplicity in mind as many consumers don’t have time to find the perfect skincare. At a press conference, Shigekazu Sugiyama, president of Shiseido Japan, said the subscription service targets people with “the dilemma of valuing skincare but struggling to find the time to find the perfect formula.” By utilising data, this innovative tool can deliver on skincare enthusiasts’ needs on an everchanging basis.

Due for release in summer 2019, Atolla, an MIT-backed start-up, is releasing their own data-fueled skincare subscription. Once a month, users test their skin, sending readings back to Atolla who uses machine learning to develop a personalised skincare routine which changes as one’s skin fluctuates through the months and seasons. As COO Sid Salvi said, “We use data to inform all our important decisions, so why not for taking care of our skin?”