Beauty marketers have embraced an array of artificial intelligence (AI) applications like using augmented reality (AR) to virtually try on lipstick or relying on chatbots for guided selling and to power personalized product recommendations.
With so many brands, products, formulations and shades, it's not surprising that 70% of US female beauty buyers said they were overwhelmed by product choices in a May 2018 survey by conversational marketing firm Automat.
One answer to the overwhelming sea of choices could be virtual beauty advisors like Sephora’s Virtual Artist, which allows users to upload photos in Messenger to "try on" bot-recommended user-selected shades of lipstick, and Madison Reed's bot Madi, which suggests hair colors based on user uploaded pics.
Nearly half of beauty buyers in the study said they would be likely or very likely to use a virtual beauty advisor when shopping for products online or offline.
Roughly one-third were unsure, which isn’t unreasonable since the concept isn’t widespread. When asked, though, 32% had heard of virtual beauty advisors, a higher recognition than other beauty tech like virtual try-ons (28%) and in-store skin scanners (22%).
Just a few years ago, there was excitement around using AI-powered chatbots in ecommerce. That hype has died down a bit, but the beauty industry is still experimenting with the technology. According to an April 2018 Celebrity Intelligence survey, a majority of beauty marketers worldwide believe technology like AI-powered personalization across email and social (65%) and AR for makeup discovery (58%) will be adopted at scale in the next two years.
Malik Abu-Ghazaleh, vice president of digital marketing and ecommerce at Lancôme, said he was exploring conversational commerce, but it didn't seem right as a near-term engagement solution for the brand. "It's more about things working in the background and suddenly transforming your experience on the site as a result of the AI that we're able to infuse," he said.
More specifically, Lancôme is testing AI to deepen its site personalization beyond the typical, "customers that bought A, also bought B" approach. The company launched a beta version in October 2017 that uses a combination of shopper behavior and user-provided details to customize the experience.