Weekly Stories

How are AI and virtual experiences transforming the beauty industry?

Reported by Grace Howard on Apr 10, 2018 12:15:00 PM

 Curology-374687-edited

Anyone who’s tried to buy a lipstick or a foundation online, only to be disappointed by the shade once it turns up on their doorstep, will attest to the fact that buying beauty online isn’t often an easy ride. However, things are changing. Thanks to deep data and machine learning, it’s becoming increasingly possible to find products that work without having to head into a physical store to sample them first.

WWD states that AI is “evolving from Silicon Valley buzzword into a tool for brands”, and big names, are beginning to harness it. AI-powered bots, primarily running through Facebook Messenger, are one of the easiest ways to tap into machine learning technology. L’Oreal, Sephora and Estee Lauder have all developed bots that’ll allow you to do everything from finding the ideal lipstick or hair colour to stocking up on your go-to shampoo or booking an in-store beauty consultation. Global Web Index notes that “although chatbots remain in their infancy, there are clearly defined use-cases for this tech in beauty. Beauty is much more personal than other industries, and messaging tends to succeed when it’s personalized – whether that’s personalized product recommendations or beauty tips.”

AI is also assisting shoppers to find more personalised product recommendations, particularly when they’ve come from social media. Makeup brand ColourPop, for example, uses an algorithm-based discovery feed on its website to help to push social media content into something shoppable – something which has proved to be difficult through Instagram due to brands’ inability to include direct links in post captions. “If you can experience a brand through other apps like Instagram or YouTube, then go and shop a feed that knows not only if you came from an app but what people like you are shopping, then people will shop,” Nate Dierks, director of technology at Colourpop, explained to Digiday.

Then there are the slew of lesser-known but fast-growing companies who are using tech to create tailor-made beauty products. One such example is Proven, a startup which takes a ‘rational, logic-based’ approach to finding skincare solutions for its customers. The company has created an AI platform which, according to the company, has worked out what different consumer segments want based upon analysis of over 8 million product, 20,000 skincare ingredients and 100,000 skincare products. Sifting through this data gives Proven invaluable insight into what works – and doesn’t – for particular skin types.

In a similar vein there’s Curology, which specialises in creating personalised skincare products for acne sufferers, and Function of Beauty, which creates hair products based on a customer’s needs. A notable thing that these startups have in common is that they utilise quick, user-friendly questionnaires to determine what shoppers need. The information is then run through algorithms that’ll suggest a number of suitable products.

Technology is commonly purported to put jobs at risk but, according to a study by Gartner, by 2020 AI will be creating more jobs than it eliminates. The company predicts that, while culling 1.8 million jobs, AI will go on to create 2.3 million new roles in 2 years’ time. Gartner’s report also suggests that things will remain rosy for shop floor staff in the beauty sector – “consumers still prefer to interact with a knowledgeable sales associate … particularly in specialized areas such as home improvement, drugstores and cosmetics, where informed associates can make a significant impact on customer satisfaction.” 

To carry on the conversation, join us at Stylus presents Decoded Future (26th June, Tobacco Dock, London) where we’ll explore how AI is making shopping for beauty easier, more convenient, more personal, and expanding the notion of industry ‘norms’ - as well as driving innovations and conversions for brands. Book your ticket here.

Image Source: Curology

Topics: Weekly Stories

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