MARCH/APRIL 2018 29 “The platform takes the best part of online to help the offline part of a brand,” Ballin says. “It makes discovering nearby retail fast and simple. You select brands you like, items you like, sizes you require, and when you are near a retailer that has what you’re interested in, the app notifies you.” This could be within department stores, malls, or main shopping streets, Ballin explains, because it works through seamless integration with a retailer’s inventory. “As a retailer, you are targeting customers who want to know about your brand, your inventory, your location,” he explains. “The platform allows you to create relationships with new and existing customers.” Operational in Dubai and London, the Shopest platform will soon be available in New York. MATCH MY SHAPE The company LikeAGlove also helps match consumers with brands—specifically jeans that fit. Consumers purchase smart leggings embedded with technology that measures high waist, low waist, high hip, and low hip. The leggings transmit measurement data to an app that then matches the consumer shape to a number of brands: Levi’s, Lucky Brand, Old Navy, 7 For All Mankind, Gap, Citizens of Humanity, American Eagle, Ann Taylor, True Religion, and more. Amazon’s recent acquisition of Body Labs, a software provider of human-aware artificial intelligence that understands the 3D body shape and motion of people from photos or videos, has many speculating on how quickly body imaging technology will improve and influence online shopping. VIRTUAL TRY ON Since 2008, Metail has been offering size and style advice to online female shoppers based on Body Modelling and 3D Modelling. Consumers get a simulated version of themselves that takes into account size and weight. A M.L. algorithm provides data to fashion bots continuously from a customer base of nearly eight million users—most of whom are based in Asia. Since launch, Metail has digitized more than 80,000 garments for virtual try on. Earlier this year the company received £10 million in Series B investment and plan to launch a men’s service later this year. The company also provides data from customer interactions back to retailers as a service. Consumers in the beauty industry have been trying on makeup looks from L’Oreal’s Makeup Genius app since 2015. Facial tracking technology allows a user to try on different makeup looks, share the images, and buy the products. Maybelline’s Colorshow A.R. was created by Blippar, a firm specializing in A.R. and Computer Vision (the field within A.I. that understands sight). By harnessing these technologies, Bilppar bridges the physical and the digital to push the boundaries of visual search and user experience. Using the Blippar app, a customer can aim her smartphone at the relevant Maybelline print ad to unlock a try-on feature that allows the customer to see how her hand will look in 40 shades of Maybelline’s nail polish. “Although launched nearly 3 years ago, Colorshow still has an average of two minutes of engagement time,” says Mikela Eskenazi, Commercial Director Blippar. While the app was designed to help customers see how a color looks against skin tone, the data collected has helped Maybelline understand what colors are popular, driving stock to store inventory in areas where the app is in use, she explains. VIRTUAL ASSISTANT Also powered by Blippar and deployed to more than 300 Boots/Walgreens stores, Max Factor’s “Beauty Consultant In Your Pocket” gives a user product information, tutorials, and customer reviews by scanning any of 500 Max Factor products. The A.R. Virtual Assistant experience informs women at key moments through knowledge and inspiration to choose the right product for them. Product can be purchased in store, online, or saved to wish lists (particularly helpful if the product is currently out of stock). The experience has resulted in 82% “Buy Now” click-throughs, with 70% of women trusting the advice from the “virtual assistant.” And while the thought of undertaking A.R. on such a large scale may seem daunting, in this case, content for the app was already created for other online channels, Eskenazi explains, making the app the amalgamation rather than creation of content. HOW DO I LOOK? “Facial recognition is becoming key as a personalization tool,” Eskenazi says. “With A.R., A.I., and M.L., it’s possible now for an app to understand the mood, patterns, and features of a consumer to recommend the right product, and help her to step-by- continued on page 30 continued from page 28 FE ATURE