Malaysia-based VLT Develops AI Powered Shopping App

Kuala Lumpur, Malaysia, 29 March 2018 – VLT, the Malaysian award winning innovation, product and design firm recently developed ‘Shop You’, an Artificial Intelligence powered retail and fashion solution, aimed to bring the technological advances to the fashion and retail industry.

According to research done by fashion-tech entrepreneurs Kelly Slessor and Emma Sharley based in Australia, only 2 out of 10 women actually enjoy shopping, while the rest dislike the time and hassle it takes, and the fuss in returning items.

With  online shopping, while 60% of traffic to a retailers site is derived from mobile, the conversion rates are discouraging because of complicated navigation, and shoppers being overwhelmed by choices.

With that in mind, VLT, was tasked by the duo to develop “Shop You”, the fashion app that would intuitively personalize a shopping experience by matching your needs with what you would actually buy  – akin to being a personal stylist, albeit online.

The app personalizes the end-to-end customer journeys with visual intelligence and fashion insights by applying artificial intelligence, using data from searches and purchasing behaviors, and continuously learns about a shopper over time. Launched in February 2018 this year, Shop You already boast partnerships with over thirty prominent Aussie and international brands, including Witchery, Spell, Uniqlo, Ellery and Cotton On.

“The technology we are building in partnership with VLT will provide the ability to grow quickly and at scale. Australia is only the beginning!” said Kelly Slessor, founding partner of Shop You.

“It is only natural that AI moves into retail and fashion as it has been seeping into various industries. We wanted to find a way to mitigate the hassle of both shopping and staying in style and developed the requirements needed to achieve this for Shop You. The  AI powered app, cleverly learns the shopper’s DNA and narrows down searches, suggesting predicted preferences instead of bombarding the shopper with unnecessary recommendations,” added Adrian Lim, CEO of VLT.

The experience begins with the on-boarding process which seeds the user’s initial preferences in the backend.  Then the recommendation engine works by taking the  user’s preferred brands and progressively filters out non-matching user preferences and finally applies other contextual information such as Product Categories, Color and Body Type. This recommendation process is further enhanced with Natural Language input by processing and understanding a user’s input from the App chat window.

The result is essentially a very personalised list of product recommendations akin to the user having the shoppers  very own personal stylist to recommend fashion products to the shopper, increasing the success rate of the user arriving at his/her desired outfit. Then the user is able to easily purchase the product from the App via the Fashion retailer website.

Whilst at the retailers end, to simplify and scale the data-entry of products into the system, VLT designed an automation algorithm for data import where the system relies on a series of product feeds from feed providers, imports it, then also periodically scrapes the Fashion retailer’s website for matching products and tag to further enhance the data available for each products.

This ensures that the latest designs are made available to the user as soon as it is released online. The app is so versatile that it can be easily and quickly applied to any international fashion market, regardless of the labels available.

“At VLT, we’re all about pushing boundaries, leveraging technology and in this case specifically AI, to further enhance the user experience in the many industries we work in. The benefits of such predictive technology allows retailers to reach customers and convert them at a higher rate. The line between a shopper completing a purchase transaction and leaving it unfulfilled is really fine and we want to close that gap, and in doing so demonstrating the defining difference AI can make,” added Lim.

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