This is the second of a four-part series on the rapid advent of technologies that’s revolutionizing Hong Kong’s economic landscape. In this article, Oswald Chan takes a look at the flourishing technology startups that are poised to transform the local retail scene
Chinese mainland e-commerce behemoth Alibaba Group joined forces with US-based fashion retailer GUESS and launched a three-day Fashion AI concept store last month at Hong Kong Polytechnic University. Powered by the tech giant’s latest technologies, the Fashion AI machine in the store can provide mix-and-match recommendations based on the user’s choice of items. (PARKER ZHENG / CHINA DAILY)
‘Experiential retail” is another convulsion brought by technologies that can radically transform Hong Kong’s retail sector.
Done correctly, this is not just about elaborate designs or gimmicks within the four walls of a store. It could be a signature scent or soundtrack, technologically advanced fitting rooms, or an optimized checkout process that can herald a new futuristic shopping experience.
By the end of this year, shoppers in Hong Kong may purchase the latest fashion and accessories in artificial intelligence-powered retail outlets operated by US-based fashion retailer GUESS.
Fashion AI can now recommend items that match the personal style, offer imagination for consumers and inject new ideas into fashion brands and retailers to enable them to rethink their business and sales models ...
Zhuang Zhuoran, Vice-President, Alibaba Group
Customers with Taobao or Tmall accounts could scan these online stores’ ID code on their mobile phones before shopping at Chinese mainland e-commerce behemoth Alibaba Group Holding’s Fashion AI concept pilot store at Hong Kong Polytechnic University from July 5 to July 7.
Taobao and Tmall are the two online shopping websites founded by tycoon Jack Ma Yun’s Alibaba Group with more than 1 billion active monthly users combined as of February this year.
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GUESS has been collaborating with Alibaba, taking five months to launch the concept trial store. It offers the retail expertise, while Alibaba leverages its AI technologies to provide smart racks, smart mirrors and smart fitting-room facilities.
When a customer picks up a particular fashion item, Alibaba’s proprietary AI-powered machine learning and computing vision technologies can identify the fashion elements, including the color and style of that piece of haute couture.
The AI machine will then provide AI-based mix-and-match recommendations on the smart mirror inside the store. The mirror has a “Taobao Wardrobe” section, which shows the possibility of consumers identifying matching pieces from the GUESS line in the store for any item they had previously purchased on Taobao or Tmall.
Images of more than 500,000 outfits put together by fashion experts from Taobao and Tmall partner brands will be displayed. Cross-brand recommendations are also provided for customers looking for the most fashion-conscious and creative advice.
As consumers pick up a particular piece of fashion or accessory, the products will be automatically displayed on the smart mirror as they are attached with Gyro-sensors — a bluetooth low energy chip and a radio-frequency identification chip.
After a customer has chosen an item on the smart mirror and would like to try it out, retail staff will be alerted by the in-store system and prepare the selected item or items in the fitting areas for the customer, avoiding the hassle of having to lug multiple products into the room.
The record of purchases at the offline store will be automatically reflected on the customer’s mobile Taobao or Tmall.com account to enable the consumer to find more mix-and-match recommendations from other brands at Taobao and Tmall.com, expanding the recommendation capability beyond the limits of an offline store.
“Fashion AI can now recommend items that match the personal style, offer imagination for consumers and inject new ideas into fashion brands and retailers to enable them to rethink their business and sales models. Leveraging AI in fashion, therefore, offers many untapped opportunities for fashion retailers,” said Alibaba Group Vice-President Zhuang Zhuoran.
Red hot fashion label
The use of big data analytics and online computing makes fashion brands smarter in ordering and maintaining inventories in the limited space of an offline shop, thus improving sales and supply-chain management, he said.
GUESS launched its online flagship store on Tmall in 2013, and the brand has become one of the most popular fashion labels. The fashion retailer’s online store at Tmall has seen growth surpassing 100 percent in the past three years.
“It’s important that we continue to invest in new technology and platforms. We plan to extend this project in the region as the future of retail,” said Jose Blanco, chief executive officer at GUESS Greater China.
Alibaba’s fashion AI technology is developed jointly by its Vision and Beauty Team and the Institute of Textiles and Clothing of Hong Kong Polytechnic University. The two parties developed the “Fashion AI Dataset” technology with a fashion image database to train the machine to accurately understand and recognize the attributes of each image.
In this undated photo, SoftBank Group Corp’s Pepper humanoid robot Timmy greets young customers with auspicious messages at Hong Kong International Airport in 2017. Retailers and landlords in the city are urged to invest more in technology to harness AI technology, such as robotics, to improve customer services. (PHOTO / BLOOMBERG)
The AI fashion technology would help improve online fashion image searching accuracy and augment the effectiveness of cross-selling and up-selling, creating an innovative buying experience, as well as facilitating customization of online shopping platforms.
Retailers, however, face challenges as to how to determine the data which is the most useful for their business and have them turned into real insights that will impact productivity and their bottom lines. It’s essential for them to invest in the right data storage, analytics platforms and digital analysis talents to help them come up with a bigger picture of how their sales and marketing strategies can be aligned.
Gartner — a global technology investment research firm — says, however, Hong Kong retailers’ investments in technology are inadequate.
The AI fashion technology would help improve online fashion image searching accuracy and augment the effectiveness of cross-selling and up-selling, creating an innovative buying experience, as well as facilitating customization of online shopping platforms
“Local retailers are still focusing on profit margins and are thus less inclined to invest to strengthen customer experience and brand image because these investments may not bring immediate profits,” said Terick Chiu, vice-president executive partner at Gartner. “They’re still championing product promotion as the main business credo.”
“Actually, retailers can consider harnessing AI technology, such as robotics, to improve customer services, as well as leveraging big data analysis and social marketing platforms to perform more predictive analysis of consumer behavior patterns,” Chiu told China Daily.
Hong Kong’s retail market is well positioned to evolve into an omni-channel solution, which allows for a myriad of retailing platforms and formats — from mobile, social media to physical stores, online stores and search engines — to be seamlessly integrated to provide a rich source of data that can be analyzed to create a personalized marketing and sales channel for every consumer.
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Besides selling products, retailers now have to provide various value-added services to offer a seamless shopping experience for customers, including stronger warranties, bespoke post-purchase, loyalty programs or even special events.
“The growing popularity of mobile payment and wider adoption of big data analytics will move us in this direction, and elevate the overall shopping consumer experience. This certainly requires retailers and landlords, such as mall operators, to invest more heavily in technology,” predicted Denis Ma, head of research at Jones Lang LaSalle Hong Kong.
A lot of retail technology startups are burgeoning in Hong Kong, and are on the threshold of giving the city’s retail market landscape a significant facelift.
With the passion to make data accessible to everyone, two Australians — former Groupon data analyst Alex Man and former Google software engineer David Yang — founded ChatQuery in 2017. The on-demand chatbot can answer business data questions and handle some 90 percent of the questions asked, leaving the rest of the tricky questions for the staff to deal with.
Users submit questions to the chatbot in plain language, and the AI-powered virtual data analyst responds with accurate answers to help the company make better decisions. This will be particularly useful for e-commerce players who cannot find or afford their own data analytics team.
Many large-scale retailers and small e-commerce players are currently clients of the Cyberport incubatee. The startup aims to showcase the future of data analytics and determine whether it’s feasible to develop the Cantonese market. “Our passion is to make data accessible to everyone, so we replaced Excel with an on-demand chatbot. It’s like having a giant team of data scientists for everyone in your business to help them make better decisions,” said Alex Man.
Goods return is also a major hurdle for retailers and e-commerce players as they have to deploy resources to engage customers in the process.
Digital payment methods have sprung up around Hong Kong as local retailers race to adopt e-payment to enable smoother transactions. (PHOTO / BLOOMBERG)
Transport Intelligence — a global research company specializing in the transport, logistics and express sectors — estimates that the goods return rate can vary from 25 percent to 50 percent for some e-commerce players. Return costs can be as high as 50 to 60 percent in the fashion business.
Pieter Paul Wittgen, Jim Cornford and Seb Poole, who had all worked at Hong Kong-based omni-channel fashion brand Grana, set up Olasso to address this pain point.
Olasso is a management platform aiming to deliver post-purchase services for customers and using AI to reduce the operational, financial and environmental impact on returns for online retailers.
“Returns are still a major pain point holding back the growth of e-commerce with customers often experiencing a painful returns journey, which reduces brand trust and loyalty. We’re committed to building a better returns experience for customers, while reducing the financial, operational and environmental impact for retailers,” said Wittgen.
This retail technology startup has a prototype which they hope to further develop to understand customer pain points.
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ChatQuery and Olasso were winners of the third-round The Cage — a three-month incubation program for early-stage startups working on retail technology operated by Asian retailer Lane Crawford Joyce Group.
The program consists of three phases — first for startups learning how to focus their applications in the retail context; then validating their business ideas by testing their theories on a retailer’s teams and customers; and pitching their products to a retailer group’s companies for a commercial agreement and external investors for potential funding.
The Cage will provide ChatQuery and Olasso tailored one-on-one mentorship schedules, go-to-market strategies with commercial opportunities, exposure to the Asian startup ecosystem and industry experts, and access to a post-program business network.
“We never know what will be co-created each year and the outcome is never prescribed. This is the key to the program, and it opens up infinite possibilities. The Cage is our opportunity to co-create new ways of approaching our business,” said Jennifer Woo, chairperson and chief executive officer of Lane Crawford Joyce Group.
Since 2016, The Cage has nurtured four retail technology startups other than ChatQuery and Olasso, ranging from AI-powered machines for preventing theft and enabling self-checkout to multi-lingual AI chatbots for elevating fashion and lifestyle customer experience.
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