AI, Analytics Power Luxury Retail Customer Experience
The personal luxury goods market is growing, thanks to renewed interest from millennials. The retail channel of the global luxury goods market grew 4 percent in 2018, according to a report by Bain & Company. However, it still faces tough competition from wholesalers and online sales.
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From a regional standpoint, China, Japan, Europe and the United States all saw positive market growth in 2018. Chinese consumers are leading the growth trend both domestically and abroad, with an estimated 33 percent of global luxury spend in 2018, according to Bain & Company.
Nowadays, everything is becoming digitally influenced in one way or another, and luxury sales are no exception. A report by McKinsey & Company stated that nearly 80 percent of luxury sales today were “digitally influenced,” meaning that “in their luxury shopping journeys, consumers hit one or more digital touch points.”
For luxury retailers, this means it is becoming critically important to better understand customers’ wants and needs in order to meet and exceed brand expectations. That is why luxury retail is finally starting to utilize artificial intelligence (AI), video analytics and other technologies and techniques more widely. By using such solutions, luxury retailers are now able to get a more in-depth look into what their customers want, not only improving the customer experience but also driving sales.
Luxury Brands Turn to Technology to Woo VIP Shoppers
Providing the best customer experience is one of the most important aspects of luxury retail, and retailers are turning to technology to ensure every customer feels like a VIP.
Tough competition for high-spending consumers means luxury retailers must provide VIP service at every step of the way. As Ray Hartjen, Marketing Director at RetailNext, puts it: “Shoppers don’t need to shop at any brand. Brands need to make shoppers want and feel like they need to shop a brand. Technology can help.”
Pressured by new entrants and online sales, luxury retailers are adopting fresh tools to better understand their customers. According to Andrew Fowkes, Head of Retail Center of Excellence at SAS UK and Ireland, this includes “looking at the end-to-end lifecycle of the products and services they sell — recognizing the importance and profit that can be made from ‘outlet’ business as well as full price offerings.” Hartjen pointed to the “connected journey” of high-end consumers, saying that following this from beginning to end could provide key information to retailers. “It will be important for luxury retailers to tie into and integrate seamlessly with shoppers’ connected journeys. They will need to understand how shoppers’ online experiences drive store visits, and how store visits have tangential and residual impacts later on in the brand’s digital touch points and channels. And, of course, they need to understand the key branded interactions that convert shoppers into buyers,” Hartjen explained.
“Luxury retailers are in many ways leading the retail industry’s response to shoppers’ connected journeys. Activations are regularly popping up around the globe where influencers and shoppers experience a brand and its ethos in ready-for-Instagram settings. The activations are more brand showroom than retail store, where the brand is the hero, not its products, and they allow for an almost continual sharing through shoppable social media platforms,” Hartjen said. “Luxury is investing in the shopping experience, because it’s what shoppers want and crave, and what’s good for shoppers is good for business.” Parallel to understanding the connected shopping journey is the need to understand who the shopper is. “Relevant communication and engagement is paramount to success, and in the luxury sphere, relevant means personalized,” Hartjen added. “The luxury segment needs to engage on a personal level, and to get shoppers to reveal personal information, there has to be value in it for the shopper. Those brands that do it well will have a loyal customer for life.”
While gathering consumer data can help retailers provide a personalized shopping experience, they must also comply with GDPR regulations. For instance, although video analytics and face recognition data is useful, GDPR rules require customer consent before such data can be used. But Stephanie Weagle, CMO of BriefCam, believes that should consumers opt in, luxury retailers can use data to optimize and personalize the shopping experience even further.
“Luxury retailers can create lists of VIP customers and upload images of these visitors to their video-content analytics engine. The video analytics solution can be configured to alert operators when key customers are recognized entering the store. By triggering a call to action any time a VIP customer walks into the store, sales associates can be mobilized to engage the visitor immediately and personally. When face recognition data is integrated with historic sales data, the retailer can quickly review and understand individual customer shopping trends and prefer- ences based on past purchases, and use this information to share personalized and relevant information and offers to drive sales,” Weagle said.
How Machine Learning, AI Improve the Luxury Retail Experience
Luxury retailers are utilizing machine learning and artificial intelligence (AI) to better understand customer needs and improve the shopping experience.
Artificial intelligence (AI) and machine learning are being introduced and utilized by nearly every industry. This includes the luxury retail sector, where advanced algorithms are allowing retailers to enhance the customer experience both in-store and online. Brands such as Dior have launched AI chatbots that can interact with and make recommendations to online shoppers. Burberry’s flagship store in London meanwhile, has fully embraced the digital age with a host of interactive multimedia tools, including smart mirrors that double as screens. In-store, luxury retailers are using AI and augmented reality (AR) to provide customers with a more personalized and immersive shopping experience. An example of this is smart mirrors, which can automatically recommend accessories for a given outfit, as well as allow shoppers to make a 360-degree video and change the color of clothes.
While luxury retailers still rely on human sales associates for the time being, AI and machine learning are playing an increasingly larger role in helping brands interact with their customers. As a report by McKinsey & Company states: “Big data and machine learning are bringing authen- ticity and relevance back into the customer relationship,” by providing advanced analytics to help brands offer services uniquely tailored to each customer and occasion. According to Andrew Fowkes, Head of Retail Centre of Excellence at SAS UK and Ireland, “applying machine learning to in-store data has great potential to help luxury retailers better understand their customers through their entire lifecycle.” He added retailers were also “utilizing these techniques to better understand demand patterns, to have the high-value merchandise in the right part of the world to fulfill demand.” Fowkes said luxury retailers were deploying machine learning techniques to better understand their customers and keep them engaged with a brand. Such techniques were also used to “apply more real-time context to offers or messages they put in front of their customers, or the messages their employees can use to sell more when face-to-face with the customers.”
Ray Hartjen, Marketing Director at RetailNext, emphasized the need for accurate footfall data, noting the importance of deep-learning based sensors such as RetailNext’s Aurora v2, which can accurately distinguish between customers and reflec- tions, shadows and shopping carts piled high with merchandise. Hartjen added that advanced sensors and processes were able to determine shoppers from sales associates, providing not only accurate footfall data, but also information on how, when and where shoppers and staff interact.
“Inside the store, sensors with AI determine what shoppers are doing at displays other than dwelling within a certain geo-fenced location. For example, the sensor can determine if a shopper reaches for an item, picks it up, looks at it more closely or tries it on, returns it to the display, etc. Deep-learning based human activity recognition delivers the data that allows for retailers to modify their store layouts, displays, fixtures, product assortment, staffing models — everything really — to drive the desired outcomes they’re designing toward,” he said.
Fowkes also pointed to the use of “computer vision;” a new discipline that trains machines to interpret and understand the visual world using digital images from cameras combined with deep learning models that mimic the processes used by the human brain.
“Our most developed customers can join online browsing data, social media influence and even images deploying computer vision techniques to automatically generate attributes. These attributes can then be used to fine tune customer real-time offers or future design and development of products,” Fowkes said.
Video Analytics: Providing Business Intelligence to Luxury Retailers
While the use of video analytics in luxury retail isn’t new, advanced algorithms are making it an increasingly invaluable business tool.
Video analytics are an optimal solution for luxury retailers. Not only does it enable them to leverage existing resources to gain operational intelligence, it also empowers them with the data to personalize and optimize the in-store experience. This helps to cement brand loyalty, increase engagement and ultimately drive sales. “Whether customers are window shopping, walking through the store, interacting with products or dwelling at certain displays, video analytic data helps the retailer understand visitor behavior and tailor the experience to meet consumer demands and expectations: from understanding when to mobilize sales associates to engage customers, to how to update the store layout for optimal navigation, video business intelligence empowers retailers to cater to luxury shoppers based on qualitative, actionable data insight,” said Stephanie Weagle, CMO of BriefCam.
While in-store video surveillance still has security monitoring functions in luxury retail, now more than ever it has become an important source of data. This is due to advances in analytics, which have retailers seeking new and innovative ways to collect and utilize data, while also taking advantage of existing resources such as video. “Many retail businesses rely on video surveillance for security monitoring; however, video analytics solutions are enabling retailers to harness video for more, such as optimizing operations and performance,” Weagle said.
In order to increase video-content-analytics coverage to optimize operations, some retailers are expanding their video surveillance systems. “By measuring traffic hotspots, store navigation patterns, dwell time and product display activity, the retailer can harness video intelligence to uncover trends; A/B test advertisements, layouts and displays and increase security and efficiency throughout its stores,” Weagle explained.
Furthermore, the demographic and activity data drawn from video analytics helps retailers make intelligent merchandising, staffing and inventory decisions to optimize sales at each store. Video analytics solutions are also enabling retailers to integrate data from sources such as point-of-sale (POS) devices in order to achieve more comprehensive analytics. “Retailers might, for example, draw conclusions about staff effectiveness by evaluating information about store entries and time spent in store, staff positioning throughout the store and final sales data,” Weagle said. “The ability to analyze and visualize traffic and shopping data into dashboards and heat maps makes it easy for retailers to identify inefficiencies, test solutions to problems and achieve data-driven optimization in store.”
This data can provide important insights into questions such as: Are shoppers dwelling next to a certain display, removing items but not purchasing? Are certain areas of the store underutilized or infrequently visited?
The ability to recognize and identify objects in video was also instrumental for employee oversight, Weagle added. “Rules can be configured to trigger calls to action for certain employee activities. For instance, by adding images of employees and using face recognition capabilities, the retailer can set alerts for when employees enter the stock room or to mobilize employees to the checkout when crowds start forming by the cashier.”
