This article was originally published in the Winter 2018 issue of The Record. Subscribe for FREE here to get the next issue delivered directly to your inbox.
Sarah wants to bake a birthday cake, so she decides to order the ingredients when she does her weekly food shop via Netherlands-based grocery retailer Albert Heijn’s website. After selecting all her regular groceries, Sarah heads to the online checkout to submit her order for delivery when she suddenly receives a notification reminding her that she has not added flour – one of the key ingredients for her cake – to her basket. At the same time, she receives a special offer for the brand of flour she usually buys, so she quickly selects it and confirms her order.
Thousands of customers like Sarah now receive grocery recommendations from Albert Heijn, thanks to a new hyper-personalisation tool called Predict My List. Built on the Microsoft Azure cloud, Predict My List uses artificial intelligence (AI) algorithms to identify patterns in customer’s buying habits and combines it with data about their location, the season and other factors to deliver relevant product recommendations and available promotions. This service is part of Albert Heijn’s new strategy to better understand the needs of its customers and deliver the types of products and shopping experiences they want.
Many other retailers worldwide are also exploring how they can use data to transform their end-to-end retail experiences. However, many have no idea know where, or how, to capture this data.
“Now that the physical and digital worlds are merging, retailers have more customer touchpoints than ever before – such as in-store sales associates, call centre operatives, in-store sensors and cameras, POS devices, mobile apps, online assets, social media and more,” says ShiSh Shridhar, director of Business Development, Data, Analytics and Internet of Things (IoT) for the Retail Sector at Microsoft. “Although all these touchpoints have the potential to provide critical data about their customers, many retailers either do not know about these sources, or they don’t have the tools to capture information from them. An easy fix for this is to digitise all of the customer touchpoints along the different paths of purchase.”
Even those retailers who do capture customer information at every touchpoint face challenges. Most collect and store this raw data in separate silos and they don’t have the tools or skilled human resources to convert it into actionable insights.
“When customer data is stored in separate silos, it’s essentially ‘dark data’ – information that cannot be used to understand customers’ preferences or shopping behaviour, or make decisions about new business strategies and practices,” says Shridhar. “Hence, retailers must consolidate these disparate data silos into one unified platform and then use analytics or technologies like AI and machine learning to mine it for insights that will enable them to create a unified 360-degree view of each customer and their preferences. Retailers can use these insights to refine the customer experience and thereby boost retention and loyalty, while driving sales. This could be achieved by delivering personalised marketing content, interacting with individuals via their preferred channels, providing relevant product recommendations and promotional offers, and more.”
Crucially, adds Shridhar, such insights help retailers to understand exactly how customers are interacting with each touchpoint. It enables them to identify where they’re losing customers and pinpoint potential opportunities for improving the experience to make it as seamless and engaging as possible.
“Any small change that makes the customer feel more valued and engaged in their shopping experience will likely lead to a sale and boost their brand loyalty,” explains Shridhar. “If, for example, analytics show that a group of online customers always spend a long time comparing products, but rarely purchase anything, the retailer could use information about their past purchases and preferences to send them personalised discounts while they’re browsing. Or, if a retailer found that multiple shoppers were abandoning its website or physical stores because they were unable to get timely product advice from a sales associate, it could implement a chatbot that can give instant answers.”
Several major retailers have already implemented chatbots to augment their human workforce. US department store Macy’s has rolled out a Microsoft Dynamics 365 AI-powered virtual agent on its website that can provide quick, accurate and personalised responses to basic questions and seamlessly transfer customers to a human operator if necessary. Similarly, UK-based electronics retailer Currys PC World has used AI, the Microsoft Bot Framework and Microsoft Cognitive Services to create a chatbot that helps customers find the products that best meet their needs.
“Not only do these chatbots offer consumers the type of compelling self-service option they’re looking for, but they also reduce the risk of lost sales and provide insights into the type of information customers want before they purchase products, so retailers can refine the services they provide,” comments Shridhar.
While chatbots are becoming a popular way for retailers to capture insights about online and mobile customers, IoT sensors are now a top favourite for retailers wanting to capture data about in-store behaviour.
“IoT sensors can track shoppers’ movements in store, capturing data about the aisles they visit, how long they spend in those areas, which items they pick up and more,” says Shridhar. “When combined with transaction and other data, this can help retailers to build a better picture of each customer. These sensors can also be used to unite the digital and physical customer experience, collapsing the online/offline divide to help retailers converse with customers in the store, or use connected apps and devices to interact with them while they are at home, work, or on the go.”
Microsoft and its strong ecosystem of retail partners – such as Adobe, Affinio, Amperity, Manthan and Redpoint Global – have developed multiple solutions to provide retailers with the tools and capabilities they need to better understand their customers.
“Retailers can use the Microsoft Data Platform to build the capabilities they need to ingest data from various sources and store it in one platform, while the comprehensive Microsoft Artificial Intelligence software platform enables them to gather intelligence and insights from this data to drive action,” says Shridhar. “They can also implement the Microsoft Dynamics 365 for Marketing automation application to develop tailored marketing campaigns and communications that turn prospects into business relationships.”
By using these technologies to unlock insights into their customers’ preferences, retailers are also able to find new ways to optimise operations.
“Shopper data can be combined with contextual information about factors that influence buying decisions – such as the weather, socio-economic trends and geographical location – and used to make accurate inventory and stock management decisions,” says Shridhar. “This empowers retailers to create hyper-local inventories for individual stores, predict optimum product pricing and track product demand and stock levels in real time so they can reduce out-of-stocks. It’s clear to see why these tools and technologies are transforming the concept of shopping; they empower retailers to deliver the types of intuitive, personalised and engaging experiences that will set them apart from the competition in future.”
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