A shopping machine – AI and the future of retail

All of us have all suffered bad shopping experiences where we ended up trawling through endless items to find the one you want, navigating a badly-structured website or dealing with ill-equipped customer service teams. Despite spending vast sums on digital tools and solutions, it can still be a struggle for retailers to provide a clean, seamless buying experience for customers.

Thanks to mobile technology and the Internet of Things (IoT), customers are more connected than ever before – meaning retailers have a range of channels to interact through (online, mobile, wearables, SMS, social media and so on). Yet retailers are often communicating inconsistently across these channels, creating a fractured and frustrating experience for consumers. While there is no one magic bullet to solve this problem, the recent advances in AI technology offer retailers a powerful tool to provide customers with a superior shopping experience.

Birth of the retail chatbot

One key application of the latest AI technology is the virtual assistant, or ‘chatbot’. With AI assistants or chatbots, retailers have the option to create a much better experience through voice interaction, giving users a ‘conversational commerce’ experience. The spoken interaction of a chatbot has a number of benefits. Firstly, so many of us love to chat as it’s far more natural than typing a query into Google; so chatbot interactions are easier and more comfortable for customers. Imagine being able to just ask your phone to order some washing powder and, thanks to AI, it knows exactly which brand you prefer and is able to comparison shop for the cheapest option in seconds without you needing to be involved.

Chatbots are both intelligent and context aware, meaning that in conversation, they are better able to engage customers, both in-store and online. This enables retailers to cross sell additional products based on real time customer feedback; as well as factors such as a customers purchasing and browsing history, location and immediate needs. All of this combines to produce a more engaging experience – and engaged consumers return more frequently to buy more products because retailers are finally able to talk ‘with’ customers not ‘at’ them.

OmniChannel with AI

OmniChannel with AI

Omni-channel AI

The utility of chatbots means they are a wonderful customer engagement tool in multiple scenarios that cannot be ignored by retailers. Yet in the same way that online commerce didn’t kill the brick and mortar store experience, chatbots will not kill the online shopping experience. The question then becomes, not whether chatbots should be used, but how they are best integrated into the omni-channel experience. There are certain tasks where chatbots are perfect for interactions must be quick and efficient; tasks like getting receipts, shipping notifications and live automated messages are ideal from a customer service perspective.

But bots are less suited for deep-dive research on a given product. Any task which involves typing out numerous responses to questions rather than simply pressing buttons renders the chatbot annoying rather than helpful. For example, research has found that 93% of millennials read product and customer reviews before purchasing a product. These types of interactions are ill-suited to chatbots. However, retailers can still rely on AI in a different form to come to the rescue – the cognitive website.

The Self-Aware Website

 Along with mobile, chatbots and social media, the website still has a key role for retailers. However, the old model of a static site is rapidly becoming outdated. In the digital age, websites need to be able to deliver a personalised, contextual and relevant experience to each individual consumer. By deploying cognitive websites which ‘learn’ about the customer, brands will be able to provide the detailed background needed ahead of a big purchase which is optimised to result in a purchasing decision. The caveat is that like all forms of marketing, it’s easy for retail AI to go too far. Just because someone has been looking at a friend’s baby pictures on Facebook, doesn’t mean they want to purchase nappies – an AI tool making the wrong inference can easily come off as creepy.

Ultimately, the utility of the various AI tools is too great for retailers to ignore, and chatbots or cognitive websites will be the future of consumer interactions. The trick is to understand which type of AI to apply, when and where. At the heart of this adaption is understanding the various AI tools that are available and which will work best for what type of customer interaction. Once this is understood, retailers can help to blend these various AI tools into a unique and seamless experience for the consumer.


The article was originally published on Information Age and is re-posted here by permission.

Frank Palermo

Executive Vice President - Global Digital Solutions, Virtusa. Frank Palermo brings more than 24 years of experience in technology leadership across a wide variety of technical products and platforms. Frank has a wealth of experience in leading global teams in large scale, transformational application and product development programs. In his current role at Virtusa, Frank heads the Global Technical Solutions Group which contains many of Virtusa’s specialized technical competency areas such as Business Process Management (BPM), Enterprise Content Management (ECM) and Data Warehousing and Business Intelligence (DWBI). The group is responsible for creating an overall go-to-market strategy, developing technical competencies and standards, and delivering IP based Solutions for each of these practice areas. Frank also leads an emerging technology group that is responsible for incubating new solutions in areas such as mobile computing, social solutions and cloud computing. Frank is also responsible for overseeing all of the Partner Channels as well as Analyst Relations for the firm. Prior to joining Virtusa, Frank was Chief Technology Officer (CTO) for Decorwalla, an emerging B2B marketplace in the interior design industry, where he was responsible for the overall technology strategy, creative direction, and site development and deployment. Prior to that, Frank was CTO and VP of Engineering for INSCI Corporation, a supplier of digital document repositories and integrated output management products and services. Prior to INSCI, Frank worked at IBM in the Advanced Workstations Division, and took part in the PowerPC consortium with IBM, Motorola and Apple. He was also involved in the design of the PowerPC family of microprocessors as well as architecting and developing a massive distributed client/server design automation and simulation system involving thousands of high-end clustered servers. Frank received several patents for his work in the area of microprocessor design and distributed client/server computing. Frank holds a BSEE degree from Northeastern University and completed advanced studies at the University of Texas.

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