The role of AI in customer experience in the retail industry

This article has been developed by the CMA’s CX Council as part of a subgroup initiative exploring AI in CX.

The piece features a Q&A based on an interview conducted by two CX Council members. Wayne Carrigan interviews Scott D’Cunha on the role of AI in the delivery of customer experience, specifically in the retail industry, touching on the impact at the strategic level and highlighting considerations for organizations when building AI into the customer experience. Read on to learn more.

A Q&A with a CX thought leader

Q: Artificial Intelligence (AI) is permeating every aspect of our lives. How do you think AI is impacting customer experience in the retail industry?

A: It’s a great question, as the rapid adoption and evolution of AI across all sectors is creating many opportunities and challenges for organizations to contemplate. Within the retail industry specifically, AI is providing the tools to tackle many of the operational challenges that retailers have encountered, such as consistency in service, as well as providing new capabilities to advance efficiencies and promote more personalization.

Within the context of customer experience, AI solutions are emerging at both the tactical and strategic levels for retailers. For example, at a tactical level, the ability to provide information, insight and recommendations is being heightened through AI in a number of ways, including:

• Richer and more relevant search capabilities for customers looking through online catalogues and collections, leveraging not just amalgamated search histories but also using time of day, weather patterns, and general trends to deliver better results for consideration (as espoused by eBay).
• Provision of better automated web-chat services during busy times of the year, or when call centres are closed, that can augment customer service agent capabilities and availability, and continue to build a body of knowledge that meets customer needs for help or information (H&M and Amazon being world-class examples).
• Use of stronger in-store customer service tools (both with sales associates and in-store digital aids) – for everything from product knowledge, trends and omni-channel options (as shown with great dexterity by Sephora and its ‘in-store companion’ on its app).

Q: What is the impact at a strategic level?

A: The ‘north star’ for many retailers today is the goal of personalization – i.e. being able to serve customers in ways they want to be served, with products and services that they prefer to buy, at times and locations which are suited to them. The data-rich environment we see today, and the collection of customer data in multiple ways including the increasing growth of loyalty programs, has meant that the data exists to better understand a large number of customers, and at least estimate with strong likelihood the desires of customers whose profile is not fully complete. But the challenge of drawing insights together in real time to create timely personalized offers has always been a constraint. Coupled with the cost of developing creative to offer personalized offers or recommendations, the goal of a fully tailored experience for all customers was always just beyond reach.

The growth of AI has removed many of the barriers to personalization. The emergence of GenAI, as seen for example in Adobe’s GenStudio, has taken campaign development and creative design from a timeline of several weeks to hours (or even minutes), and the creative templates that can go further than simply adding the right name and loyalty number to an email or online offer.

Additionally, the aggregation of data from multiple sources in ever-evolving customer data platforms, processed and evaluated with AI, allows the faster creation of offers that are perpetually improved, and can better resonate with customers and provide real-time relevancy. While this is still a work in progress - organizations still need to develop fully effective ways to align individual customer buying habits, market trends and touchpoint strategy to optimize the experience) – AI has significantly cut the time and cost to reach the nirvana that personalization offers, with greater engagement, loyalty and revenues.

Q: What do organizations need to be more aware of when leveraging AI for customer experience?

A: There are several factors that need to be considered when building AI into customer experience. For many of the tactical opportunities, retailers can forge ahead with the use of non-identifiable data to formulate several better and richer experiences that can be drawn and identified from the ‘wisdom of the crowd.’

But for the journey to personalization, there is a need to be cognizant of legal and regulatory requirements, and ensure that the use of customer data is permitted, approved by customers and following standards that are increasingly stringent as data collection methods become more ubiquitous. Additionally, retailers need to introduce some level of judgment between what level of personalization is attentive and welcomed, versus intrusive and creepy. This judgement should be continually reviewed through the lens of ongoing customer feedback to ensure that trending preferences are considered in the design decisions.  

With the plethora of tools available to retailers across multiple platforms, the key to innovating in the space with AI is to create specific use cases that be trialled and refined and provide real value to customers.  As retailers seek to create brand differentiation in markets that are increasingly competitive, there is no surprise that the age-old retail method of test and pilot still applies in using AI to add value in developing understanding, and consequently far-reaching winning strategies.

Contributors:
Wayne Carrigan
Scott D’Cunha