The first article in this two-part series on the shifting nature of the ‘retail experience’ discussed how fragmented customer service leads to lost customers—and how a few small tweaks can add value to the customer journey for a lifetime. In this second article, we pull back the lens to look at the roles of data and evolving corporate leadership in this critical aspect of retail.
Here’s a scenario you may find familiar: You try to return a pair of pants you bought online via a store’s mobile app, which gives you a number to call; the representative on the other end of the line can’t find your order number and you don’t know it either; it’s a time-consuming and frustrating experience. On the flip side, we’ve already looked at some examples in which brands use the data they’ve gathered about their customers to make the experience—everything from shopping to purchasing to owning–more seamless, frictionless, and fun. Here we’ll focus on how to get there: how to approach your data, how it can be put to use, and the necessary accompanying shift in mindset, leadership, and culture.
We all know that there is a wealth of possibility in data. But keeping the totality of customer data in one place—in one massive, unwieldy platform—is a pipe dream. The current popular system of housing certain bits of data in different departments, depending on perceived relevance, leads to missing pieces for some and repetition for others… a similar failure. Instead, data needs to live in multiple locations that can run on their own but can communicate with one another in real-time. The front-end website can be fed enough information on the back end to monitor the customer’s journey without having to hold every piece of that customer’s data itself.
A modern approach to housing, managing, and feeding data is important because you can only use what you can access. A couple of examples come to mind. One company we work with built a tool that can predict when a customer is about to abandon a cart, based on past purchase data as well as on the behaviors and habits of demographically similar individuals. In the first article, we also discussed the example of Amazon’s one-click button—the e-commerce giant’s answer to cart abandonment as a major source of retail loss and a prime area for improvement. My client’s solution to that problem was to come up with a fully automated tool that can identify the critical moment of cart abandonment and create a personalized discount coupon for the customer, keeping the customer on track.
Another company I work with tracks sentiment through data, to find the precise point when a consumer’s sentiment shifts. The idea is to solve for weak link theory, which, as we discussed earlier, explains that just one unpleasant interaction, even among overall positive experiences, is enough to lose a customer. The solution this company offers uses data from a range of customer interactions to determine if and when sentiment turns negative, and if so, to proactively reach out and re-engage the customer. The common thread connecting these tools is that they analyze the whole journey. How did the consumer get to making that purchase, in that particular position? What did they look at and abandon along the way? These data points represent key intelligence and areas for machine learning and pattern recognition to work behind the scenes.
The holistic integration of data, however, is only made possible by a corresponding unification of the ingredients that together comprise whatever it means when we use the term ‘experience.’ These include digital experience, analog or in-store experience, customer-company touchpoints, as well as where else the customer was looking before they even reached the company, the marketing they saw on Instagram, and the advertisement in the podcast they listened to; all of these ingredients are intertwined. There is a massive disconnect when corporate structure fails to realize that essentially unified nature. The result is that it remains segmented within itself. What were once silos of different information, controlled by different people—purchasing, merchandising, Chief of Digital Operations, Chief Information Officer (CIO)—need to come together. Just as the data must talk to each other, so too must the leadership.
The CIO especially is now being charged with moving from function-centric applications to user-centric ones. That bears repeating – it’s the CIO’s job not to think in terms of the functionality of a given application, but to how the user engages with it. And by “user,” we could be referring either to the external user (i.e. the consumer), or the internal user (for example, the operations team). This thought is the backbone of an article in the Harvard Business Review, “Why Every Company Needs a CXO,” which describes the integral part that employee experience (EX) plays in customer experience (CX), and advocates for the creation of a new position, the Chief Experience Officer (CXO), to oversee a more holistic approach. Denise Lee Yohn, the article’s author, explains how so many companies focus only on the customer experience, ironically to the detriment of customer experience: “If an organization separates leadership CX from EX, disconnects between CX and EX are likely to arise, even if those roles are part of the executive team. The fact is, employees can and will only deliver experiences to customers that they experience themselves.” Similar thinking and foundations underpin this approach to both customer and employee experience and their data-driven upgrades. Companies must rethink their internal operations, otherwise, their insides won’t match their shiny new outsides, and that gap will become clear.
Bringing retail into the digital age requires more than just a website. Rather, precision data tools championed by the right leadership is critical in fueling brand success. Of course, digitization became a more pressing issue as more and more people started to shop from home during the pandemic, and we can anticipate that for some, those habits will remain even as pandemic-era stay-at-home orders are lifted. One important lesson from the past year or so is that none of this will work without flexibility. Machine learning tools can analyze vast amounts of data, recognize patterns, and then implement tools to boost profits based on that knowledge—but any of those patterns can change at the drop of a hat. It’s imperative that our algorithms are constantly ready to experiment and learn alongside the corporate leadership that harnesses them. It’s only with their dual dynamism that retail can reach its potential for a seamlessly integrated, personal, and delightful experience.
- Disparate data sources must be able to communicate with one another in real time, but this data can only become holistic when viewed through the lens of user experience.
- The different strands of corporate leadership—the CIO, purchasing, merchandising, and digital operations—need to unify in order to move from a function-centric to a user-centric approach.
- New positions like CXO—Chief Experience Officer—help to bridge the gap between corporate culture and state-of-the-art tech enablement, and consider the equal importance of the employee experience (UX) and the customer experience (CX).