Digital native companies like Google, Facebook, Snapchat, Netflix, Amazon, and Spotify deliver the large majority of online interactions today, and have created a new standard for customer experience. And it’s not just happening online–products and services like Echo, Dash, Google Now, and Uber extend the expectation of relevant, ubiquitous, and real-time brand interactions to the physical world.
Artificial intelligence is helping smart brands learn about individual customers and maintain personal conversations with users from the get-go, rather than waiting for complaints or problems to arise–traditionally, where customer care began. Using data to scale personalized customer care creates strong bonds with users by anticipating their needs: Google Now or Google Assistant could proactively let me know there’s traffic so I should leave for the airport 30 minutes early–and offer to order me an Uber. My cable company could let me know via text that there’s a soccer game from my favorite team coming up that I won’t want to miss–and remind me to watch it for free on their app, or in a nearby bar. If my phone bill spikes, a heads up and explanation from my carrier may fend off the inevitable, likely unpleasant customer-service call.
Expectations for this level of personal, anticipatory service are flowing to customer care. But most current implementations (like going to a “my account” page on a website) still feel impersonal–dry, digital presentations of account info, preferences, or options to upgrade or cancel services. As customers, we want brands to know us, love us, tell us what matters, and anticipate our next moves before we do. Only then do we love brands back. We also expect brands to be transparent and put our interests on par with theirs. We want brands to tell us what’s relevant to us, even if it doesn’t necessarily mean new sales for them.
The best customer support experience is personalized, empathetic, and effective. This traditionally has been associated with well-trained personnel who talked to customers, understood their needs and problems, and provided quick solutions. When done well, it’s great for customers, but expensive for business.
The good news is that with the ubiquity of connectivity and advances in experience design and artificial intelligence, it is now possible to make personal services scalable–even to a level that feels more personalized than human interactions, since machines can access data and run algorithms much faster than us. Using the knowledge gleaned from AI, smart brands will leverage anticipatory design and create seamless customer service experiences, sometimes even fixing issues before they occur. Only the brands that do so will be able to capture the cost advantage of a fully automated service, and the customer trust and love that comes with a valuable, personalized connection. Successful companies will put the customer (each individual, not the average) truly at the center.
The NPS of One.
In the past decade or so, companies have distilled their user centricity into a single metric: net promoter score, or NPS–the standard measure of a customer’s loyalty. That made sense ten years ago, but it’s outdated in a world where digital is the medium. Imagine a service company with tens of millions of users that takes measure of its customer experience solely by averaging the results of a survey that’s the same for every user, and only asks one question. Averages are good to manage a business, but not to optimize the capabilities that will drive personal conversations with your customer.
A high aggregate NPS score was once the ultimate goal, but today, customer intimacy—the ability to understand, empathize, and ultimately anticipate the needs of any one specific user-—is the new make-or-break measure. Scaling customer empathy and automating solutions for personal conversations will become the new norm. The NPS of One is the ability to assess how each customer feels about your brand. If Sarah is a customer that you have selected randomly, how would you answer these questions:
- How’s Sarah doing?
- What additional value can we bring her?
Companies can find implicit predictors of a user’s feeling about their brand through data analytics. For example, a telecom company could look at time spent with the call center or on an account page, calls dropped, peaks in charges, and plans purchased through direct sales but not used as indicators of a low promoter score; responses to SMS messages, reduced support calls, addition of lines and length of relation could be predictors of a high score.
Building Trust Through Anticipatory Design.
Understanding individual users through data is the jumping-off point to successful anticipatory design. While most companies recognize this need, few have adopted anticipatory tactics into their experiences. In some cases, they have been selfishly anticipatory, optimizing for up-sales but neglecting other drivers of customer value.
Unselfish anticipatory design asks what is the most valuable thing that we can do for that user now? The answer to this question should drive the next customer interaction. But early implementations of anticipatory design in most traditional companies focus on finding what is the thing that a customer is most likely to buy now? That could be appropriate and valuable to a user, but the approach would quickly smother customer trust if it were always one-sided.
Imagine that Sarah purchased an international calling plan for $25 a month, but has not made international calls for 4 months. Would it be valuable and anticipatory to propose to cancel it? The answer is yes–but is your technology, and more importantly, your culture and incentive structure, ready to actually support that option? High-value anticipatory design will surprise the user if it is unselfish, creating significant brand equity.
We are entering a new era in user experience, enabled by the advance and ubiquity in artificial intelligence and the blending of the physical and digital worlds. Over the next 3 to 5 years, brands that fall behind on this front will face an unbridgeable gap. Smart brands will increase exponentially their ability to know their customers, and predict how to create value, or avoid pain, for them. The goal? To create empathy one customer at a time, while providing user-specific interactions that balance business KPIs and customer value.
Article sourced from Hugeinc.