Data, Data, Everywhere … But Who the #%$& Are You ?

An old song by the group The Who screamed the in-your-face question: Who the #%$& are you?

But seeking help or services from an organization to which you’re handing over your hard-earned money isn’t one of them.

Unfortunately, you likely don’t have to reach far back in memory to recall a circumstance in which an encounter with customer service didn’t exactly leave you with the warm fuzzies. You might have felt over-interrogated, under-served, and quite unappreciated- all from a company that has happily accepted your cash for products or services.

Emotional bumps and bruises received during interactions with customer service are all too commonplace. But here’s the real shame of it: In this age of Big Data and advanced technology, the infliction of such brand-damaging trauma is completely avoidable.

While the knee-jerk reaction might be to label those times as the good old days, they really weren’t. Humans, quite bluntly, aren’t especially well-suited for customer service roles. They have bad days and good days. They get tired and, sometimes, a little cranky. And they have limited capacity for data recall.

Machines, on the other hand, suffer from none of those human foibles. And, over the past couple of decades, machines have been increasingly deployed to bear much of the customer service burden. But, in all-too-many cases, machine-based customer service hasn’t exactly out -performed their human counterparts.

That’s because the state of Artifcial Intelligence (AI) technology just hadn’t caught up to the potential.

Until now.

In just the past few years advancements in AI technology, data storage, and data-handling have morphed the potential of machine-human interactions from a far-in-the-future promise to a here-and-now reality. AI technology has advanced to the degree that organizations are rapidly transforming to capitalize upon AI-powered digital technologies such as voice- driven bots and mobile apps.

Each of these technologies are capable of interacting intelligently with humans. And most organizations recognize the potential inherent with these technologies.

A recent survey, in fact, revealed that nearly 95% of businesses expect to deploy AI-powered voice technologies within two years. Nearly 90% of companies believe that this technology will provide their company with a clear competitive advantage. Leadership in the majority of surveyed companies believe that AI voice technology will increase operational effciencies and reduce the cost of every customer transaction.¹

But all AI-powered technologies, voice included, rely upon a key resource: data. LOTS of data. And lots of data is available — about you, and about virtually everyone else on the planet. More than 2.5 quintillion bytes of data are currently generated during the course of each passing day. By 2020, 1.7MB of new data is expected to be generated every single second for every single person on earth.² 

Most organizations currently collect mountains of data about each of their customers. The data collected includes information such as demographic pro�les, buying patterns, preferences, and behavioral patterns. And all of this data is used to fuel AI-powered interactive technologies.

It’s all made possible with data — data about you, the customer. And the technology is available right now for any companies that wish to help lead the way into the age of AI.

Digital touchpoints such as mobile apps and interactive voice response (IVR), for example, are perfectly suited to take advantage of the ever-expanding personalized customer knowledge base. These technologies can leverage the customer knowledge base in anticipating a user’s needs based upon data that has previously been collected.

According to a ZDNet article, “Use of AI by customer service teams is projected to increase by 143 percent over the next 18 months.”³

Sometimes labeled the Fourth Industrial Revolution⁴, the age of AI-powered technology is rapidly escalating customer expectations. Consumers are aware that the companies that serve them now know — or should know — more about each customer than ever before. And consumers expect that all of that data will be put to good use.

Recent research found that three out of four consumers expect companies to understand their expectations and anticipate their needs. And for the companies that cannot live up to those high expectations? The same research found that “…76% of customers now report that it’s easier than ever to take their business elsewhere — switching from brand to brand to find an experience that matches their expectations.”⁵

The simple fact is that customers are exposed to AI-powered technologies more and more frequently, and are beginning to expect “intelligent interactions” across every touchpoint. And that includes human-to-human touchpoints.

But human agents are often less efficient than their AI-powered counterparts such as chatbots. And while customers may still crave human-to-human interaction, they recognize the increased efficiency that AI has enabled.

More than half of all consumers, in fact, prefer to be served by a chatbot rather than a human. Why? Because the efficiency of the AI-powered chatbot saves time.⁶ This fact illustrates the inefficiency with which the capabilities of AI and Big Data have been wielded by human customer service agents.

Unfortunately, in all too many instances, when AI is introduced into the human-to-human touchpoint, knowledge gaps quickly arise that lead to frustration.

Clumsy, inefficient, customer-infuriating exchanges such as the above are hardly what were envisioned when companies began to use AI in an attempt to make IVR ‘smarter.’

Humans will be in the customer service mix for some time to come. So it’s essential that the potential of AI be leveraged effectively by human agents, and not just by machines such as chatbots.

And that’s the challenge that so many companies currently face. How do we get this mountain of data — all the current data that we have for a given customer — into the mind of the customer service rep that’s serving that customer? And how do we accomplish that task in a manner that facilitates and maintains the smooth, intelligent interaction that everyone craves, both company and customer alike?

A machine such as a chatbot can access and process that mountain of data with near instantaneous efficiency. But human agents simply don’t possess that capability. Forcing the human rep to frantically scan (there’s no time to actually read!) multiple screens of historical interactions and transactions while the customer, stewing in frustration, waits for the rep to get up-to-speed is no solution.

The Answer: A New Interface for Managing That Data Mountain

The wealth of data now available about each customer must be managed differently for a human agent vs. a machine agent. The interface between that data and the human agent must be capable of retrieving and integrating that data into a highly customized, human-friendly data presentation. Such an interface can empower a human agent with an in-depth understanding of the customer within just seconds — and with near machine-like efficiency

Synthesizing the mountain of data into such a simple interface is no easy task. It requires all the work the marketing and customer experience folks have been working – the “customer journey” and knowledge of all the data an organization collects and stores about its customers. Boiling that down to a simple, single screen is difficult, but it can be done.

Hey, I know you!

A data interface that enables more intelligent interactions between human agents and customers can help customer service reps serve with far greater efficiency. Service reps can be provided with the information necessary, through AI, that arms them with the data essential for successfully deducing and intuiting the customer’s wants, needs, and preferences.

The only missing piece might be in recognizing the customers by their appearance when they walk in the door. But location-aware mobile apps and facial recognition technologies can now provide the ability to fill even that knowledge gap.

From the customers’ viewpoint, the difference can be like night and day. Instead of feeling unwelcome, underappreciated, and even somewhat interrogated (who the #%$& are you?), customers might instead feel more like an old ‘80s sitcom character, Norm from Cheers.

With the right building blocks in place, customer interactions can be part of an ongoing, seamless conversation that transcends individual touchpoints, helping the customers feel as though they are truly “known.” And that’s the holy grail of customer engagement.

Because just like the characters from that old show, each of whom found a warm and friendly home away from home, customers truly want to do business with companies “…where everybody knows your name, and they’re always glad you came.” Those are the companies that build brand loyalty, and that customers keep going back to again and again.

And in the age of AI, those companies are going to be the winners that stand apart from the competition by enabling intelligent interactions with their customers - regardless of which channel they use.

References

1 https://www.pindrop.com/blog/welcoming-conversational-economy-securing-voice-channel/

2 https://www.pindrop.com/blog/welcoming-conversational-economy-securing-voice-channel/https://www.domo.com/solution/data-n ever-sleeps-6

3 https://www.zdnet.com/article/ai-is-revolutionizing-customer-service/

4 https://www.salesforce.com/blog/2018/12/what-is-the-fourth-industrial-revolution-4IR.html

5 https://www.salesforce.com/research/customer-expectations/#