American consumers have access to enterprise brands through more touchpoints than ever before. In the past, enterprises controlled the times, policies and marketing funnel for customer interactions.
When things went wrong, customers reluctantly picked up the phone to call customer support, fully expecting not to be recognized, to be put on hold, to have to repeat the same information several times, and to have to spend a lot of time and effort to receive “customer service.”
With the ubiquity of the Web, and with smartphone use, social networking, and consumer expectations for products and services at an all-time high, customer service experiences are changing for the better.
Technology has enabled consumers to redefine how and when they will interact with enterprises at any point in their brand journey. From researching and purchasing to evaluating and returning, consumers set the pace, time, location, and the device used to perform those activities.
At the Core of Greatness
The key trend for companies today is being able to use data to anticipate customer needs across an entire journey. Once it’s collected, the challenge becomes how to leverage the data into a design that promotes an effortless and comprehensive user experience, no matter the device or channel.
UX design luminaries such as Gitta Solomon, Mike Mills and Bruce Tognazzini shared a common belief that putting people at the center of the design of software-engineered experiences — a method called “user-centered design” — was the only way to create great customer experiences.
What makes a great customer experience? The successful formula combines desirability (users wanted it), feasibility (it can technically be built), and viability (people want to buy it) and the ability to scale.
In fact, Tognazzini wrote the first principles for HCI (human computer interaction) design and usability testing, one of which plays a major role in how companies should be using this customer data to their advantage.
Design Principle: Bring to the user all the information and tools needed for each step of the process.
Much has been said about big data from the perspectives of science, technology and privacy. There has been less attention to how an enterprise leverages and effectively productizes its knowledge of customer data to anticipate the needs of customers.
Each industry has a high volume of repetitive journeys that users take as they interact with a brand. For example, in retail banking, the most common customer journeys are checking account balances (94 percent), transferring money (61 percent), receiving an alert (57 percent), and depositing a check (51 percent).
The Pareto principle (also known as the “80-20 rule”) states that for many events, roughly 80 percent of the effects come from 20 percent of the causes. Big data is an ideal tool for identifying the top 20 percent of customer journeys.
Typically, qualitative insights such as speaking with customers or scanning chat transcripts and traffic logs for common bottlenecks have been used to help map out customer journeys. However, combining these with modern big data platforms can provide the material for redefining these journeys in an even more customer-centric fashion.
Anticipate Customer Journeys
Following is a good example of the application of this principle.
A frequent, repeat guest using a lodging rental service wanted to stay at a particular location for three nights, but only two nights were available. He inquired if the reservation of the person staying on the third night could be canceled and replaced with his own reservation. The host, unsure what to do, looked up “cancellation policy” with the service.
Instantly, a well-written answer appeared, informing the host of the consequences and penalties of making that type of cancellation. The host was able to share the information with the repeat guest, and the matter was resolved. The service had anticipated the host’s needs without any knowledge of the particular problem and provided the right tools at the right time to resolve the issue.
Further, because those tools were available through a self-service channel, there was no need to route the customer to a customer service representative.
When applied to the most frequent customer journeys, quantitative and qualitative research methods, combined with user-centered design thinking, will deliver all the information and tools needed for each step of the process. For enterprises, this translates into improved customer service metrics, including reduced average handling time, increased first-caller response and higher customer satisfaction.
When an enterprise thoughtfully productizes its data around anticipating customer needs at every touch point in a brand experience, then customer loyalty increases and the enterprise earns the chance at gaining customer trust in its brand.
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