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The Future of CX: Turn Actionable Data into Knowledge
Juanita Coley, CEO and founder of Solid Rock Consulting and No Jitter contributor, took center stage at Zoomtopia this week during her session, “The Future of Customer Experience.” Accompanying Coley during her panel discussion were Ted Yoshikawa, head of product for contact center, Zoom; Scott Brown, head of contact center sales and GTM, Zoom; and Mahesh Ram, head of digital customer experience, Zoom. The conversation focused on the future of customer experience (CX), available technologies that enable businesses to innovate, plus why contact centers must utilize actionable data to improve CX.
Before diving in, Coley encouraged attendees to close their eyes and envision the future of CX because her unique experience at a fast food restaurant prompted her to think about it one day. While pulling into the drive-thru after an outing with her children, Coley recited their order to an automated system. Once the system thanked Coley and told her to pull up to the next window, a person was there to hand over the food. “Everything was correct,” Coley said. “That experience got me thinking about the future of the customer experience.” That’s because Coley realized her engagement with the technology was at least 80% automated and “got giddy” at the thought of this being next-level CX.
The Future of CX in Your Contact Center: Meet Customer Expectations
Coley asked panelists to articulate how businesses are engaging with customers when so much about the entire customer cycle – from how the customer engages to what their expectations are – has changed. Brown gave an example of many consumers, himself included, taking advantage of capabilities like Doordash or Instacart during the pandemic. But often, Brown explained, having Little Debbie snack cakes delivered to your house in 20 minutes (i.e., speedy service) doesn’t translate into what if the customer has an issue, challenge, problem, or needs help driving remediation to closure (i.e., customer resolution).
First, he said, consumers want to engage on their timeline in the modality they choose—i.e., online chat, call, email, or SMS—so contact centers must know who their customers are. “My expectation [as a consumer] is the brand relationship I have is straightforward, Brown said, adding, “If I’m already authenticated in a mobile app or logged into a website, you should know who I am.”
Next, Brown says contact centers must also know their customer’s history. Are they first-time customers? Do they have a history with your brand? “If so, please understand what that relationship is and value [that relationship].”
Lastly, be prescriptive and pre-emptive about why a customer may be reaching out. Do they have a current case or ticket open? Do they have one product and seeking information on another? “I find myself often disappointed in those [customer] experiences,” Brown explained, where the agent doesn’t have all his information. He also referred to contact centers and the employees who operate them, adding, “I think we all have to make those [customer] experiences better, more prescriptive, more predictable, more expedient.”
AI, Automation, & Machine Learning Help Understand the Customer’s Intent
Coley pointed out that customers, technologies, and employees are getting more sophisticated—prompting consumers to “respond quickly and have a shorter attention span.” That sophistication and shorter attention span drive change in customer experience and contact centers.
Brown elaborated that consumers historically thought of contact centers as isolated brick-and-mortar building employed by folks who come into work daily, hate their jobs, and have to navigate through 25 different applications to obtain the right internal or external information. “I think this whole persona of what the contact center can bring to market is no longer captive within an isolated world—the level of experience is elevated by things like automation.” That means not speaking to a human agent to reset your password. Or by the time you reach a human agent, your historical context should arrive with you, Brown added. “Those modalities and capabilities are critical and necessary, but also increase the value in that contact center representative.”
Ram says consumers are making decisions based on how effortless brands make the experience to interact with them. He added, “If contact center managers think about what an effortless experience is—it’s not always about automation—it’s about understanding.” You must understand your customer, the context of their request and getting them to the right path to resolution. In some cases, that involves self-service. In others it involves getting the consumer to the proper human agent, at the right time, with the right context, “that’s what the consumer wants,” Ram said.
On the other hand, Ram added, businesses want and need their agents to do the highest quality work—more things that require human interaction, like upselling, cross-selling, or recommending products to consumers. Ram says technology plays a role in making agents more efficient, but also saving businesses time and money because they value delivering an effortless experience to the customer as efficiently as possible.
When thinking about the application of artificial intelligence (AI), machine learning, and customer experience, “We have to be very thoughtful,” Ram said. “You can’t throw these [technologies] out there and hope for the best.” Ram then advised attendees to focus on some fundamental principles.
One fundamental principle Ram described is doing a better job at understanding why the consumer (end user, brand, employee) arrived at their resolution destination and using AI, machine learning, and natural language understanding tools to do so.
“Understanding the intent involves using AI and machine learning, and natural-language understanding to better understand why the customer is here, ‘what’s your issue,’ then be able to take them on the correct journey that involves a human experience,” he said.
When a consumer reaches the appropriate human agent—one fully equipped with all the context and intent; and knows why they’re here—it makes the interaction faster. “You’ve also got a consumer who’s delighted because [they feel the contact center agent] has valued their time,” Ram said. “If AI and machine learning can give us back time, make those experiences more efficient and faster on the self-service and agent side, we’re very grateful.”
Turn Actionable Data into Knowledge and Power
Coley explained that technologies enabled employees to become more dynamic, as she reminded attendees about her fast-food example at the beginning of her presentation. When talking about technologies like AI and machine learning, Coley refers to them as “just-in-time learning” and “the conduit to the future of customer experience” because you’re giving agents the knowledge at their fingertips to resolve an issue in a matter of moments.
Ram noted how Zoom is constantly thinking about how to make data and analytics actionable and turning that actionable data into “power and knowledge for a business.”
Citing a customer example, Ram described a company facing many issues with PayPal being a valid form of payment in a particular foreign country. It didn’t have the knowledge base (centralized repository of information) or FAQ content confirming PayPal was available in that country. Zoom informed the customer of this within an hour of launching the new product, which prompted this company to write a piece of knowledge about it—and immediately started surfacing those answers. “It’s not always about the transaction, but looking at a billion of those transactions and helping businesses with what they don’t know.”
While wrapping up the discussion, Coley recapped working in workforce management and how senior leadership report requests made her “eye twitch all the time” because the leadership would never do anything with the data. Brown explained that those metrics are “core to the business because they add to the lifeblood of business revenue and make customers happy.”