How machine learning and AI are transforming customer support
Tonya Hall sits down with Amit Sood, chief technology officer and head of product at Simplr, to talk about how the company is building custom data sets for customer support.
Life is a series of progressions. Take the transition from student to professional, for example. In school, our objective is to learn the fundamentals of a subject. When we start our careers, we aim to apply what we’ve learned. As we gain seniority, we seek to hone our expertise and carve our niches. In these different stages, our goals are different, and thus the standards to which we hold ourselves are different.
Also: Digital Transformation: A CXO’s Guide
The same can be said of customer service, which is not only progressing — but transforming — into something greater than its former self. The new State of Service report from Salesforce shows that, much like a junior employee progressing in her journey, customer service’s definition of success is changing, and KPIs are following suit. In addition, the use of artificial intelligence (AI) to manage customer service programs is helping companies bolster their relationships with stakeholders – customers, employees, business partners and communities.
Measurement is fabulous. Unless you are busy measuring what is easy to measure, as opposed to what is important.” — Seth Godin
Changing Roles Mean Changing Objectives
Modern customer service agents are a far cry from call center employees of the past. Today, agents are responsible for not only interacting with customers across a multitude of channels and touchpoints, but to serve as their advocates and partners through highly personalized and contextualized engagement.
When customers have more choice and access to information than ever, their interactions with agents can make or break an entire relationship. In fact, 75 percent of the agents surveyed by Salesforce say they are viewed by their companies as brand ambassadors. The traditional view of customer service as a transactional function isn’t relevant anymore. Today, 72 percent of agents view their interactions with customers as relationship-oriented, with those at high-performing organizations (those with excellent customer satisfaction) eighteen percentage points more likely to agree than agents at under-performing competitors.
Customer service professionals view their role as more strategic, focusing more on customer relationship building.
×
screen-shot-2019-02-11-at-6-13-28-pm.png
This begs the question: Can customer service organizations that remain focused on traditional objectives of churning through as many cases in as little time as possible survive in today’s environment? And if not, what KPIs can they turn to instead?
Also: Digital transformation in 2019: Lessons learned the hard way
Customer Experience Imperatives are Ushering a New Generation of Service Metrics
It’s important to note that speed hasn’t diminished in importance when it comes to customer service. In fact, 66 percent of consumers and 80 percent of B2B buyers expect real-time engagement from companies. Average handle time (AHT) and average response time (ART) are thus tracked by 70 percent and 69 percent of service teams, respectively.
Service organizations that track the following service metrics. (Click to enlarge.)
×
kpis.png
The difference is that speed can no longer be the sole indicator of success. Today, when the “service” aspect of the customer service is revered, valued, and held to higher standards than ever, 79 percent of agents say their metrics emphasize value over timeliness. As new technologies allow customers service to analyze the customer experience with more granularity. The definition of success is being broadened to measure much more.
Fifty-one percent of customer service teams, for example, track agent-driven revenue such as that from up-selling.
Here are a few emerging metrics that will play an increasingly critical role in customer service moving forward:
Customer effort score (CES): How easy is it for customers to contact an agent? Can they do so through their preferred channels? Once they connect with someone, do they need to explain the issue in painstaking detail (perhaps to multiple people) or do agents have that information readily available? These are some of the qualities that a CES gauges. By identifying customers’ pain points that arise after they’ve decided to reach out for service, leadership can implement process improvements that make customer and agent lives easier. Fewer than half (44 percent) of teams track CES today, but an additional 28% plan to do so, representing potential growth of 58 percent.First contact resolution (FCR): When a customer connects with an agent (or, increasingly, a chatbot), can they expect their issue to be resolved by the end of that interaction? Or will it be more likely that they’ll need to call back or be transferred among various departments? Low FCR rates can indicate, among other things, a lack of necessary information among agents, or the need for additional training. Fifty-five percent of teams (including 62 percent of high-performing teams) already track FCR, and their ranks are poised to expand by 52 percent.Case deflection: The Holy Grail for service departments is eliminating the need for customers to reach out in the first place. Making better products and services is the obvious way to achieve this, but so is empowering customers to find answers on their own. Hence, 69 percent of service decision makers cite self-service as a major part of their overall strategies. Only 41 percent of service teams track case deflection, although that figure rises to 54 percent among high-performing organizations. An additional 41 percent plan to measure case deflection, representing potential growth of 77 percent.
Among other increasingly popular service metrics are customer attrition rates — which recognize the comparative value of a repeat customer versus a newly acquired one — and agent-driven revenue — a nod to the opportunities for agents to partner with sales to not only deepen customer relationships, but also increase share-of-wallet.
Seventy-nine percent of service professionals say their metrics emphasize value over timeliness.
Related Topics:
Artificial Intelligence
CXO
Innovation
Digital Transformation: A CXOs Guide
Big Data Analytics