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How Customer Service and Customer Experience Teams Differ Over VoC

An unforeseen consequence of the rise of customer experience teams at the world's companies is that some of their daily work processes clash with that of customer service teams; voice of the customer data is one good example

Customer service teams may have been around for a long time in most companies but the way they do their jobs has changed a lot in recent years, and most of this is down to a new function. Customer experience teams are increasingly popular at many companies, and are charged with making their firms more “customer centric.”

This essentially means ensuring all processes and decisions put customers first rather than other common business goals, such as cutting costs or making a process quicker for employees to complete. While this is undoubtedly the right move for many firms, it does cause some problems, and not least is that customer service and customer experience teams view certain goals and processes differently.

This series of posts has looked at some of those differences (see list on the right hand side of this post), and one of the most important is how customer service and customer experience teams use voice of the customer (VoC) data, as they rarely use these tools in the same way.

The difference really boils down to the scope of their use of VoC data. Customer service teams use VoC to monitor and improve the service experience, a key driver of customer loyalty. Whereas customer experience teams use VoC to bolster customer awareness within the company, to feed strategic cross-functional decision making, and to measure the ROI of customer experience investments.

Voice of the Customer

VoC describes the methods used to source and understand the actual experiences and perceptions customers have while interacting with the company. There are many ways to collect VoC, but these methods are categorized in two ways. First, how a company sources the data (whether it’s solicited or observed) and, second, the form of the data (whether it’s structured or unstructured). Common examples are:

Similarities

Each function uses VoC to:

  • Measure the customer experience from the customer’s point of view. Metrics like NPS, Customer Effort, or Customer Satisfaction, each have counterpoints to more pragmatic metrics, such as “average handle time” or “on-time delivery,” that relate to the company’s operational perspective.

  • Identify particular problems within the customer experience that can be improved. Whether one-off or systemic, customer feedback can rapidly clarify the who, what, when, where, and why of issues that affect customers’ satisfaction with a product or service.

Differences

Each function has a distinctive perspective that shapes their own VoC tactics and goals:

  • Perspective: Customer service teams usually focus more narrowly on the quality of service interactions. Customer experience teams use VoC to assess the strength of overall customer loyalty.

  • Purpose: Despite using VoC to improve their measurement of customer satisfaction and identify where the customer service expeience isn’t working, customer service managers also depend on VoC to control or audit channel/rep performance, guide training efforts through a deeper customer understanding, and inform their work on multi-channel service design.

    Customer experience teams, in contrast, use VoC to broaden customer understanding to functions that may not deal with customers directly, coordinate and prioritize cross-functional collaboration by using the “end-to-end customer journey” (the typical set of interactions that a customer has with the company), and to enable granular analysis of customer loyalty economics.

  • Audience: Customer service teams most often report their data within the function, ensuring team leaders have access to the information.

    For their part, customer experience functions typically bring their data to product and functional leaders, and many companies have created cross-functional “customer experience councils” to help identify and prioritize opportunities for improvement that VoC data throw up.

 

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