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Lay the Foundation for Customer Analytics in the Contact Center

Data is nothing new to the contact center. Companies have been collecting data for as long as they’ve been serving customers. What’s new is what the data is being used to empower. Big Data and Analytics are two of the discussions that have come to the fore over the last few years. Now that we have the technology to tap the data, we’ve got to figure out what to do with it to drive business.

There are, of course, different applications of analytics. The types of service analytics include business analytics, consumption analytics and customer analytics. This series of blog posts is focused on customer analytics in the contact center. As defined by the TSIA:

“Customer analytics serve as the basis for Voice of the Customer (VoC) programs, analyzing customer conversations from support interactions, surveys and social media to identify trends and sentiments.”

Sounds simple, right? But what the TSIA discovered in a six-month deep research dive into customer analytics identifies a few flies in the ointment, including:

  • Services employees lack the training or knowledge to use analytics platforms
  • Access to data analysts who can help define services analytics are limited due to IT downsizing
  • TSIA members average 13 separate databases of customer information, increasing complexity

The TSIA also found that companies are turning to service providers to define customer analytics programs as they realized “data scientist” is not in their DNA. With that in mind, this post (1 in a series of 5) delves into the explanation of how to define the customer insights you need from analytics to take action that drives business.

Defining the Customer Journey to Loyalty

There’s so much data to look at that it’s often difficult to decide which has the most impact on customer satisfaction and loyalty. In analyzing data, sometimes you may even find that the pressure between doing the job and the operational goals are in conflict. What it comes down to is identifying which characteristics contribute the most toward your company’s definition for success. Customer analytics should replace intuition with intelligence based on an analysis of customer sentiment, verbatims and behaviors in relation to desired business objectives.

Loyalty is a metric that fluctuates, depending on those objectives. It is a metric that each company must figure out for itself. Whatever you decide to measure must cause a business goal you care about. For example, one company’s highest customer priority is for people to renew their contracts. For others, it could be about increasing customer advocacy or expanding share of customer wallet.

The secret to metrics is that you must answer the questions in order to create them. In this case, this means answering, “What does loyalty mean to you?” Once you have the question answered you need to identify what the customer journey looks like on the way to achieving that answer. It’s important to realize that no one transaction defines the life of a customer. It’s constructed of multiple touch points that can include:

  • What happens in retail stores
  • The experience of adding services
  • Using self-help on the website
  • What about the mobile app?

What you need to define is what we call the trajectory of the customer experience. This means looking at how each touch point satisfies the need at the center of each experience during that lifetime. Also to be considered is what choices the customer has during each experience – to purchase or defer renewal, for example.

Below is an example of what the customer journey could look like for a wireless customer:

customer-analytics-in-the-contact-center

customer-analytics-in-the-contact-center

Once you’ve analyzed the different experiences that a customer could encounter during their relationship journey, it’s important to define what will constitute their memories from each experience. You see, customers don’t remember everything; they remember the peaks and discard the rest. So what you really need to focus on using customer analytics to do is to help you understand the peaks and how to create the ones that contribute to the customer choosing to do what meets your defined metric for loyalty.

In the next post of the series, we’ll look at how to use customer analytics to design business processes