An Analytical Approach to Better Call Center Customer Service

Call Center Customer Service and Analytics Data

Call center customer service can make or break the success of a business. Around the world, many call centers struggle to provide a strong customer service experience that drives customer retention.

However, there seems to be a disconnect between callers and companies in the way that they perceive customer service efforts in call centers. A Harvard Management Update cited by Forbes notes: “80% of companies surveyed said that they offer superior customer service, but only 8% of their customers agreed with them.”

Why Call Center Customer Service Matters

Just how important is call center customer service to retaining customers and driving success?

According to statistics cited by credit card giant American Express, “78% of consumers have bailed on a transaction or not made an intended purchase because of a poor service experience.” Worse yet, the AmEx study also stated that “two in five Americans have threatened to switch to a competitor (39%).”

In other words, bad customer service doesn’t just hurt your company, it can give competitors a leg up by sending free business their way.

The Data Issue

The need for better customer service in call centers for any industry is clear, but creating a strategy for making improvements is difficult at best. There are a lot of factors that can make or break a customer’s call experience. The most basic elements that call centers often seek to improve include, but are not limited to:

  • Phone agent soft skills
  • Phone agent knowledge
  • Phone system interface

To create a strategy to improve any of these elements requires call centers to have something else FIRST: detailed information on customer interactions with the call center.

To empower a strategy approach for improving customer service in a call center, you need information. The trouble is, most call centers are working with incomplete data, often relying on assessments of just 1-2% of phone agent to customer interactions.

Empowering an Analytical Approach to Superior Call Center Customer Service

So, what’s one thing your call center could do right now to empower better planning for achieving superior customer service?

Collecting data on the other 98-99% of calls that can’t be assessed manually.

This is where automated analysis solutions such as predictive voice analytics can really make a difference. Predictive voice analytics solutions use powerful machine-learning algorithms to take recorded audio and break up the voices of callers into defined feature vectors using digital signal processing.

Once the voice features of callers (or phone agents) have been broken down into feature vectors, those vectors are plugged into advanced algorithms that continuously learn with additional results data.

Voice analytics can pick out the emotional behavior and tone of all of your agents and customers across all conversations in your call center operation. This gives you the ability to learn:

  • Which agents were able to actively engage customers and which agents were apathetic and/or disengaged
  • How your phone agents engaged with your customers (use of empathy/soft skills)
  • Which customers remain upset after ending the call

The more information you have about your operations, the more empowered you will be to make improvements to your call center’s customer experience.

For example, you can use the automated assessments of phone agent performance to quickly establish which phone agents are most in need of extra training, improving your call center customer experience by improving underperforming phone agents.

To make a thorough and effective plan for improving caller experience at your call center, you need the right information. Predictive voice analytics helps put that information at your fingertips.

Discover How Predictive Voice Analytics Increases Agent Performance