Transforming Customer Emotions and Behaviors into Usable Information

Customer contact centers have always collected data or at least informally made observations about their customers personalities. Phone agents use these observations to help guide customer interactions in subtle, but effective ways.

Just as body language gives us a wealth of information about a person in our daily conversations, so does the way a person speaks inform our opinions when we speak over the phone.

Until recently, this information has only been subjective  and only determined at an individual level  some people are better at assessing the emotions and behaviors beyond the words spoken to really move the conversation forward.

New technologies, however, have made it possible to train computers using artificial intelligence to conduct the same type of voice analysis as humans do  only faster, more reliably and on a massive scale. Those new technologies can transform the best guess intuitional assessment of customer intentions into usable information that you can leverage across your business.

How did this technology come about, how can we make sense of the data it collects, and how does this affect the customer experience? Here are a few answers to these questions:

How Did We Get Here?

In the last few decades, information technology has grown by leaps and bounds. Our society has become one that is always on, with smartphones giving people persistent access to the internet.

Thanks to advancements in computer technology, it is now possible to create self-learning algorithms for artificial intelligence programs that can learn by observing patterns in large-scale data sets. These advanced unsupervised machine learning programs can achieve a predictive analysis of likely outcomes based on this data from past trends.

Over time, as these programs collect more and more data, theyll become even better at creating predictions of future outcomes. One example of this is how RankMiners predictive voice analytics solution can assess a customers emotional behavior and tone to predict how theyll respond during a future call.

Making Sense of Enormous Data Sets

With the rise of the internet came the rise of big data on a scale that was previously unimaginable. It used to take a considerable amount of time for analysts to compile data manually and organize it into useful reports.

Advances in computer technology have allowed tremendous advancements in big data, allowing for enormous data sets to be compiled by computers and for machine learning algorithms to turn that data into useful information.

This information can be used by companies to gain insight into customers and to prescribe reasonable next steps for optimizing business results.

For example, predictive voice analytics can pick apart how customers speak during a phone call to analyze their emotional behavior at the time of the call. By comparing all of your calls, the program can then identify which customers are most likely to give your phone agents a positive response on a future call. This allows you to prioritize the calls that will drive your business forward.

How Has This Affected the Customer Experience (CX)?

The application of predictive voice analytics to contact center operations has dramatically improved CX for those companies that have taken advantage of this technology.

By analyzing 100% of calls with automated machine learning algorithms, businesses can get reliable, well-sampled assessments of how customers are interacting with a brand. This, in turn, allows contact centers to identify strengths and weaknesses in the brand, improving their ability to interact with customers and increase satisfaction.

The specific analysis of a customers voice-based emotional state can provide deeper insight into why that customer is dissatisfied or leaving the business relationship.

For example, if a customers mood changes suddenly during a conversation, a voice analytics program can pick up when the shift occurred so that QA stall listening to the call can skip to that part and hear what was said and how, potentially uncovering a major source of dissatisfaction.

With the right predictive voice analytics solution, you can turn customer emotions/behaviors into specific, actionable information that can help build your contact centers success.

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