Four Types of Data You Should Be Measuring in Your Contact Center

Posted by John Rake

6/25/15 4:36 PM

call_centerThe majority of contact center advancements today are centered on the promise of big data and analytics. For example, digital customer service channels like live chat and videoconferencing invite (or even mandate) customers to enter data about themselves or their service inquiry prior to an interaction.

The agent can then leverage that data input to better serve the customer in a way that increases his or her satisfaction as well as drive organizational profit. For instance, armed with the right information, the agent can keep the session short yet impactful, improving cost per customer and decreasing OPEX. Meanwhile, certain data the customer supplied may lead to an upsell opportunity for the agent.  

Research shows that supported by big data and analytics, best-in-class contact centers outperform the competition in a number of key areas, including first contact resolution, customer satisfaction, agent productivity and average handle time. Here are four types of data that every contact center manager should be strategically using to make actionable and profitable improvements:

Transactional data: Transactional data—pertaining to such things as orders and payments—can help managers see how much money the average customer tends to spend during an interaction, and can determine what variables directly affect spending. For instance, a manager may see that customers spend an average 20 percent more when being serviced via live chat verses phone.

Voice of the customer (VOC) data: VOC data includes information about customer likes, dislikes, habits and tendencies. A solution that capitalizes on VOC data can offer agents an interaction evaluation survey that immediately reveals data about what the customer ordered, what processes were followed, what the customer complained about (and why) and if any notable patterns are emerging.

Customer survey data: You may see that your customers use live chat, but was it a successful service interaction? In what areas did the interaction falter and in which was the customer most satisfied? Data derived from customer surveys, offered as an option following a service interaction, are invaluable for digging deeper into each and every agent interaction. 

Historical data: Historical data provides agents with a window into each customers’ history of behaviors, preferences and patterns. Managers can use this data to identify big picture trends; for instance, after analyzing data from the last 200 customer interactions, a manager might see that a vast majority of customers used live chat, indicating it may be a preferred channel. Managers can also use this data for forecasting and conducting predictive analysis.

There is a myriad of data you can be optimizing within your contact center; however, these four types of data should be fundamental.

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