Call Center Management Featured Article
Making Sense of Call Center Data with Analytics
Data is everywhere these days. If you’re using any modern call center solutions at all, you’re probably capturing a lot of information from your phone system, your workforce management solution, your call recording system and more. Maybe you even use some of that information to prepare regular reports. But are you using it to your maximum advantage? As the saying goes, “Data is not information.” Not until someone’s made sense of it.
Many call center solutions today come with built-in analytics tools that make the capture of data and its interpretation into usable information easier than in the past. So the question is…what should you be measuring?
What Data Should I Measure in the Call Center?
Data and analytics can help your call center improve and monitor its operations in in a variety of areas, from caller wait times to employee performance, customer experience and satisfaction, and overall efficiency. It can track valuable metrics such as first call resolution and quantify your call center’s performance when it comes to the customer journey.
How Do Call Center Solutions Analytics Help?
There are a variety of ways data can be captured in the contact center using analytics. These might include:
Speech analytics. This method uses natural language processing to understand what’s being said in calls in real time. It can also capture sentiment (what’s being said by NOT being said) and tone to effectively gauge customer emotion and satisfaction. It can help you gather data on agent skills and performance, call type, knowledge gaps, and the overall customer experience.
Text analytics. Like speech analytics, text analytics captures the intent of written language such as in emails or live chat. Cross-channel analytics are often an indication that a solution will gather data from both speech sources and text sources to build a complete picture of the customer interaction, which may have happened in more than one channel.
Performance analytics. These are for the agents, and they gather information on how efficiently an agent is doing his or her job, and if that agent is hitting all the optimal procedures for the call. It can measure actual call/contact time, wrap-up, after-call work, handle times and look for inefficiencies.
Predictive analytics. Predictive analytics use current conditions to make predictions. If a customer asks for x, chances are that the next logical step will be y. Predictive analytics can make agents’ jobs easier and cut down on handle time by providing the agent with the likely resources and answers he or she will need to complete the call.
To help call centers learn more about how they can improve customer interactions and processes with analytics, Verint (News - Alert) Monet’s Integrated Analytics Tools has prepared a series of demos that explains the benefits and outcomes.
Edited by Maurice Nagle