Call Center Management Featured Article
Data Overload: What's the Most Critical Data to Analyze in the Contact Center?
Each day, your contact center collects thousands of data points. While most of them are never put to use, these data points pile up anyway. For companies seeking to maximize efficiency and workforce productivity, more data analysis can mean lower expenses, happier employees, more satisfied customers and higher profits.
We hear a lot about “big data” today, but most companies are still unaware of how to take advantage of the concept to the fullest. Unanalyzed data is just noise, and it can be distracting and time-consuming to attempt to use it without proper organization, collation, analysis and distribution.
What Data Should You Analyze?
To start with, call center management needs to know what data to collect and analyze for maximum impact on customer satisfaction and the customer experience, according to a recent article by Dick Bourke writing for Customer Think.
“Data and analytics can help your call center monitor and improve its service in everything from wait times to employee performance, customer experience and satisfaction, and overall efficiency,” he wrote. “It gives you a comprehensive and precise picture of your call center’s performance with the goal being to ensure that your call center operates at its peak.”
Without putting some thought into collecting the right data, the contact center and employees can quickly become overwhelmed by data. Consider identifying your customers’ biggest pain points – hold times, transfers, conflicting information, awkward returns – and collect the data that directly correlates to those point points so you can identify problems before they occur.
Key Performance Indicators (KPIs)
Customer Think’s Bourke notes that the following KPIs are generally the most useful to track.
Average time in queue.If this number is longer than industry standard – both for phone calls and other media such as chat -- your forecasts and workforce management are likely out of whack. Alternatively, it could mean that your after-call wrap-up time is too long, which may indicate overly onerous administrative procedures.
Average abandon rate.This is a very significant statistic, since most people who abandon a call or other contact will never return as a customer again. It’s a good place to focus your analysis.
Average handle time.This statistic will tell you how well your employees are resolving customer issues. Long AHTs may mean that agents need more resources or training.
First contact resolution.This is a critical KPI, as it speaks to the quality of operations in your call center and represents a significant element of customer satisfaction. How many calls, chats, emails, or social media messages did it take to solve the customer’s concern?
Absenteeism. High levels of absenteeism may correlate with a lack of training, a poor contact center culture, ineffective management and high turnover. Finding ways to reduce absenteeism will directly benefit the business, as well as other employees.
Schedule adherence.How well your agents adhere to their schedule as a metric of productivity and how well your agents are performing. Low adherence could be due to agent training, bad forecasts, inflexible schedules, and poor call center management processes.
Edited by Maurice Nagle