CONTACT CENTER METRICS
ILLUSTRATION PROVIDED BY ADOBE STOCK
FROM
EFFICIENCY TO CX WHY AND HOW DATA-DRIVEN CONTACT CENTER METRICS HAVE CHANGED .
BY DINA VANCE , ULYSSES LEARNING
Overhead projectors . Pagers . Oneline red LED tickers . These were the early ways we shared our call center statistics . It is incredible how much the contact center landscape has evolved since then . Words we use today such as chatbots , predictive analytics , sentiment analysis , artificial intelligence ( AI ), call routing , and voice assistance would be unheard of a few years ago ( SEE FIGURE 1 ).
These concepts have changed how consumers interact with companies , and in many cases have enabled contact centers to become an integral part of a company ’ s ability to shape the customer experience ( CX ). The evolution of both technology and metrics has also created a new landscape for screening , hiring , managing , and coaching agents .
18 CONTACT CENTER PIPELINE
CRITICALITY OF MEASUREMENT
One aspect of driving improved CX results that has not changed is “ what gets measured gets done .” As the industry has evolved , the focus on what to measure and how to measure it - ensuring the right outcomes at each point of contact between customer service representatives and their customers - has become essential to obtaining and retaining an organization ’ s competitive advantage .
ONE ASPECT OF DRIVING IMPROVED CX RESULTS THAT HAS NOT CHANGED IS “ WHAT GETS MEASURED GETS DONE .”
The shift to a more data-driven approach in measuring CX has become critical in driving improved results . Organizations now place greater emphasis on identifying key performance indicators ( KPIs ) that truly reflect customer satisfaction and loyalty .
This involves not only tracking traditional metrics like Net Promoter Score ( NPS ) and Customer Satisfaction ( CSAT ) scores but also incorporating advanced analytics and real-time feedback mechanisms .
By leveraging technologies such as AI and machine learning , companies can analyze vast amounts of data to uncover deeper insights into customer behavior and preferences . This allows for more personalized and proactive engagement strategies , ensuring that the right outcomes are achieved at all points of customer contact .