At contact center provider Afni, the hours of customer contact its agents engage in on a daily basis constitute big data. Every word spoken or typed is a piece of data that can be analyzed and used to improve training, coaching, and performance. To help harness the power of big data, Afni last year partnered with speech analytics company CallMiner.
CallMiner converts spoken words to text, and then mines for what is said and the context in which it is said. This information is placed into categories and finally rolled up into scores. The system boils down data from hundreds of calls into a single number and shows trends.
Data Application
There are two specific areas in which Afni’s CallMiner project has seen early success. The first is in individual interactions between agent and coach. Where a coach may listen to two or three calls and make assumptions, CallMiner looks at every metric on a high volume of calls, giving a more accurate representation of what is going on. Coaches are able to quickly identify behaviors that affect multiple metrics and work with their agents to fix them. Additionally, coaches can pinpoint specific examples for agents to view and listen to, helping with buy-in at the agent level. This has reduced coach prep time by more than 20 percent in most interactions, allowing the coach to spend more time building relationships. Additional time spent in human interactions has contributed to 3 percent less attrition last year.
On a broader scale, CallMiner has allowed Afni to see overall trends within the call center. When CallMinder analyzed one of Afni’s crucial quality metrics, Entire Rep Performance (ERP), it found a direct correlation between the five steps of the call sequencing model and ERP scores. If an agent did none of the steps, he scored below 80 percent. Hitting two steps earned an 86 percent; three steps earned a 92 percent, and four or more steps resulted in a 96 percent. This knowledge gave rise to a training and coaching campaign around call sequencing that has resulted in ERP rising 5 percent in two months.
Currently, Afni is utilizing CallMiner in only one of its large projects. But within this project, Afni continues to find new uses for the system. One initiative is looking at call types to identify opportunities for supplemental training and coaching, as well as increasing the effectiveness of new hire training. Afni also just finished implementing it in the Receivables Management group and next will implement it in the Philippines.
Results
CallMiner has made Afni more effective at coaching its agents and identified opportunities for targeted training. Performance improvement gained from this system has contributed to the 800-seat growth Afni saw last year, as well as expansion of its Philippines center, which grew by 100 people last year, and Work-at-Home operations, which grew to 170 seats.
