Each of Chaise’s 6,000 call enter agents worldwide at the company’s 1 1 call centers fields field up to 120 calls per day. The company handles slightly less than 200 million calls each year from a customer base of 100 million. Even a small reduction of to the amount of calls received results in savings of millions of dollars and improved customer service for Chase. Achieving such a reduction is easier said than done, however. Lie. ‘ 2006, Chase Card Services attempted to com- polish this by Improving first-call resolution.
First-call resolution Is when a call center agent Is able to resolve a customers issues during the initial call to customer service without requiring additional calls. The problem was that the company’s record keeping did not give an accurate account of current rates of first-call resolution. Chase had previously tried tracking first-call resolution rates ay having agents log the content and results of each call they received. But this task was time- consuming and was not standardized, since agents :ended to record results subjectively and not in a uniform way.
Company policies for some customer requests were also far from ideal for Increasing First-call resolution. For example, agents were only able to process balance transfers for customers ailing from their homes, and the fee structure Underwent multiple changes over a short span, prompting repeat calls. ‘Pop improve call center efficiency, Chase contracted with Innate technologies to implement a The system monitors and tags each call with the :epic and length of the call as well as the length of time the agent that handled the call has been working.
It doesn’t require agents to perform any lotion to acquire this information; it tracks calls automatically by keeping track of the keyboard strokes of each agent. As soon as an agent clicks on the feature of the account that the customer is calling bout, the Innate system automatically identifies the reason for the call. Propriety algorithms match the reason and caller identification to the amount of time predetermined for each type of call. The system then monitors discrepancies in call time, depending on the reason for the call.
For example, a call from a customer requiring card activation should be a quick call, so the system will pinpoint card activation calls that take longer than normal, or fee dispute calls that are shorter than normal. But sometimes customers have multiple reasons for calling, which would have been very official to track prior to the implementation of Antenna’s system. Now Innate separates each individual- al reason for calling and organizes them into a sequence, so that a call with multiple issues to resolve is analyzed using the appropriate time frame.
By separating and organizing reasons for calling into distinct categories, Chase is able to determine criteria for declaring particular calls ‘resolved’ For example, a card activation call will be considered resolved after only a few days without a follow-up call, but a disputed fee call won’t be considered resolved until the customer received another statement without any complaints. This method gives Chase much more accurate data on first-call resolution, a feat which is regarded as very difficult and impressive in the industry.
Innate compiles this data and distributes it to Chase Card Services in the form of weekly reports on call type and length, call handling times, repeat call rates, and other performance measures that allow both agents and supervisors to monitor their performance. The system also connects reports with call recordings to assist managers in coaching and evaluating their agents. When the system was still Ewing implemented, Innate used historical call data gathered prior to the implementation to create initial reports.
