Real Time Resolutions Improves Contact Center Efficiency with CallMiner Eureka Analytics
公司规模
200-1,000
地区
- America
国家
- United States
产品
- CallMiner Eureka Interaction Analytics
- CallMiner myEureka Performance Feedback Portal
技术栈
- Interaction Analytics
- Performance Feedback Portal
实施规模
- Enterprise-wide Deployment
影响指标
- Cost Savings
- Productivity Improvements
技术
- 分析与建模 - 实时分析
适用行业
- 金融与保险
适用功能
- 销售与市场营销
用例
- 过程控制与优化
- 实时定位系统 (RTLS)
服务
- 数据科学服务
关于客户
Real Time Resolutions (RTR) is a full-service mortgage servicer, debt collection, and business process outsourcer operating in the 1st and 3rd party marketplace. Their portfolio consists of mortgage and a variety of consumer accounts including those in bankruptcy. RTR employs 150 Recovery Agents (CSPs) across their U.S. branches. The company is committed to delivering the best possible service to its customers while also maintaining a high level of efficiency in its operations. They are constantly looking for ways to improve their processes and reduce operational costs. One of the key areas they identified for improvement was their contact center, where they saw potential for reducing After Call Work (ACW) and increasing call volumes. They recognized the need for a solution that could help them achieve these goals without compromising on the quality of service they provide to their customers.
挑战
Real Time Resolutions (RTR) is a full-service mortgage servicer, debt collection, and business process outsourcer operating in the 1st and 3rd party marketplace with a portfolio consisting of mortgage and a variety of consumer accounts including those in bankruptcy. RTR employs 150 Recovery Agents (CSPs) across their U.S. branches. The company was facing challenges in reducing After Call Work (ACW) and operational costs, and improving call volumes in their contact center. They identified that the agents’ average ACW had a strong relationship to product type. For one specific product type, the average call duration was 2 minutes 30 seconds, but the average after call work was 6 minutes 30 seconds. This was not an occasional occurrence. In some months, the average for call durations was only one third of ACW. The analysis also uncovered that some agents (even those who sat next to each other) had drastically different ACW times.
解决方案
RTR decided to concentrate on one or two easily identifiable business problems that could be solved with a minimum amount of effort in a short period of time. They used CallMiner’s Eureka Interaction Analytics to identify the difference between revenue-generating ‘Talk Time’ (TT) and resource-burning ‘After Call Work’ (ACW). CallMiner Interaction Analytics automatically categorises every call into existing (or expanded) codes. This automation eliminates the need for manual categorisation (saving 100 percent of that time). It also more accurately captures the data. After aggregating call attributes, and other data, the CallMiner Eureka platform categorizes all words in each call to determine reasons for the call, product or competitors mentioned, participant behaviors, presence of procedural language, outcomes or actions. It also measures acoustic signals for call duration, silence/noise, agitation, stress and tempo, and scores calls by calculating performance indicators per call.
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