Sokolove Law CallMiner Interaction Analytics Delivers Higher Call Center Quality at Lower Cost for Law Firm
公司规模
Mid-size Company
地区
- America
国家
- United States
产品
- CallMiner Eureka Interaction Analytics
- CallMiner MyEureka Performance Feedback Portal
技术栈
- Interaction Analytics
- Automated Monitoring
- Automated Scoring
实施规模
- Enterprise-wide Deployment
影响指标
- Cost Savings
- Productivity Improvements
- Customer Satisfaction
技术
- 分析与建模 - 实时分析
- 应用基础设施与中间件 - 数据交换与集成
服务
- 数据科学服务
- 系统集成
关于客户
Sokolove Law is a national personal injury law firm with operations in all 50 states of the United States. The firm has an internal Tier 1 call center with 55 agents, along with Tier 2 and Tier 3 external call centers with an additional 29 agents. These agents support current and potential clients, discussing sensitive personal information with them. Therefore, quality and professionalism are essential in their interactions. To ensure these standards, Sokolove employed a team of five quality assurance managers to supervise the 55 agents. The firm's process called for each contact center agent to have one call per week reviewed by a quality assurance analyst.
挑战
Sokolove Law, a national personal injury law firm, had a call center with 55 agents that dealt with sensitive personal information. Quality and professionalism were paramount. To ensure these standards, Sokolove employed a team of five quality assurance managers (QA) to supervise the agents. The QA team's job involved listening to call recordings to ensure interactions met Sokolove’s high standards and to identify areas for improvement. However, this manual process was time-consuming and could only cover a fraction of the calls. The firm needed a solution that could analyze more calls, ensure adherence to interaction protocols, improve productivity and outcomes, and provide objective agent evaluations on more calls.
解决方案
Sokolove Law implemented the CallMiner Eureka Interaction Analytics and the CallMiner MyEureka Performance Feedback Portal. The Eureka platform automatically monitors 100% of contacts, including calls, chat/text, and email, and applies advanced analytics to monitor contacts for parameters defined by Sokolove. It calculates and provides a score for each call, which can be analyzed and reported at multiple levels. The myEureka self-service feedback portal provides fair, impartial scoring of all interactions, alleviating the subjectivity of the former manual QA process. The implementation process was divided into three stages: Discover, Create & Monitor, and Rollout. The process took approximately 4½ months from start to finish.
运营影响
数量效益
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