CallMiner > 实例探究 > Afni Improves CSAT, Sales and FCR with Automated Analytics

Afni Improves CSAT, Sales and FCR with Automated Analytics

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公司规模
1,000+
地区
  • America
国家
  • United States
产品
  • CallMiner Eureka Interaction Analytics
  • CallMiner myEureka Performance Feedback Portal
技术栈
  • Data Analytics
  • Data Visualization
实施规模
  • Enterprise-wide Deployment
影响指标
  • Customer Satisfaction
  • Productivity Improvements
  • Revenue Growth
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
适用功能
  • 商业运营
  • 销售与市场营销
服务
  • 数据科学服务
关于客户
Afni is a business process outsourcing (BPO) services provider that works closely with its clients to improve their business outcomes. To accomplish that, Afni pursues continual improvement in its own operations. The company employs more than 9,000 agents and handles a large volume of customer interactions across various channels. Afni's commitment to quality training is firm, but the company wanted to make its training more targeted and effective by accurately identifying areas for performance improvement. The company recognized the importance of optimizing customer contact outcomes, including raising customer satisfaction, improving performance on sales calls, and increasing its first call resolution (FCR) rate.
挑战
Afni, a business process outsourcing (BPO) services provider, wanted to improve the quality of work performed in its contact centers by identifying training opportunities and improving the training and coaching it gives its more than 9,000 agents. The company was firmly committed to quality training, but wanted to more accurately identify areas for performance improvement and then make the training more targeted and effective. Afni recognized that the keys to optimizing customer contact outcomes including raising customer satisfaction among the clients’ customers it contacts, improving performance on sales calls, and increasing its first call resolution (FCR) rate. It specifically wanted to use analytics to learn what language was used and what other specific behaviors occurred on its calls. The idea was to assess the best outcomes for contacts, determine which agents achieved those results, benchmark what those top performers did and apply it across all agents through training, while also using coaching to bring agents that lagged on KPIs closer to the norms.
解决方案
Afni implemented CallMiner’s Eureka interaction analytics solution and the myEureka portal solution that provides performance feedback to agents and managers. The initial rollout was used to support two Afni clients that collectively accounted for 400 agents and 400,000 monthly inbound calls. CallMiner Eureka is the leading solution to improve contact center and enterprise performance through automated interaction analytics. It immediately reveals insights from automated analysis of communications between contact centers and customers across multiple channels. CallMiner Eureka provides comprehensive performance data and insight because it can automatically monitor, record, transcribe and objectively score 100 percent of telephone, email and text contacts. Afni set the words, phrases and conditions they wanted CallMiner Eureka to monitor. Results are compiled into scorecards that reflect performance at the agent and group levels. The scoring enables contact center supervisors to instantly identify potential problems or trends.
运营影响
  • Afni was able to identify specific behaviors that correlated with customer behavior and uncover other cause-and-effect relationships.
  • The company was able to make changes to its processes, training, and coaching based on the insights gained from the analytics.
  • Coaches were able to find the type of calls they wanted to review 35% faster.
  • The total time required to prepare for client calibration sessions was reduced by 90%.
数量效益
  • A 17% improvement in the correct positioning language used on calls.
  • An 8.7% improvement in discovery process statements.
  • A 4% increase in customer satisfaction.
  • A 55% increase in agents that exceeded their sales goals.
  • A 2.8% increase in first call resolution.

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