Leading North American MSO Uses Guavus-IQ Analytics to Accelerate Operations and Dramatically Reduce Costs
公司规模
1,000+
地区
- America
国家
- United States
产品
- Ops-IQ
- LiveOps
技术栈
- Big Data Analytics
- Machine Learning
- Data Lake
实施规模
- Enterprise-wide Deployment
影响指标
- Cost Savings
- Customer Satisfaction
- Productivity Improvements
技术
- 分析与建模 - 大数据分析
- 分析与建模 - 机器学习
适用行业
- 电信
用例
- 预测性维护
服务
- 数据科学服务
- 系统集成
关于客户
The customer is a leading Multiple-System Operator in North America, offering content, TV and internet services to millions of subscribers. The corporation has thousands of employees who are focused on providing an excellent experience to customers spread throughout the United States. Managing a network of this size requires the ultimate in organization and rapid access to information.
挑战
The corporation, a leading Multiple-System Operator in North America, was facing challenges with delayed problem resolution which was affecting customer satisfaction. The Operations Team was unable to identify the root of the problem and rapidly distinguish between customer premise problems and headend CMTS or video server issues. This led to unnecessary dispatch of technicians to homes, which often turned out to be a headend problem instead of an individual set-top box problem. This resulted in customer frustration and a negative impact on their Net Promoter Score.
解决方案
The corporation implemented Ops-IQ, a product that brought together data from separate portions of the Care organization: technical support calls, subscriber trouble tickets and truck roll data. This allowed the Care Ops teams to quickly discover previously overlooked issues common across micro-populations of subscribers. Using Machine Intelligence, Ops-IQ automatically determined the normal rate of care events specific to that micro-population and recognized anomalies in these rates in real-time. This enabled the Care Ops team to immediately triage and pinpoint the heart of the problem and resolve it more expeditiously, improving customer satisfaction and Net Promoter Score dramatically.
运营影响
数量效益
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