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Tag Archives | data analysis

Detection of Data Errors

Ten Guidelines for Clean Customer Feedback Data

Customer experience management (CEM) programs involve the collection, analysis and dissemination of customer feedback. These customer feedback data are extremely valuable to businesses. Customer feedback data are used to help senior executives identify and improve key drivers of customer loyalty. They help call center staff immediately address specific customer issues.  They help managers understand how […]

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Assessing the Validity of your Customer Experience Management Program

Companies with customer experience management (CEM) programs rely heavily on customer feedback in making business decisions, including, setting strategy, compensating employees, allocating company resources, changing business processes, benchmarking best practices and developing employee training programs just to name a few. The quality of the customer feedback directly impacts the quality of these business decisions. Poor […]

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Two Things Everyone Needs to Know About Your CEM Program

Customer Experience Management (CEM) programs are complex, data intensive programs. To be successful, you need to effectively communicate information about that program to important stakeholders, including employees, partners, and customers. We know that loyalty leading companies communicate customer initiatives throughout the company, from top executives to front-line employees.  For example, in a best practices study on […]

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Simplifying Loyalty Driver Analysis

Customer Experience Management (CEM) programs use customer feedback data to help understand and improve the quality of the customer relationship. In their attempts to improve systemic problems, companies use these data to identify where customer experience improvement efforts will have the greatest return on investment (ROI). Facing a tidal wave of customer feedback data, how do […]

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Maximizing the value of your customer experience management data

Customer experience management (CEM) programs can generate a lot of data. The value of these data is based on their utility to improve the customer experience and the overall quality of the customer relationship. Companies, to be successful need to effectively organize and analyze these large data sets as well as disseminate resulting information to […]

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