Customer service

Data analysis and cloud-based solutions, keys to improve customer service

Enreach 15/12/2016
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Contact centers are moving from being mere call centers to becoming true centers of customer knowledge through the adoption of cloud-based solutions and tools that enable rapid and efficient analysis of large amounts of data. The more customer knowledge, the more business and growth opportunities we will have.

Thus, knowledge is becoming more and more valuable. A recent study by the consulting firm Gartner estimates that by the year 2020, the market value of data analysis and information will be around 1.6 million dollars. The fundamental reason for this growth is simple: a company that knows its customers better improves the quality of its contact centers because it is able to respond to their needs in a more efficient way, increasing their satisfaction and loyalty.

Thanks to the integration of all customer data from satisfaction surveys, technical support questions, telephone calls, invoices, etc., and to the modern tools that make it possible to jointly analyze all this information, it is possible to generate unique knowledge and great value that can be used to increase customer satisfaction and loyalty and, consequently, business benefits.

The key, therefore, is to enhance data analysis in order to improve the customer experience, as Wendy Mikkelsen, Director of Marketing Solutions at Interactive Intelligence, points out, who also gives us five keys to increase and maximize the data analysis:

  • Analysis of the recorded conversations must be combined with real-time analysis, while certain words and/or key expressions, emotions and reactions… are produced and detected, using alerts, automation and other tools.
  • Optimization of automatic response systems or interactive voice response by integrating them into an omnichannel client strategy to offer simple and personalized customer choices and, if necessary, refer the appropriate agent.
  • Data analysis must be implemented in the different channels used by clients in real time, in order to identify the interactions, interests, behaviors and that the agent can serve them more efficiently thanks to the information available to them.
  • Promote predictive analysis because it serves as a basis for improving both the strategic planning of contact centers and the customer service itself by offering a more personalized and proactive service.
  • Analyzing performance, both historical and in real time, is essential to understand what is happening, identifying trends and, ultimately, improving customer service.
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