In order to measure the performance of a call center’s customer service representatives individually and as a whole, call center analytics is used. Also, this is used to gauge a call center’s overall approach to customer relationship management (CRM) in a quick and responsive manner. Call center management uses this analytics to evaluate interactions, spot patterns, identify knowledge gaps, and make corrections through more training or other means.
1. Text analytics:
The term text analytics refers to a set of linguistic, statistical, and machine learning techniques that model and structure the information content of textual sources for business intelligence, exploratory data analysis, research, or investigation. It is extensively used to respond to business problems, whether independently or in conjunction with query and analysis of fielded, numerical data. Also, the communication with customers these days is not limited to just the written documents. It is also carried out through email, secure messaging, Facebook, Twitter, and other text-centered media. Text analytics, as call center analytics, can review and monitor not only the messages sent to customers but also the message they send to the company. This helps in having a thorough knowledge of customers’ issues.
2. Speech analytics:
The process of analyzing recorded calls to gather customer information to improve communication and future interaction is known as speech analytics. This process is used by customer contact centers to extract information buried in client interactions with an enterprise. Using speech analytics, companies can monitor calls in real time and unearth inefficiencies in their current model, and make process improvements, such as moving to a call script or developing systems for call center agents to utilize in order to achieve the desired outcome. Moreover, the technology can pinpoint cost drivers, trend analysis, identify strengths and weaknesses with processes and products.
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