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What are practical applications of contact-center analytics?

Analytics can be vital to optimize contact-center and agent performance. UC expert Jon Arnold explains two analytics use cases and the key metrics to measure in the contact center.

Analytics are becoming more mainstream in the contact center, with a growing range of practical applications. There...

isn't, however, a standardized set of analytics metrics that every contact center uses. The first step to contact-center analytics is to understand the basic types of analytics applications and the specific business objectives they address. For the contact center, there are two core analytics use cases to consider and, for each, a few specific types of metrics.

First would be agent-based, contact-center analytics that are used to monitor agent performance. One set of metrics could track agent activity across various channels, namely when using the phone, as well as for all the tools used on the desktop. A more advanced set of analytics could be applied to text and voice interactions, where the recognition of keywords or phrases would trigger real-time alerts to ensure agents are staying on-message, as well as to provide assistance for difficult situations.

A second set of contact-center analytics would focus on the overall operational performance of the contact center. One set of metrics could be used to optimize network performance, especially when volumes are highly variable. Another set could monitor cross-channel activity to help the business understand which mix of channels work best for specific customer needs. Not only must those analytics tie into decisions around network management, but they must integrate with customer relationship management data to help agents provide better outcomes for customers.

You should think about contact-center analytics in terms of enabling agents to provide more personalized forms of support based on a deeper understanding of the customer journey. In today's digital world, multichannel is the norm, and this creates new challenges for the contact center, especially for managing all the data associated with a richer set of inputs. This is a key driver for contact-center analytics, as the applications are purpose-built for these new streams of data and help provide agents with a more holistic view of customer needs in real time.

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