24th January 2023

Contact centres interact with customers across multiple channels, from phone calls to online chats.
Understanding these interactions is crucial for improving service, ensuring compliance, and supporting agents.
Conversation analytics helps organisations make sense of these conversations by providing valuable insights.
To find out more, we asked Frank Sherlock, VP of International, CallMiner, to define conversation analytics.
Watch the video below to hear Frank give a definition of conversation analytics:
With thanks to Frank Sherlock, VP of International, CallMiner, for contributing to this video.
Conversation analytics is the process of analysing customer interactions across different communication channels. It builds on speech analytics, which converts spoken words into text and analyses them for key phrases and patterns.
However, conversation analytics goes further by looking at interactions more holistically, as Frank explains:
“If you think back to speech analytics, speech analytics does what it says on the tin. It basically is analysing speech text, that is converting speech to text and doing an analytics based on the words and phrases within those conversations.”
Rather than focusing only on words and phrases, it examines the full customer journey. It helps organisations assess the quality and consistency of interactions, whether they happen over the phone, via email, or through messaging apps.
Conversation analytics is widely used for:
By offering a clearer view of customer interactions, conversation analytics helps contact centres enhance service quality, identify trends, and support their teams more effectively.
“Conversation analytics provides organizations with insights based on the interactions with customers across channels to provide a more comprehensive, and more coherent, sense of the quality and consistency of those interactions.
Generally it’s used to support compliance, as well as agent insights both in real time and post-interaction.”
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Reviewed by: Hannah Swankie