Collect, dissect and act on customer interaction data. Integrate it with different company departments, especially the C-suite. And watch out for privacy issues.
Customer interactions are brimming with valuable intelligence. Savvy customer experience leaders and other business executives use this data to drive CX improvements in operational efficiency, sales effectiveness and other initiatives. Such potential makes conversation and interaction analytics one of the most compelling technologies for the contact center today.
All customer interactions are applicable, whether they occur between human agents and customers or AI agents, bots and customers.
First, organizations should gather raw and unstructured customer interaction data, such as text and audio. This includes transcripts of customer service calls, text messages from chatbot interactions, email, social media direct messages, video and screen-sharing sessions and call recordings. Next, make that data available for analysis, with the goal of understanding what was said, how it was said and why it was said.
This is where conversation analytics, the use of software and machine learning, including natural language processing, comes in. Applying conversation analytics enables companies to derive business value from their conversation data; they analyze it to extract meaning, insights and quantitative metrics.
Gather, analyze and act on customer data
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