Speech analytics has revolutionised how organisations manage customer interactions, progressing from its origins in large contact centres to becoming a critical enabler of real-time customer engagement. Historically, it was a resource-intensive tool housed on on-premise servers, primarily adopted by enterprises to optimise quality assurance (QA) processes, extract insights from customer interactions, and, in some cases, improve sales performance. Today, advancements in real-time analytics and large language models (LLMs) have vastly expanded its capabilities, introducing automation, efficiency, and real-time problem-solving into operational workflows.

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This article was first published in the 2025 Best Practice Guide - Raising Standards

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