Definition
Speech analytics is technology that analyses recorded or live call audio to detect patterns, keywords, sentiment and compliance issues at scale, well beyond what manual call sampling can cover.
From a WFM perspective, speech analytics data increasingly feeds into forecasting and quality processes by flagging shifts in call reasons or complexity before they show up as a change in AHT. This gives planners earlier warning of a driver behind a volume or handle-time shift.
It is distinct from Automatic Speech Recognition, which is the underlying technology that converts speech to text. Speech analytics is the layer that finds patterns in that text.
Why it matters
- Speech analytics can reveal why AHT or volume is changing before the trend is visible in historical averages.
- It extends quality coverage far beyond manual sampling, which helps identify training needs that affect future handle time.
- Planners should treat it as an input signal, not a replacement for the core forecast, since patterns still need to be validated against actual volume.
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