Definition
Named entity recognition (NER) is a natural language processing technique that automatically identifies and classifies specific pieces of information inside unstructured text, such as a call transcript. Common entity types include names, locations, dates, phone numbers, product names, and competitor mentions.
In call tracking, NER runs against transcribed conversations to pull out structured facts without manual review. A call where a customer mentions a specific vehicle model, a service address, or a competitor's name gets tagged automatically, at scale.
That matters because 96% of inbound calls are analyzed by zero humans. NER is one of the mechanisms that makes automated analysis possible without sacrificing specificity.
Convirza applies NER as part of its Embedded Conversation Intelligence layer, drawing on the deepest call benchmark corpus in the industry to train entity models against real-world call patterns across verticals.
For broader context on how NER fits into call analysis, see Conversation Intelligence.
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