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For agents at a contact centre receiving calls, the most important piece ofinformation is the reason for a given call. An agent cannot provide support ona call if they do not know why a customer is calling. In this paper we describeour implementation of a commercial system to detect Purpose of Call statementsin English business call transcripts in real time. We present a detailedanalysis of types of Purpose of Call statements and language patterns relatedto them, discuss an approach to collect rich training data by bootstrappingfrom a set of rules to a neural model, and describe a hybrid model whichconsists of a transformer-based classifier and a set of rules by leveraginginsights from the analysis of call transcripts. The model achieved 88.6 F1 onaverage in various types of business calls when tested on real life data andhas low inference time. We reflect on the challenges and design decisions whendeveloping and deploying the system.

Developing a Production System for Purpose of Call Detection in Business Phone Conversations