Call Center Classification


A large global bank was looking for ways to improve its customer engagement. They decided to prioritize inbound communications in order to focus on customers that really needs human intervention and time, and to return automate responses to more simple and recurrent queries. The Bank wonders if Artificial intelligence could help to classify inbound communications, optimizing the whole process without increasing the call center human resources needs.


To Classify inbound communications


We use our T7 Machine to understand the nature of inbound communications, to prioritize the ones that require human interventions and to automate responses of the simpler and common ones. T7 Machine processes written communications (live chat, email, social media) with entity extraction, and verbal communications with voice-to-text plus entity extraction.

After the training, the T7 Machine is able to classify the queries attending to Bank key specifications. This allows to return a priority list of the incoming queries, and to automate responses of many others simpler ones, like balance queries or opening hours.   

The automation reduces the amount of queries that requires human intervention and, at the same time, allows agents to spend more time with the highest priority cases. This improves customer satisfaction without increasing operational costs.


Satisfaction without increasing operational costs

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