May 31, 2021
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Service categories
Service Lines
Artificial Intelligence
Software Development
Web Development
Domain focus
Business Services
Technology
Challenge
An average call center operator takes several tens of calls a day. So there are about four hundred or more phone calls a month. It is therefore only natural for call center managers that it is not in their time to listen to all calls, to discover and decide effectively who of the operators is doing their job well and who is not. At the same time, they need to know whether any of the operators is not starting on a particular day, hour or conversation to deteriorate or improve, what are the connections between the words of the operator and the reaction of customers, etc.
An average call center operator takes several tens of calls a day. So there are about four hundred or more phone calls a month. It is therefore only natural for call center managers that it is not in their time to listen to all calls, to discover and decide effectively who of the operators is doing their job well and who is not. At the same time, they need to know whether any of the operators is not starting on a particular day, hour or conversation to deteriorate or improve, what are the connections between the words of the operator and the reaction of customers, etc.
Solution
The development of an automatic solution was preceded by meetings with owners of call centers, team leaders and people from HR, where they deal with customer care and sales. We use third-party technology to recognize emotions by analyzing sound and transcription tools to create automated tools for verifying and controlling call quality. Thanks to this, we are able to detect emotions during a conversation, we know how people react to certain specific words or sentences, whether the operator follows the set scenario, speaks clearly, or even whether he/she understands a specific issue. The information obtained in this way can then be selected in various ways, certain patterns and contexts can be searched in them.
The development of an automatic solution was preceded by meetings with owners of call centers, team leaders and people from HR, where they deal with customer care and sales. We use third-party technology to recognize emotions by analyzing sound and transcription tools to create automated tools for verifying and controlling call quality. Thanks to this, we are able to detect emotions during a conversation, we know how people react to certain specific words or sentences, whether the operator follows the set scenario, speaks clearly, or even whether he/she understands a specific issue. The information obtained in this way can then be selected in various ways, certain patterns and contexts can be searched in them.
Results
Our solution is tailored for clients so that they can define for themselves what they are interested in when checking calls, what they want to know or find out. Our software can therefore test all calls in a certain period of time and highlight the ones that team leaders or call center managers should look at, respectively - to listen to. As a result, they can use the time saved for activities other than listening to calls. Currently, our solution is actively sold in London and further offered to other call centers.
Our solution is tailored for clients so that they can define for themselves what they are interested in when checking calls, what they want to know or find out. Our software can therefore test all calls in a certain period of time and highlight the ones that team leaders or call center managers should look at, respectively - to listen to. As a result, they can use the time saved for activities other than listening to calls. Currently, our solution is actively sold in London and further offered to other call centers.
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