Abstract
In this paper, we present our solution for argumentative analysis of call center conversations in order to provide useful insights for enhancing Customer Interaction Analytics to a level that will enable more qualitative metrics and key performance indicators (KPIs) beyond the standard approach used in Customer Interaction Analytics. These metrics rely on understanding the dynamics of conversations by highlighting the way participants discuss about topics. By doing that we can detect relevant situations such as social behaviors, controversial topics, customer oriented behaviors, and also predict customer satisfaction.
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Pallotta, V., Delmonte, R. (2013). Interaction Mining: The New Frontier of Customer Interaction Analytics. In: Lai, C., Semeraro, G., Vargiu, E. (eds) New Challenges in Distributed Information Filtering and Retrieval. Studies in Computational Intelligence, vol 439. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31546-6_6
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DOI: https://doi.org/10.1007/978-3-642-31546-6_6
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