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Customer-Focused Churn Prevention with Social CRM at Orange Polska SA (Research in Progress)

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Business Information Systems Workshops (BIS 2020)

Abstract

This article presents research in progress on customer-focused churn prevention. The research aims at providing a customer-centric methodology for churn prevention based on customer social data (social CRM), as a significant complement to an approach based on customer data derived from their calling activities (e.g. discovering calling patterns) from Orange systems (like CRM). In scope of the presented research a customer churn tendency is intended to be inferred as knowledge from customers’ messages posted on a company portal (such as Orange one) thanks to discovering customer’s emotions, opinions and sentiment of customers’ messages. As a result of the present stage of research works a literature review was provided, as well as a first conceptual model derived from the review in order to underpin a role of social CRM for churn prediction. A research agenda was also elaborated. This article provides an attempt of presenting a concept of a measure of customer churn tendency based on a customer experience, in particular customer satisfaction. This particular work considers a business case for a telecom industry, as an example of an industry for which reducing customer churn is one of the fundamental requirements. It is a work in progress concerned on analysing data from a social media channel related to one of the telecom companies (Orange) aiming at discovering signals hidden in textual messages, which can be signs of a potential churn.

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Notes

  1. 1.

    http://clarin-pl.eu/en/.

  2. 2.

    http://zil.ipipan.waw.pl/.

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Acknowledgement

This research is supported by Orange Polska SA.

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Correspondence to Ewelina Szczekocka .

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Szczekocka, E. (2020). Customer-Focused Churn Prevention with Social CRM at Orange Polska SA (Research in Progress). In: Abramowicz, W., Klein, G. (eds) Business Information Systems Workshops. BIS 2020. Lecture Notes in Business Information Processing, vol 394. Springer, Cham. https://doi.org/10.1007/978-3-030-61146-0_18

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  • DOI: https://doi.org/10.1007/978-3-030-61146-0_18

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