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Customer Churn Prediction in B2B Contexts
Corporate Technology, Siemens AG, 81739, Munich, Germany.
Corporate Technology, Siemens AG, 81739, Munich, Germany.
Department of Computer Science and Engineering, Chalmers University of Technology, Hörselgången 11, 412 96, Göteborg, Sweden.
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).ORCID iD: 0000-0002-7700-1816
2019 (English)In: Software Business: 10th International Conference, ICSOB 2019, Jyväskylä, Finland, November 18–20, 2019, Proceedings / [ed] Sami Hyrynsalmi, Mari Suoranta, Anh Nguyen-Duc, Pasi Tyrväinen, Pekka Abrahamsson, Springer, 2019, p. 378-386Conference paper, Published paper (Refereed)
Abstract [en]

While business-to-customer (B2C) companies, in the telecom sector for instance, have been making use of customer churn prediction for many years, churn prediction in the business-to-business (B2B) domain receives much less attention in existing literature. Nevertheless, B2B-specific characteristics, such as a lower number of customers with much higher transactional values, indicate the importance of identifying potentially churning customers. To achieve this, we implemented a prediction model for customer churn within a B2B software product and derived a model based on the results. For one, we present an approach that enables the mapping of customer- and end-user-data based on “customer phases” which allows the prediction model to take all critical influencing factors into consideration. In addition to that, we introduce a B2B customer churn prediction process based on the proposed data mapping.

Place, publisher, year, edition, pages
Springer, 2019. p. 378-386
Series
Lecture Notes in Business Information Processing, ISSN 1865-1348, E-ISSN 1865-1356 ; 370
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:mau:diva-64418DOI: 10.1007/978-3-030-33742-1_30ISI: 000611525900030Scopus ID: 2-s2.0-85076177008ISBN: 978-3-030-33741-4 (print)ISBN: 978-3-030-33742-1 (electronic)OAI: oai:DiVA.org:mau-64418DiVA, id: diva2:1819476
Conference
10th International Conference, ICSOB 2019, Jyväskylä, Finland, November 18–20, 2019
Available from: 2023-12-14 Created: 2023-12-14 Last updated: 2023-12-14Bibliographically approved

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Olsson, Helena Holmström

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