Keep the conversations going: engagement-based customer segmentation on online social service platforms

Nripesh Trivedi (), Daniel Adomako Asamoah () and Derek Doran ()
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Nripesh Trivedi: Banaras Hindu University
Daniel Adomako Asamoah: Wright State University
Derek Doran: Wright State University

Information Systems Frontiers, 2018, vol. 20, issue 2, No 5, 239-257

Abstract: Abstract Most businesses and organizations develop online services as a value-added offering, which is a significant revenue stream from their existing user base. Such services may be enhanced with social elements to serve as value-added tools for user attraction and retention. Social elements may allow users to post content, share information and directly interact with each other. Investments in these social features are for naught if they do not encourage users to engage on the platform effectively. However, common ways to segment customers by their engagement is hindered by the statistical nature of behavioral data based on social elements. To address this important concern, this paper presents a methodological framework for engagement-based customer segmentation able to appropriately consider signals from social elements. It argues why the traditional approaches for user segmentation is ill-suited and advocates for the integration of kernel functions with clustering to segment, identify and understand user engagement profiles. The framework is demonstrated with real data from a large, very active OSS.

Keywords: Analytics; Online social services; Engagement analysis; Kernel k-means; Clustering; Big data (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (10)

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DOI: 10.1007/s10796-016-9719-x

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