Payment platforms have significantly evolved in recent years to keep pace with the proliferation of online and cashless payments. These platforms are increasingly aligned with online social networks, allowing users to interact with each other and transfer small amounts of money in a Peer-to-Peer fashion. This poses new challenges for analysing payment data, as traditional methods are only user-centric or business-centric and neglect the network users build during the interaction. This paper proposes a first methodology for measuring user value in modern payment platforms. We combine quantitative user-centric metrics with an analysis of the graph created by users’ activities and its topological features inspired by the evolution of opinions in social networks. We showcase our approach using a dataset from a large operational payment platform and show how it can support business decisions and marketing campaign design, e.g., by targeting specific users.

User Value in Modern Payment Platforms: A Graph Approach / Arditti, Laura; Trevisan, Martino; Vassio, Luca; Lazzari, Alberto De; Danese, Alberto. - STAMPA. - (2022), pp. 71-78. (Intervento presentato al convegno 2022 IEEE International Conference on Data Mining Workshops (ICDMW) tenutosi a Orlando, Florida nel 28 November - 1 December 2022) [10.1109/ICDMW58026.2022.00018].

User Value in Modern Payment Platforms: A Graph Approach

Arditti, Laura;Trevisan, Martino;Vassio, Luca;
2022

Abstract

Payment platforms have significantly evolved in recent years to keep pace with the proliferation of online and cashless payments. These platforms are increasingly aligned with online social networks, allowing users to interact with each other and transfer small amounts of money in a Peer-to-Peer fashion. This poses new challenges for analysing payment data, as traditional methods are only user-centric or business-centric and neglect the network users build during the interaction. This paper proposes a first methodology for measuring user value in modern payment platforms. We combine quantitative user-centric metrics with an analysis of the graph created by users’ activities and its topological features inspired by the evolution of opinions in social networks. We showcase our approach using a dataset from a large operational payment platform and show how it can support business decisions and marketing campaign design, e.g., by targeting specific users.
2022
979-8-3503-4609-1
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2976472