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

Abstract

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Cross-visiting Behaviour of Online Consumers Across Retailers’ and Comparison Sites, a Macro-Study

“…It is associated with the amount of information that is retrieved and evaluated on a website (Klein 1998;Rozic-Hristovski et al 2002). Usage intensity or engagement in an online environment has been previously measured by the duration of visit (Ip and Wagner 2008;Trivedi et al 2018) and number of pages visited (Rozic-Hristovski et al 2002). These measures capture the behaviour of consumers within one specific website and are used in this research.…”

“…It allows them to locate such customers early on and take measures to prevent them from switching. By offering a usage-based customer segmentation (Trivedi et al 2018), the findings help managers better understand the cross-channel behaviour of different segments and design effective targeted strategies for each group, for example, price sensitive switchers. This study examines large-scale observations of consumers' actions, including their entire interactions with different websites.…”

“…This is advantageous because usage data retrieved from system logs is not necessarily correlated with subjective self-reported usage (Albashrawi et al 2019). In addition, measuring the actual behaviour of consumers can create business insights by offering valuable usage-based segmentation (Trivedi et al 2018).…”

Behavior of Users Illustrated using Heavy-Tailed Distribution

“…Users participate in online social services [1] for different purposes. Some become part of these services to engage with other users while others become part of these services to engage with features of this online social service.…”

Big Data & Analytics for Societal Impact: Recent Research and Trends

“…This study investigates various inflows and outflows that can give asset investor in making informed choices about which fund to choose. Trivedi et al (2018) present a methodological framework for engagement-based customer segmentation by using signals from social elements to better understand customer profiles. They show how their approach overcomes the limitation of traditional segmentation approaches by using data from an online emotional support service system, which plays a critical role in health management.…”