Contextual Segmentation: Using Context to Improve Behavior Predictive Models in E-commerce

Faraone, M. F.; Gorgoglione, Michele; Palmisano, Cosimo

doi:10.1109/icdmw.2010.101

Cited by 4 publications

(2 citation statements)

References 18 publications

(26 reference statements)

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“…Moreover, Jiang and Tuzhilin (2007) proposed a micro targeting approach based on customer groups to build better personalized predictive models of customer behavior. More recently, Faraone et al (2010, 2012) used segment based approach to improve the predictive performance of customer-purchasing behavior in e-commerce domain. Additionally, a recent study, Liu et al (2013) proposed a novel prediction model utilizing customer segments to provide targeted point-of-interest (POI) recommendations.…”

Section: Literature Reviewmentioning

confidence: 99%

A hybrid approach for predicting customers’ individual purchase behavior

Peker

Kocyigit

Eren

2017

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Purpose Predicting customers’ purchase behaviors is a challenging task. The literature has introduced the individual-level and the segment-based predictive modeling approaches for this purpose. Each method has its own advantages and drawbacks, and performs in certain cases. The purpose of this paper is to propose a hybrid approach which predicts customers’ individual purchase behaviors and reduces the limitations of these two methods by combining the advantages of them. Design/methodology/approach The proposed hybrid approach is established based on individual-level and segment-based approaches and utilizes the historical transactional data and predictive algorithms to generate predictions. The effectiveness of the proposed approach is experimentally evaluated in the domain of supermarket shopping by using real-world data and using five popular machine learning classification algorithms including logistic regression, decision trees, support vector machines, neural networks and random forests. Findings A comparison of results shows that the proposed hybrid approach substantially outperforms the individual-level and the segment-based approaches in terms of prediction coverage while maintaining roughly comparable prediction accuracy to the individual-level method. Moreover, the experimental results demonstrate that logistic regression performs better than the other classifiers in predicting customer purchase behavior. Practical implications The study concludes that the proposed approach would be beneficial for enterprises in terms of designing customized services and one-to-one marketing strategies. Originality/value This study is the first attempt to adopt a hybrid approach combining individual-level and segment-based approaches to predict customers’ individual purchase behaviors.

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Section: Literature Reviewmentioning

confidence: 99%

A hybrid approach for predicting customers’ individual purchase behavior

Peker

Kocyigit

Eren

2017

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“…More recent research [29] has proved that by considering the context of a transaction in modelling, the predictive power of customer behaviour, especially individual behaviour, is increased. The authors showed that since each customer may have different behavioural patterns in respect to different contexts, a behavioural segmentation may not be useful if context is not included in the analysis.…”

Section: Research Frameworkmentioning

confidence: 99%

Exploring Media Convergence: Evidence from Italy

Bettiga

Boaretto

Shan

2013

International Journal of Engineering Business Management

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The evolution of media and devices is enabling the ubiquitous and multi-device access to media and information, so that a media mutual contamination is in play. New forms of user interactions with media, in which different devices are used simultaneously in different contexts, have emerged. These new interactions are significantly impacting on users' attitudes towards the media and their way of searching and generating content. Such a change, called “media convergence”, has a strong potential impact on marketing and communication processes, but as yet has not been deeply analysed in the literature. This paper presents the outcomes of several studies aimed at exploring media convergence on the demand-side to advance possible implications for marketers and managers.

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