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Customer segmentation in e-commerce: Applications to the cashback business model

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  • Ballestar, María Teresa
  • Grau-Carles, Pilar
  • Sainz, Jorge

Abstract

This paper presents a segmentation of cashback website customers. The segmentation is based on customers' commercial activity and role within the site's social network. In this social network, customers profit from the transactions they make on affiliate websites. Mixing traditional marketing strategies with word-of-mouth recommendations is crucial for the success of this business model because these recommendations boost new customer acquisitions and strengthen the loyalty of existing customers. This study shows how the customer's role within the cashback website's social network determines the customer's behavior and commercial activity on the website. The segmentation presented describes the customer journey in terms of customer profitability and seniority. The findings explain customer behavior in e-commerce and the value of applying personalized retention strategies to each cluster rather than generic strategies or customer acquisition strategies. This paper describes how customers move between clusters, enabling practitioners to increase customer loyalty and long-term profitability.

Suggested Citation

  • Ballestar, María Teresa & Grau-Carles, Pilar & Sainz, Jorge, 2018. "Customer segmentation in e-commerce: Applications to the cashback business model," Journal of Business Research, Elsevier, vol. 88(C), pages 407-414.
    • Handle: RePEc:eee:jbrese:v:88:y:2018:i:c:p:407-414
    DOI: 10.1016/j.jbusres.2017.11.047
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    References listed on IDEAS

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    1. Rapp, Adam & Trainor, Kevin J. & Agnihotri, Raj, 2010. "Performance implications of customer-linking capabilities: Examining the complementary role of customer orientation and CRM technology," Journal of Business Research, Elsevier, vol. 63(11), pages 1229-1236, November.
    2. Ravi Bapna & Akhmed Umyarov, 2015. "Do Your Online Friends Make You Pay? A Randomized Field Experiment on Peer Influence in Online Social Networks," Management Science, INFORMS, vol. 61(8), pages 1902-1920, August.
    3. Sinan Aral & Dylan Walker, 2011. "Creating Social Contagion Through Viral Product Design: A Randomized Trial of Peer Influence in Networks," Management Science, INFORMS, vol. 57(9), pages 1623-1639, February.
    4. Voorhees, Clay M. & Fombelle, Paul W. & Gregoire, Yany & Bone, Sterling & Gustafsson, Anders & Sousa, Rui & Walkowiak, Travis, 2017. "Service encounters, experiences and the customer journey: Defining the field and a call to expand our lens," Journal of Business Research, Elsevier, vol. 79(C), pages 269-280.
    5. Ananda Das Gupta, 2014. "Social Impact Management," India Studies in Business and Economics, in: Business Ethics, edition 127, chapter 0, pages 189-195, Springer.
    6. Joseph F. Hair & G. Tomas M. Hult & Christian M. Ringle & Marko Sarstedt & Kai Oliver Thiele, 2017. "Mirror, mirror on the wall: a comparative evaluation of composite-based structural equation modeling methods," Journal of the Academy of Marketing Science, Springer, vol. 45(5), pages 616-632, September.
    7. Sinan Aral, 2011. "Commentary--Identifying Social Influence: A Comment on Opinion Leadership and Social Contagion in New Product Diffusion," Marketing Science, INFORMS, vol. 30(2), pages 217-223, 03-04.
    8. Ballestar, María Teresa & Grau-Carles, Pilar & Sainz, Jorge, 2016. "Consumer behavior on cashback websites: Network strategies," Journal of Business Research, Elsevier, vol. 69(6), pages 2101-2107.
    9. Monaghan, Sinéad & Lavelle, Jonathan & Gunnigle, Patrick, 2017. "Mapping networks: Exploring the utility of social network analysis in management research and practice," Journal of Business Research, Elsevier, vol. 76(C), pages 136-144.
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    8. Fatma M. Talaat & Abdussalam Aljadani & Bshair Alharthi & Mohammed A. Farsi & Mahmoud Badawy & Mostafa Elhosseini, 2023. "A Mathematical Model for Customer Segmentation Leveraging Deep Learning, Explainable AI, and RFM Analysis in Targeted Marketing," Mathematics, MDPI, vol. 11(18), pages 1-26, September.
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    15. Kessara Kanchanapoom & Jongsawas Chongwatpol, 2023. "Integrated customer lifetime value (CLV) and customer migration model to improve customer segmentation," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(2), pages 172-185, June.
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