IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v88y2018icp407-414.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148296317304939
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jbusres.2017.11.047?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Baoliang Hu & Wei Huang & Shuai Yan & Guang Liu & Tao Zhang, 2020. "Business Model Design and Customer Loyalty: The Mediating Role of Customer Citizenship Behavior," Sustainability, MDPI, vol. 12(17), pages 1-14, August.
    2. Ballestar, María Teresa & Díaz-Chao, Ángel & Sainz, Jorge & Torrent-Sellens, Joan, 2021. "Impact of robotics on manufacturing: A longitudinal machine learning perspective," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    3. Ballestar, María Teresa & Mir, Miguel Cuerdo & Pedrera, Luis Miguel Doncel & Sainz, Jorge, 2024. "Effectiveness of tutoring at school: A machine learning evaluation," Technological Forecasting and Social Change, Elsevier, vol. 199(C).
    4. Tueanrat, Yanika & Papagiannidis, Savvas & Alamanos, Eleftherios, 2021. "Going on a journey: A review of the customer journey literature," Journal of Business Research, Elsevier, vol. 125(C), pages 336-353.
    5. Tueanrat, Yanika & Papagiannidis, Savvas & Alamanos, Eleftherios, 2021. "A conceptual framework of the antecedents of customer journey satisfaction in omnichannel retailing," Journal of Retailing and Consumer Services, Elsevier, vol. 61(C).
    6. Afonso Vieira, Valter & Agnihotri, Raj & de Almeida, Marcos Inácio Severo & Lopes, Evandro Luiz, 2022. "How cashback strategies yield financial benefits for retailers: The mediating role of consumers’ program loyalty," Journal of Business Research, Elsevier, vol. 141(C), pages 200-212.
    7. Griva, Anastasia, 2022. "“I can get no e-satisfaction†. What analytics say? Evidence using satisfaction data from e-commerce," Journal of Retailing and Consumer Services, Elsevier, vol. 66(C).
    8. Xu, Lina & Roy, Abhijit, 2022. "Cashback as cash forward: The serial mediating effect of time/effort and money savings," Journal of Business Research, Elsevier, vol. 149(C), pages 30-37.
    9. 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.
    10. Ata Allah Taleizadeh & Alireza Mahmoudzade Varzi & Hadi Akbarzadeh Khorshidi & Mahsa Noori-daryan, 2024. "Retail pricing, cashback and refund decisions in a supply chain with e-shop and direct channels," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 23(2), pages 140-163, April.
    11. Kokkoris, Michail D. & Hoelzl, Erik & Kamleitner, Bernadette, 2020. "Self-found, spellbound: The sense of own discovery shapes customer bonds with service venues," Journal of Business Research, Elsevier, vol. 113(C), pages 303-316.
    12. Olha Fedirko & Tetiana Zatonatska & Tomasz Wolowiec & Stanislaw Skowron, 2021. "Data Science and Marketing in E-Commerce Amid COVID-19 Pandemic," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 2), pages 3-16.
    13. Farid Huseynov & Sevgi Özkan Yıldırım, 2019. "Online Consumer Typologies and Their Shopping Behaviors in B2C E-Commerce Platforms," SAGE Open, , vol. 9(2), pages 21582440198, May.
    14. Ballestar, María Teresa & García-Lazaro, Aida & Sainz, Jorge & Sanz, Ismael, 2022. "Why is your company not robotic? The technology and human capital needed by firms to become robotic," Journal of Business Research, Elsevier, vol. 142(C), pages 328-343.
    15. Zuzana Svobodová & Jaroslava Rajchlová, 2020. "Strategic Behavior of E-Commerce Businesses in Online Industry of Electronics from a Customer Perspective," Administrative Sciences, MDPI, vol. 10(4), pages 1-24, October.
    16. Ballestar, María Teresa & Doncel, Luis Miguel & Sainz, Jorge & Ortigosa-Blanch, Arturo, 2019. "A novel machine learning approach for evaluation of public policies: An application in relation to the performance of university researchers," Technological Forecasting and Social Change, Elsevier, vol. 149(C).
    17. 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.
    18. Joni Salminen & Mekhail Mustak & Muhammad Sufyan & Bernard J. Jansen, 2023. "How can algorithms help in segmenting users and customers? A systematic review and research agenda for algorithmic customer segmentation," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(4), pages 677-692, December.
    19. Lewlisa Saha & Hrudaya Kumar Tripathy & Soumya Ranjan Nayak & Akash Kumar Bhoi & Paolo Barsocchi, 2021. "Amalgamation of Customer Relationship Management and Data Analytics in Different Business Sectors—A Systematic Literature Review," Sustainability, MDPI, vol. 13(9), pages 1-35, May.
    20. Halpern, Nigel & Mwesiumo, Deodat & Budd, Thomas & Suau-Sanchez, Pere & Bråthen, Svein, 2021. "Segmentation of passenger preferences for using digital technologies at airports in Norway," Journal of Air Transport Management, Elsevier, vol. 91(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shan Huang & Sinan Aral & Yu Jeffrey Hu & Erik Brynjolfsson, 2020. "Social Advertising Effectiveness Across Products: A Large-Scale Field Experiment," Marketing Science, INFORMS, vol. 39(6), pages 1142-1165, November.
    2. Wang, Le & Luo, Xin (Robert) & Li, Han, 2022. "Envy or conformity? An empirical investigation of peer influence on the purchase of non-functional items in mobile free-to-play games," Journal of Business Research, Elsevier, vol. 147(C), pages 308-324.
    3. Haris Krijestorac & Rajiv Garg & Vijay Mahajan, 2020. "Cross-Platform Spillover Effects in Consumption of Viral Content: A Quasi-Experimental Analysis Using Synthetic Controls," Information Systems Research, INFORMS, vol. 31(2), pages 449-472, June.
    4. Miguel Godinho de Matos & Pedro Ferreira & Michael D. Smith & Rahul Telang, 2016. "Culling the Herd: Using Real-World Randomized Experiments to Measure Social Bias with Known Costly Goods," Management Science, INFORMS, vol. 62(9), pages 2563-2580, September.
    5. Sarah Gelper & Ralf van der Lans & Gerrit van Bruggen, 2021. "Competition for Attention in Online Social Networks: Implications for Seeding Strategies," Management Science, INFORMS, vol. 67(2), pages 1026-1047, February.
    6. Albert Chukwunonso Diachi & Ayşe Tansu & Oseyenbhin Sunday Osemeahon, 2021. "No One Is Leaving This Time: Social Media Fashion Brand Communities," Sustainability, MDPI, vol. 13(23), pages 1-14, November.
    7. Horton, John J. & Zeckhauser, Richard J., 2016. "The Causes of Peer Effects in Production: Evidence from a Series of Field Experiments," Working Paper Series 16-027, Harvard University, John F. Kennedy School of Government.
    8. Kexin Zhao & Bin Zhang & Xue Bai, 2018. "Estimating Contextual Motivating Factors in Virtual Interorganizational Communities of Practice: Peer Effects and Organizational Influences," Information Systems Research, INFORMS, vol. 29(4), pages 910-927, December.
    9. Bireswar Dutta & Mei-Hui Peng & Chien-Chih Chen & Shu-Lung Sun, 2021. "Interpreting Usability Factors Predicting Sustainable Adoption of Cloud-Based E-Learning Environment during COVID-19 Pandemic," Sustainability, MDPI, vol. 13(16), pages 1-22, August.
    10. Sinan Aral & Chrysanthos Dellarocas & David Godes, 2013. "Introduction to the Special Issue ---Social Media and Business Transformation: A Framework for Research," Information Systems Research, INFORMS, vol. 24(1), pages 3-13, March.
    11. Johannes Loh, 2022. "Selection, Consumption, and New Music Exploration in an Online Social Network: A Dyadic Approach," CESifo Working Paper Series 10120, CESifo.
    12. Sinan Aral & Erik Brynjolfsson & Marshall Van Alstyne, 2012. "Information, Technology, and Information Worker Productivity," Information Systems Research, INFORMS, vol. 23(3-part-2), pages 849-867, September.
    13. Tianshu Sun & Sean J. Taylor, 2020. "Displaying things in common to encourage friendship formation: A large randomized field experiment," Quantitative Marketing and Economics (QME), Springer, vol. 18(3), pages 237-271, September.
    14. Ravi Bapna & Jui Ramaprasad & Galit Shmueli & Akhmed Umyarov, 2016. "One-Way Mirrors in Online Dating: A Randomized Field Experiment," Management Science, INFORMS, vol. 62(11), pages 3100-3122, November.
    15. Jaehwuen Jung & Ravi Bapna & Joseph M. Golden & Tianshu Sun, 2020. "Words Matter! Toward a Prosocial Call-to-Action for Online Referral: Evidence from Two Field Experiments," Information Systems Research, INFORMS, vol. 31(1), pages 16-36, March.
    16. Locander, Jennifer A. & White, Allyn & Newman, Christopher L., 2020. "Customer responses to frontline employee complaining in retail service environments: The role of perceived impropriety," Journal of Business Research, Elsevier, vol. 107(C), pages 315-323.
    17. Zhihong Ke & De Liu & Daniel J. Brass, 2020. "Do Online Friends Bring Out the Best in Us? The Effect of Friend Contributions on Online Review Provision," Information Systems Research, INFORMS, vol. 31(4), pages 1322-1336, December.
    18. Mithila Guha & Daniel Korschun, 2024. "Peer effects on brand activism: evidence from brand and user chatter on Twitter," Journal of Brand Management, Palgrave Macmillan, vol. 31(2), pages 153-167, March.
    19. 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.
    20. Tianshu Sun & Guodong (Gordon) Gao & Ginger Zhe Jin, 2019. "Mobile Messaging for Offline Group Formation in Prosocial Activities: A Large Field Experiment," Management Science, INFORMS, vol. 67(6), pages 2717-2736, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jbrese:v:88:y:2018:i:c:p:407-414. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jbusres .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.