IDEAS home Printed from https://ideas.repec.org/a/eee/joreco/v63y2021ics0969698921002162.html
   My bibliography  Save this article

The provenance of loyalty card data for urban and retail analytics

Author

Listed:
  • Rains, Tim
  • Longley, Paul

Abstract

The deployment of loyalty card and other consumer data in geographic research brings opportunities to explore and understand patterns of purchasing behaviour in unprecedented detail. However, valid generalisation requires thorough evaluation of their potential bias. We argue that, in competitive markets where consumers can choose to shop across competing retailers, loyalty card data from just one of these may not represent a ‘complete’ view of all purchases, and that this ‘completeness’ must be controlled for when assessing bias. To this end, we undertake a UK wide analysis of loyalty card data assembled by a major UK grocery retailer and provide guidelines for their effective deployment in the domains of urban and retail analysis. We assess, for the first time, the ‘completeness’ of circa 500 million customer transactions recorded by a major customer loyalty programme in representing the overall purchasing patterns of circa 16 million consumers across the entire UK, and develop a method by which to do this. Moreover, no operator has complete national store coverage, and so we suggest ways of accommodating this when conducting analysis using loyalty card data. We illustrate the importance of these issues before providing recommendations for the wider use of consumer loyalty card data.

Suggested Citation

  • Rains, Tim & Longley, Paul, 2021. "The provenance of loyalty card data for urban and retail analytics," Journal of Retailing and Consumer Services, Elsevier, vol. 63(C).
    • Handle: RePEc:eee:joreco:v:63:y:2021:i:c:s0969698921002162
    DOI: 10.1016/j.jretconser.2021.102650
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0969698921002162
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jretconser.2021.102650?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. Neil Wrigley & Steve Wood & Dionysia Lambiri & Michelle Lowe, 2019. "Corporate convenience store development effects in small towns: Convenience culture during economic and digital storms," Environment and Planning A, , vol. 51(1), pages 112-132, February.
    2. Cortiñas, Mónica & Elorz, Margarita & Múgica, José Miguel, 2008. "The use of loyalty-cards databases: Differences in regular price and discount sensitivity in the brand choice decision between card and non-card holders," Journal of Retailing and Consumer Services, Elsevier, vol. 15(1), pages 52-62.
    3. Bradlow, Eric T. & Gangwar, Manish & Kopalle, Praveen & Voleti, Sudhir, 2017. "The Role of Big Data and Predictive Analytics in Retailing," Journal of Retailing, Elsevier, vol. 93(1), pages 79-95.
    4. David Martin & Samantha Cockings & Samuel Leung, 2015. "Developing a Flexible Framework for Spatiotemporal Population Modeling," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 105(4), pages 754-772, July.
    5. Ho, Hillbun & Tien, Keng-Ming (Terence) & Wu, Anne & Singh, Sonika, 2021. "A sequence analysis approach to segmenting credit card customers," Journal of Retailing and Consumer Services, Elsevier, vol. 59(C).
    6. Melis, Kristina & Campo, Katia & Lamey, Lien & Breugelmans, Els, 2016. "A Bigger Slice of the Multichannel Grocery Pie: When Does Consumers’ Online Channel Use Expand Retailers’ Share of Wallet?," Journal of Retailing, Elsevier, vol. 92(3), pages 268-286.
    7. Birkin, Mark, 2019. "Spatial data analytics of mobility with consumer data," Journal of Transport Geography, Elsevier, vol. 76(C), pages 245-253.
    8. Park, Chang Hee & Park, Young-Hoon & Schweidel, David A., 2014. "A multi-category customer base analysis," International Journal of Research in Marketing, Elsevier, vol. 31(3), pages 266-279.
    9. Frasquet, Marta & Ieva, Marco & Ziliani, Cristina, 2021. "Online channel adoption in supermarket retailing," Journal of Retailing and Consumer Services, Elsevier, vol. 59(C).
    10. Treadgold, Alan & Reynolds, Jonathan, 2016. "Navigating the New Retail Landscape: A Guide for Business Leaders," OUP Catalogue, Oxford University Press, number 9780198745754.
    11. Felgate, Melanie & Fearne, Andrew, 2012. "Using Supermarket Loyalty Card Data to Inform Better Promotional Strategies," 2012 International European Forum, February 13-17, 2012, Innsbruck-Igls, Austria 144966, International European Forum on System Dynamics and Innovation in Food Networks.
    12. Gijsbrechts, Els & Campo, Katia & Nisol, Patricia, 2008. "Beyond promotion-based store switching: Antecedents and patterns of systematic multiple-store shopping," International Journal of Research in Marketing, Elsevier, vol. 25(1), pages 5-21.
    13. Sarantopoulos, Panagiotis & Theotokis, Aristeidis & Pramatari, Katerina & Doukidis, Georgios, 2016. "Shopping missions: An analytical method for the identification of shopper need states," Journal of Business Research, Elsevier, vol. 69(3), pages 1043-1052.
    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. Formánek, Tomáš & Sokol, Ondřej, 2022. "Location effects: Geo-spatial and socio-demographic determinants of sales dynamics in brick-and-mortar retail stores," Journal of Retailing and Consumer Services, Elsevier, vol. 66(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. Anastasia Griva & Cleopatra Bardaki & Katerina Pramatari & Georgios Doukidis, 2022. "Factors Affecting Customer Analytics: Evidence from Three Retail Cases," Information Systems Frontiers, Springer, vol. 24(2), pages 493-516, April.
    2. van Heerde, Harald J. & Dinner, Isaac M. & Neslin, Scott A., 2019. "Engaging the unengaged customer: The value of a retailer mobile app," International Journal of Research in Marketing, Elsevier, vol. 36(3), pages 420-438.
    3. Pramono, Ari & Oppewal, Harmen, 2021. "Where to refuel: Modeling on-the-way choice of convenience outlet," Journal of Retailing and Consumer Services, Elsevier, vol. 61(C).
    4. Els Breugelmans & Marleen Hermans & Manfred Krafft & Mirja Kroschke & Felix Lehmkuhle & Murali Mantrala, 2024. "What is happening to my nearby stores? The own- and cross-effect of a radical store transformation on existing customers," Journal of the Academy of Marketing Science, Springer, vol. 52(1), pages 217-238, January.
    5. Malik, Sheraz Alam & Hingley, Martin K., 2021. "Consumer demand information as a re-balancing tool for power asymmetry between food retailers and suppliers," Economia agro-alimentare / Food Economy, Italian Society of Agri-food Economics/Società Italiana di Economia Agro-Alimentare (SIEA), vol. 23(2), July.
    6. Neslin, Scott A., 2022. "The omnichannel continuum: Integrating online and offline channels along the customer journey," Journal of Retailing, Elsevier, vol. 98(1), pages 111-132.
    7. Chen, Yanhong & Liu, Luning & Zheng, Dequan & Li, Bin, 2023. "Estimating travellers’ value when purchasing auxiliary services in the airline industry based on the RFM model," Journal of Retailing and Consumer Services, Elsevier, vol. 74(C).
    8. Chen, Yanyan & Mandler, Timo & Meyer-Waarden, Lars, 2021. "Three decades of research on loyalty programs: A literature review and future research agenda," Journal of Business Research, Elsevier, vol. 124(C), pages 179-197.
    9. Van Droogenbroeck, Ellen & Van Hove, Leo, 2020. "Intra-household task allocation in online grocery shopping: Together alone," Journal of Retailing and Consumer Services, Elsevier, vol. 56(C).
    10. Namin, Aidin & Soysal, Gonca P. & Ratchford, Brian T., 2022. "Alleviating demand uncertainty for seasonal goods: An analysis of attribute-based markdown policy for fashion retailers," Journal of Business Research, Elsevier, vol. 145(C), pages 671-681.
    11. Melis, Kristina & Campo, Katia & Lamey, Lien & Breugelmans, Els, 2016. "A Bigger Slice of the Multichannel Grocery Pie: When Does Consumers’ Online Channel Use Expand Retailers’ Share of Wallet?," Journal of Retailing, Elsevier, vol. 92(3), pages 268-286.
    12. Bogomolova, Svetlana & Dunn, Steven & Trinh, Giang & Taylor, Jennifer & Volpe, Richard J., 2015. "Price promotion landscape in the US and UK: Depicting retail practice to inform future research agenda," Journal of Retailing and Consumer Services, Elsevier, vol. 25(C), pages 1-11.
    13. Ionut Anica-Popa & Liana Anica-Popa & Cristina Radulescu & Marinela Vrincianu, 2021. "The Integration of Artificial Intelligence in Retail: Benefits, Challenges and a Dedicated Conceptual Framework," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 23(56), pages 120-120, February.
    14. Ron Berman & Ayelet Israeli, 2022. "The Value of Descriptive Analytics: Evidence from Online Retailers," Marketing Science, INFORMS, vol. 41(6), pages 1074-1096, November.
    15. Christiane Lehrer & Manuel Trenz, 2022. "Omnichannel Business," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(2), pages 687-699, June.
    16. Wieland, Thomas, 2015. "Nahversorgung im Kontext raumökonomischer Entwicklungen im Lebensmitteleinzelhandel: Konzeption und Durchführung einer GIS-gestützten Analyse der Strukturen des Lebensmitteleinzelhandels und der Nahve," MPRA Paper 77145, University Library of Munich, Germany.
    17. Kim, Chul & Jun, Duk Bin & Park, Sungho, 2018. "Capturing flexible correlations in multiple-discrete choice outcomes using copulas," International Journal of Research in Marketing, Elsevier, vol. 35(1), pages 34-59.
    18. Guyt, Jonne & Gijsbrechts, Els, 2018. "On consumer choice patterns and the net impact of feature promotions," International Journal of Research in Marketing, Elsevier, vol. 35(3), pages 490-508.
    19. Agrawal, Shiv Ratan & Mittal, Divya, 2022. "Optimizing customer engagement content strategy in retail and E-tail: Available on online product review videos," Journal of Retailing and Consumer Services, Elsevier, vol. 67(C).
    20. Gautier Daras & Bruno Agard & Bernard Penz, 2019. "Conceptual Framework for SDSS Development with an Application in the Retail Industry," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(3), pages 357-373, 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:joreco:v:63:y:2021:i:c:s0969698921002162. 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: https://www.journals.elsevier.com/journal-of-retailing-and-consumer-services .

    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.