IDEAS home Printed from https://ideas.repec.org/a/jfr/jms111/v5y2014i1p33-38.html
   My bibliography  Save this article

Research Intelligent Precision Marketing of E-commerce Based on the Big Data

Author

Listed:
  • Jianhui Zhang
  • Junxuan Zhu

Abstract

This paper analyzed and summarized the development path of electronic commerce marketing based on the big data; the related aspects of intelligent precision marketing framework has been designed combined with smart technology; and describes its functional structure and operational processes. Taking into account the differences between e-commerce and traditional retail industry; constructed RFMA model combined with characterizes of the electricity suppliers, by means of k-means clustering to achieve the client's "precision" division. Finally, verified the model of marketing by a c2c transaction data, clarify this model could develop precise marketing strategies to deal with the challenges posed by big data has some significance.

Suggested Citation

  • Jianhui Zhang & Junxuan Zhu, 2014. "Research Intelligent Precision Marketing of E-commerce Based on the Big Data," Journal of Management and Strategy, Journal of Management and Strategy, Sciedu Press, vol. 5(1), pages 33-38, February.
    • Handle: RePEc:jfr:jms111:v:5:y:2014:i:1:p:33-38
    as

    Download full text from publisher

    File URL: http://www.sciedu.ca/journal/index.php/jms/article/view/4236/2428
    Download Restriction: no
    File URL: http://www.sciedu.ca/journal/index.php/jms/article/view/4236
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ho, Ying & Chung, Yuho & Lau, Kin-nam, 2010. "Unfolding large-scale marketing data," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 119-132.
    2. Wu, Couchen & Chen, Hsiu-Li, 2000. "Counting your customers: Compounding customer's in-store decisions, interpurchase time and repurchasing behavior," European Journal of Operational Research, Elsevier, vol. 127(1), pages 109-119, November.
    Full references (including those not matched with items on IDEAS)

    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. Jerath, Kinshuk & Fader, Peter S. & Hardie, Bruce G.S., 2016. "Customer-base analysis using repeated cross-sectional summary (RCSS) data," European Journal of Operational Research, Elsevier, vol. 249(1), pages 340-350.
    2. Reutterer, Thomas & Platzer, Michael & Schröder, Nadine, 2021. "Leveraging purchase regularity for predicting customer behavior the easy way," International Journal of Research in Marketing, Elsevier, vol. 38(1), pages 194-215.
    3. Trinh, Giang & Wright, Malcolm J., 2022. "Predicting future consumer purchases in grocery retailing with the condensed Poisson lognormal model," Journal of Retailing and Consumer Services, Elsevier, vol. 64(C).
    4. Tammo H.A. Bijmolt & Michel Wedel & Wayne S. DeSarbo, 2021. "Adaptive Multidimensional Scaling: Brand Positioning Based on Decision Sets and Dissimilarity Judgments," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 8(1), pages 1-15, June.
    5. Pallant, Jason I. & Danaher, Peter J. & Sands, Sean J. & Danaher, Tracey S., 2017. "An empirical analysis of factors that influence retail website visit types," Journal of Retailing and Consumer Services, Elsevier, vol. 39(C), pages 62-70.
    6. Van den Poel, Dirk & Buckinx, Wouter, 2005. "Predicting online-purchasing behaviour," European Journal of Operational Research, Elsevier, vol. 166(2), pages 557-575, October.
    7. Peter S. Fader & Bruce G. S. Hardie & Ka Lok Lee, 2005. "“Counting Your Customers” the Easy Way: An Alternative to the Pareto/NBD Model," Marketing Science, INFORMS, vol. 24(2), pages 275-284, August.
    8. Dawn Iacobucci & Maria Petrescu & Anjala Krishen & Michael Bendixen, 2019. "The state of marketing analytics in research and practice," Journal of Marketing Analytics, Palgrave Macmillan, vol. 7(3), pages 152-181, September.
    9. Nadarajah, Saralees & Kotz, Samuel, 2009. "Models for purchase frequency," European Journal of Operational Research, Elsevier, vol. 192(3), pages 1014-1026, February.
    10. van de Velden, M. & de Beuckelaer, A. & Groenen, P.J.F. & Busing, F.M.T.A., 2011. "Nonmetric Unfolding of Marketing Data: Degeneracy and Stability," ERIM Report Series Research in Management ERS-2011-006-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    11. Meade, Nigel & Islam, Towhidul, 2010. "Using copulas to model repeat purchase behaviour - An exploratory analysis via a case study," European Journal of Operational Research, Elsevier, vol. 200(3), pages 908-917, February.
    12. Sorensen, Herb & Bogomolova, Svetlana & Anderson, Katherine & Trinh, Giang & Sharp, Anne & Kennedy, Rachel & Page, Bill & Wright, Malcolm, 2017. "Fundamental patterns of in-store shopper behavior," Journal of Retailing and Consumer Services, Elsevier, vol. 37(C), pages 182-194.
    13. Buckinx, Wouter & Van den Poel, Dirk, 2005. "Customer base analysis: partial defection of behaviourally loyal clients in a non-contractual FMCG retail setting," European Journal of Operational Research, Elsevier, vol. 164(1), pages 252-268, July.
    14. Trinh, Giang, 2014. "Predicting variation in repertoire size with the NBD model," Australasian marketing journal, Elsevier, vol. 22(2), pages 111-116.
    15. Gázquez-Abad, Juan Carlos & Canniére, Marie Hélène De & Martínez-López, Francisco J., 2011. "Dynamics of Customer Response to Promotional and Relational Direct Mailings from an Apparel Retailer: The Moderating Role of Relationship Strength," Journal of Retailing, Elsevier, vol. 87(2), pages 166-181.
    16. Fader, Peter S. & Hardie, Bruce G. S., 2002. "A note on an integrated model of customer buying behavior," European Journal of Operational Research, Elsevier, vol. 139(3), pages 682-687, June.
    17. Tammo Bijmolt & Michel Velden, 2012. "Multiattribute perceptual mapping with idiosyncratic brand and attribute sets," Marketing Letters, Springer, vol. 23(3), pages 585-601, September.
    18. Korkmaz, E. & Kuik, R. & Fok, D., 2013. ""Counting Your Customers": When will they buy next? An empirical validation of probabilistic customer base analysis models based on purchase timing," ERIM Report Series Research in Management ERS-2013-001-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    19. Fader, Peter S. & Hardie, Bruce G.S., 2009. "Probability Models for Customer-Base Analysis," Journal of Interactive Marketing, Elsevier, vol. 23(1), pages 61-69.

    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:jfr:jms111:v:5:y:2014:i:1:p:33-38. 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: Jenny Zhang (email available below). General contact details of provider: http://jms.sciedupress.com .

    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.