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Designing Email Marketing Campaigns - A Data Mining Approach Based On Consumer Preferences


  • Radu Ioan Mogos

    (‘Bucharest University of Economic Studies‘ Romania)

  • Carmen Acatrinei

    (‘Bucharest University of Economic Studies‘ Romania)


The organizations should approach the consumers by using only the instruments accepted andtrusted by them and if the email is one of the instruments , companies must be able to design emailmarketing communication campaigns that would have a high response rate (either in what concerns theopen rate, click rate and / or conversion rate). By owning a database and by designing email marketingcampaigns, the organizations can send individually, personalized offers. The messages used for writingthe emails should be adapted to the requirements of the target, based on some common characteristicsand / or behaviors. These common characteristics can be found out by analyzing the interaction that thepotential client has with the company’s website, through personal designation of interests andpreferences, by analyzing the buying behavior of the products visualized and the time spent on the websitebefore / after the purchase was made. The present paper presents the results of a research among thefactors that influence the recipients to open direct emails and make an action desired by the company andalso studies whether and what elements in the email would influence them to buy the products / servicespromoted. The results are obtained based on a data mining analysis which includes clustering andclassification processes and offer a guide on how organizations should design their email marketingcommunications in order to have higher response rates.

Suggested Citation

  • Radu Ioan Mogos & Carmen Acatrinei, 2015. "Designing Email Marketing Campaigns - A Data Mining Approach Based On Consumer Preferences," Annales Universitatis Apulensis Series Oeconomica, Faculty of Sciences, "1 Decembrie 1918" University, Alba Iulia, vol. 1(17), pages 1-1.
  • Handle: RePEc:alu:journl:v:1:y:2015:i:17:p:1

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    More about this item


    email marketing campaigns; email customization; data mining analysis; consumer preferences;

    JEL classification:

    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • M37 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Advertising
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis


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