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


  • Radu Ioan MogoÛ
  • Carmen Acatrinei


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

Suggested Citation

  • Radu Ioan MogoÛ & 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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