Recommendation System to Optimize Email Marketing Campaign Using Apriori Algorithm Case Study: Webeli.Com

  • Authors

    • Ratih Widayanti Kosaman
    • Djoko Harsono
    • Ibnu Hadi Sumitro
    2018-11-26
    https://doi.org/10.14419/ijet.v7i4.29.21698
  • Email Marketing, Product Promotion, Recommendation Systems, Apriori Algorithm, Association Rules

  • Abstract

    Email marketing campaign has uniqueness in customer personalization, ability to raise the conversion rate of a website, and a high click-through rate. Unfortunately, email marketing campaign cannot always provide relevant contents for customers. To solve this problem, Webeli.com build recommendation system to find out what products are liked by the customers. The purpose of this research is using association rules technique to optimize email marketing campaign and to influence customers into purchasing particular products that relevant to their interest. The algorithm that used to analyze the association rules among products that purchased together by the customers in one shopping cart is apriori algorithm. This research produces a system that can provide product recommendations that relevant with customers’ interest and can optimize email marketing campaign by increasing efficiency number of the email recipient, duration of delivery email, and cost of delivery email.

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  • How to Cite

    Kosaman, R. W., Harsono, D., & Sumitro, I. H. (2018). Recommendation System to Optimize Email Marketing Campaign Using Apriori Algorithm Case Study: Webeli.Com. International Journal of Engineering & Technology, 7(4.29), 115-121. https://doi.org/10.14419/ijet.v7i4.29.21698

    Received date: 2018-11-26

    Accepted date: 2018-11-26

    Published date: 2018-11-26