LTV Prediction Based on RFM and Customer Characteristics

DOI

Bibliographic Information

Other Title
  • RFM指標と顧客特性に基づくLTV予測モデル

Description

<p>Lifetime Value (LTV) as we know it, is an important indicator of customer evaluation. To build long-term relationships with the right customer, it is important to predict LTV with increasingly higher accuracy levels. Once we attain that, we would be able to communicate with them through appropriate marketing actions. While predicting LTV in a non-contractual setting, three indicators, namely; Recency, Frequency and Monetary Value (RFM) are widely used. RFM is used as an indicator of customers’ buying behaviour on the whole, however normally dimensions like demographics are not considered. In this paper, we propose a model for predicting LTV based not just on RFM, but also other customer characteristics. To support our proposal and its effectiveness we have also provided the details of the experiments, their outputs and our inference using a real dataset.</p>

Journal

Keywords

Details 詳細情報について

  • CRID
    1390845713074331904
  • NII Article ID
    130007658562
  • DOI
    10.11517/pjsai.jsai2019.0_2q1j202
  • ISSN
    27587347
  • Text Lang
    ja
  • Data Source
    • JaLC
    • CiNii Articles
  • Abstract License Flag
    Disallowed

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