고객만족, NPS, Bayesian Inference 및 Hidden Markov Model로 구현하는 명품구매에 관한확률적 추적 메카니즘 = A Probabilistic Tracking Mechanism for Luxury Purchase Implemented by Hidden Markov Model, Bayesian Inference, Customer Satisfaction and Net Promoter Score

다국어 초록 (Multilingual Abstract)

The purpose of this study is to specify a probabilistic tracking mechanism for customer luxury purchase implemented by hidden Markov model, Bayesian inference, customer satisfaction and net promoter score. In this paper, we have designed a probabilistic model based on customer's actual data containing purchase or non-purchase states by tracking the SPC chain : customer satisfaction -> customer referral -> purchase/non-purchase. By applying hidden Markov model and Viterbi algorithm to marketing theory, we have developed the statistical model related to probability theories and have found the best purchase pattern scenario from customer's purchase records.

참고문헌 (Reference)

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