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RFMTC行銷模式之理論解析

Theoretical Approach of RFMTC Marketing Model

摘要


本研究將RFM模式加以擴充,加入了二個變數:T(Time)表示顧客距第一次購買的時間、C(Churn)表示顧客每歷經一次行銷後流失的機率,再利用機率理論中的Bernoulli序列,導出可以預測顧客購買次數的期望值、顧客終生回應次數期望值、顧客行銷價值、顧客終身價值的模型。本研究也提出估計模型參數的方法,並以一個實際個案進行實證研究。研究結果顯示,本研究所導出的理論模型可以準確預測顧客未來購買次數的期望值。

並列摘要


This study expanded the RFM model by including two parameters, time since first purchase (T) and churn probability (C). Using Bernoulli sequence in probability theory, this study derived out the model that can predict the expected value of the number of times that the customer will buy in the future, customer's marketing value at the next campaign, and customer lifetime value. This study also proposed the methodology to estimate the unknown parameters, such as churn probability, in the formulas, and examined a real case to verify the model. The findings showed that the model can accurately predict the expected value of the number of times that the customer will buy in the future.

並列關鍵字

FM model customer churn Life Time Value marketing probability

參考文獻


楊清潭(2003)。應用資料探勘技術於顧客價值分析之研究(碩士論文)。東吳大學商學院資訊科學系。
蘇柏全、林熙禎、李宙奇(2006)。RFM模型結合貝氏隨機模式與時間序列模式運用於顧客狀態預測。電子商務學報。8(2),193-217。
邱宏彬、蘇建源(2004)。一個可彈性支援顧客關係管理與資料庫行銷之模糊RFM Model。電子商務學報。6(2),149-173。
Berger, P. D.,Nasr, N. I.(1998).Customer lifetime value: Marketing models and applications.Journal of Interactive Marketing.12(1),17-30.
Bult, J. R.,Wansbeek, T.(1995).Optimal selection for direct mail.Marketing Science.14(4),378-381.

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