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Counting Your Customers One by One: A Hierarchical Bayes Extension to the Pareto/NBD Model
http://hdl.handle.net/2261/18417
http://hdl.handle.net/2261/18417b2510f79-5bcf-47c7-906f-b4ad99391dd1
| アイテムタイプ | テクニカルレポート / Technical Report(1) | |||||
|---|---|---|---|---|---|---|
| 公開日 | 2013-05-31 | |||||
| タイトル | ||||||
| タイトル | Counting Your Customers One by One: A Hierarchical Bayes Extension to the Pareto/NBD Model | |||||
| 言語 | ||||||
| 言語 | eng | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | CRM | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | direct marketing | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | customer lifetime | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | Bayesian method | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | MCMC | |||||
| 資源タイプ | ||||||
| 資源 | http://purl.org/coar/resource_type/c_18gh | |||||
| タイプ | technical report | |||||
| アクセス権 | ||||||
| アクセス権 | metadata only access | |||||
| アクセス権URI | http://purl.org/coar/access_right/c_14cb | |||||
| 著者 |
Abe, Makoto
× Abe, Makoto |
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| 著者所属 | ||||||
| 著者所属 | University of Tokyo | |||||
| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | This research extends a Pareto/NBD model of customer-base analysis using a hierarchical Bayesian (HB) framework to suit today's customized marketing. The proposed HB model presumes three tried and tested assumptions of Pareto/NBD models: (1) a Poisson purchase process, (2) a memoryless dropout process (i.e., constant hazard rate), and (3) heterogeneity across customers, while relaxing the independence assumption of the purchase and dropout rates and incorporating customer characteristics as covariates. The model also provides useful output for CRM, such as a customer-specific lifetime and survival rate, as by-products of the MCMC estimation. Using three different types of databases --- music CD for e-commerce, FSP data for a department store and a music CD chain, the HB model is compared against the benchmark Pareto/NBD model. The study demonstrates that recency-frequency data, in conjunction with customer behavior and characteristics, can provide important insights into direct marketing issues, such as the demographic profile of best customers and whether long-life customers spend more. | |||||
| 内容記述 | ||||||
| 内容記述タイプ | Other | |||||
| 内容記述 | 本文フィルはリンク先を参照のこと | |||||
| 書誌情報 |
Discussion paper series. CIRJE-F 巻 CIRJE-F-537, 発行日 2008-01 |
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| 書誌レコードID | ||||||
| 収録物識別子タイプ | NCID | |||||
| 収録物識別子 | AA11450569 | |||||
| フォーマット | ||||||
| 内容記述タイプ | Other | |||||
| 内容記述 | application/pdf | |||||
| 日本十進分類法 | ||||||
| 主題Scheme | NDC | |||||
| 主題 | 335 | |||||
| 出版者 | ||||||
| 出版者 | 日本経済国際共同センター | |||||
| 出版者別名 | ||||||
| Center for International Research on the Japanese Economy | ||||||
| 関係URI | ||||||
| 識別子タイプ | URI | |||||
| 関連識別子 | http://www.cirje.e.u-tokyo.ac.jp/research/dp/2008/2008cf537ab.html | |||||
