WEKO3
アイテム
{"_buckets": {"deposit": "613543f0-93d3-4200-8a5c-86d0badbc0a6"}, "_deposit": {"id": "42075", "owners": [], "pid": {"revision_id": 0, "type": "depid", "value": "42075"}, "status": "published"}, "_oai": {"id": "oai:repository.dl.itc.u-tokyo.ac.jp:00042075", "sets": ["7436", "7434"]}, "item_8_biblio_info_7": {"attribute_name": "書誌情報", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2009-03", "bibliographicIssueDateType": "Issued"}, "bibliographicVolumeNumber": "CIRJE-F-616", "bibliographic_titles": [{"bibliographic_title": "Discussion paper series. CIRJE-F"}]}]}, "item_8_description_13": {"attribute_name": "フォーマット", "attribute_value_mlt": [{"subitem_description": "application/pdf", "subitem_description_type": "Other"}]}, "item_8_description_5": {"attribute_name": "抄録", "attribute_value_mlt": [{"subitem_description": "A customer behavior model that permits the estimation of customer lifetime value (CLV) from standard RFM data in \"non-contractual\" setting is developed by extending the hierarchical Bayes (HB) framework of the Pareto/NBD model (Abe 2008). The model relates customer characteristics to frequency, dropout and spending behavior, which, in turn, is linked to CLV to provide useful insight into acquisition. The proposed model (1) relaxes the assumption of independently distributed parameters for frequency, dropout and spending processes across customers, (2) accommodates the inclusion of covariates through hierarchical modeling, (3) allows easy estimation of latent variables at the individual level, which could be useful for CRM, and (4) provides the correct measure of errors. Using FSP data from a department store and a CD chain, the HB model is shown to perform well on calibration and holdout samples both at the aggregate and disaggregate levels in comparison with the benchmark Pareto/NBD-based model. Several substantive issues are uncovered. First, both of our datasets exhibit correlation between frequency and spending parameters, violating the assumption of the existing Pareto/NBD-based CLV models. Direction of the correlation is found to be data dependent. Second, useful insight into acquisition is gained by decomposing the effect of change in covariates on CLV into three components: frequency, dropout and spending. The three components can exert influences in opposite directions, thereby canceling each other to produce less effect as the total on CLV. Third, not accounting for uncertainty in parameter estimate can cause large bias in measures, such as CLV and elasticity. Its ignorance can potentially have a serious consequence on managerial decision making.", "subitem_description_type": "Abstract"}]}, "item_8_description_6": {"attribute_name": "内容記述", "attribute_value_mlt": [{"subitem_description": "本文フィルはリンク先を参照のこと", "subitem_description_type": "Other"}]}, "item_8_publisher_20": {"attribute_name": "出版者", "attribute_value_mlt": [{"subitem_publisher": "日本経済国際共同センター"}]}, "item_8_relation_25": {"attribute_name": "関係URI", "attribute_value_mlt": [{"subitem_relation_type_id": {"subitem_relation_type_id_text": "http://www.cirje.e.u-tokyo.ac.jp/research/dp/2009/2009cf616ab.html", "subitem_relation_type_select": "URI"}}]}, "item_8_source_id_10": {"attribute_name": "書誌レコードID", "attribute_value_mlt": [{"subitem_source_identifier": "AA11450569", "subitem_source_identifier_type": "NCID"}]}, "item_8_subject_15": {"attribute_name": "日本十進分類法", "attribute_value_mlt": [{"subitem_subject": "335", "subitem_subject_scheme": "NDC"}]}, "item_8_text_21": {"attribute_name": "出版者別名", "attribute_value_mlt": [{"subitem_text_value": "Center for International Research on the Japanese Economy"}]}, "item_8_text_34": {"attribute_name": "資源タイプ", "attribute_value_mlt": [{"subitem_text_value": "Discussion Paper"}]}, "item_8_text_4": {"attribute_name": "著者所属", "attribute_value_mlt": [{"subitem_text_value": "University of Tokyo"}]}, "item_access_right": {"attribute_name": "アクセス権", "attribute_value_mlt": [{"subitem_access_right": "metadata only access", "subitem_access_right_uri": "http://purl.org/coar/access_right/c_14cb"}]}, "item_creator": {"attribute_name": "著者", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "Abe, Makoto"}], "nameIdentifiers": [{"nameIdentifier": "96831", "nameIdentifierScheme": "WEKO"}]}]}, "item_keyword": {"attribute_name": "キーワード", "attribute_value_mlt": [{"subitem_subject": "CRM", "subitem_subject_scheme": "Other"}, {"subitem_subject": "Acquisition", "subitem_subject_scheme": "Other"}, {"subitem_subject": "hierarchical Bayes", "subitem_subject_scheme": "Other"}, {"subitem_subject": "Pareto/NBD", "subitem_subject_scheme": "Other"}, {"subitem_subject": "MCMC", "subitem_subject_scheme": "Other"}]}, "item_language": {"attribute_name": "言語", "attribute_value_mlt": [{"subitem_language": "eng"}]}, "item_resource_type": {"attribute_name": "資源タイプ", "attribute_value_mlt": [{"resourcetype": "technical report", "resourceuri": "http://purl.org/coar/resource_type/c_18gh"}]}, "item_title": "Customer Lifetime Value and RFM Data : Accounting Your Customers: One by One", "item_titles": {"attribute_name": "タイトル", "attribute_value_mlt": [{"subitem_title": "Customer Lifetime Value and RFM Data : Accounting Your Customers: One by One"}]}, "item_type_id": "8", "owner": "1", "path": ["7436", "7434"], "permalink_uri": "http://hdl.handle.net/2261/25752", "pubdate": {"attribute_name": "公開日", "attribute_value": "2013-05-31"}, "publish_date": "2013-05-31", "publish_status": "0", "recid": "42075", "relation": {}, "relation_version_is_last": true, "title": ["Customer Lifetime Value and RFM Data : Accounting Your Customers: One by One"], "weko_shared_id": null}
Customer Lifetime Value and RFM Data : Accounting Your Customers: One by One
http://hdl.handle.net/2261/25752
http://hdl.handle.net/2261/25752cf44b0f6-e0d7-45a8-8090-c786e309ec47
Item type | 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 | Customer Lifetime Value and RFM Data : Accounting Your Customers: One by One | |||||
言語 | ||||||
言語 | eng | |||||
キーワード | ||||||
主題 | CRM | |||||
主題Scheme | Other | |||||
キーワード | ||||||
主題 | Acquisition | |||||
主題Scheme | Other | |||||
キーワード | ||||||
主題 | hierarchical Bayes | |||||
主題Scheme | Other | |||||
キーワード | ||||||
主題 | Pareto/NBD | |||||
主題Scheme | Other | |||||
キーワード | ||||||
主題 | MCMC | |||||
主題Scheme | Other | |||||
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 |
|||||
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 | A customer behavior model that permits the estimation of customer lifetime value (CLV) from standard RFM data in "non-contractual" setting is developed by extending the hierarchical Bayes (HB) framework of the Pareto/NBD model (Abe 2008). The model relates customer characteristics to frequency, dropout and spending behavior, which, in turn, is linked to CLV to provide useful insight into acquisition. The proposed model (1) relaxes the assumption of independently distributed parameters for frequency, dropout and spending processes across customers, (2) accommodates the inclusion of covariates through hierarchical modeling, (3) allows easy estimation of latent variables at the individual level, which could be useful for CRM, and (4) provides the correct measure of errors. Using FSP data from a department store and a CD chain, the HB model is shown to perform well on calibration and holdout samples both at the aggregate and disaggregate levels in comparison with the benchmark Pareto/NBD-based model. Several substantive issues are uncovered. First, both of our datasets exhibit correlation between frequency and spending parameters, violating the assumption of the existing Pareto/NBD-based CLV models. Direction of the correlation is found to be data dependent. Second, useful insight into acquisition is gained by decomposing the effect of change in covariates on CLV into three components: frequency, dropout and spending. The three components can exert influences in opposite directions, thereby canceling each other to produce less effect as the total on CLV. Third, not accounting for uncertainty in parameter estimate can cause large bias in measures, such as CLV and elasticity. Its ignorance can potentially have a serious consequence on managerial decision making. | |||||
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-616, 発行日 2009-03 |
|||||
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 | 335 | |||||
主題Scheme | NDC | |||||
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/2009/2009cf616ab.html |