Modeling Customer Lifetimes with Multiple Causes of Churn
Customer retention and customer churn are key metrics of interest to marketers, but little attention has been placed on linking the different reasons for which customers churn to their value to a contractual service provider. In this paper, we put forth a hierarchical competing-risk model to jointly...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
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Institute for Operations Research and the Management Sciences (INFORMS)
2012
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| Online Access: | http://hdl.handle.net/1721.1/74625 |
| _version_ | 1811097882927824896 |
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| author | Braun, Michael Schweidel, David A. |
| author2 | Sloan School of Management |
| author_facet | Sloan School of Management Braun, Michael Schweidel, David A. |
| author_sort | Braun, Michael |
| collection | MIT |
| description | Customer retention and customer churn are key metrics of interest to marketers, but little attention has been placed on linking the different reasons for which customers churn to their value to a contractual service provider. In this paper, we put forth a hierarchical competing-risk model to jointly model when customers choose to terminate their service and why. Some of these reasons for churn can be influenced by the firm (e.g., service problems or price–value trade-offs), but others are uncontrollable (e.g., customer relocation and death). Using this framework, we demonstrate that the impact of a firm's efforts to reduce customer churn for controllable reasons is mitigated by the prevalence of uncontrollable ones, resulting in a “damper effect” on the return from a firm's retention marketing efforts. We use data from a provider of land-based telecommunication services to demonstrate how the competing-risk model can be used to derive a measure of the incremental customer value that a firm can expect to accrue through its efforts to delay churn, taking this damper effect into account. In addition to varying across customers based on geodemographic information, the magnitude of the damper effect depends on a customer's tenure to date. We discuss how our framework can be used to tailor the firm's retention strategy to individual customers, both in terms of which customers to target and when retention efforts should be deployed. |
| first_indexed | 2024-09-23T17:06:28Z |
| format | Article |
| id | mit-1721.1/74625 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T17:06:28Z |
| publishDate | 2012 |
| publisher | Institute for Operations Research and the Management Sciences (INFORMS) |
| record_format | dspace |
| spelling | mit-1721.1/746252022-10-03T10:27:22Z Modeling Customer Lifetimes with Multiple Causes of Churn Braun, Michael Schweidel, David A. Sloan School of Management Braun, Michael Customer retention and customer churn are key metrics of interest to marketers, but little attention has been placed on linking the different reasons for which customers churn to their value to a contractual service provider. In this paper, we put forth a hierarchical competing-risk model to jointly model when customers choose to terminate their service and why. Some of these reasons for churn can be influenced by the firm (e.g., service problems or price–value trade-offs), but others are uncontrollable (e.g., customer relocation and death). Using this framework, we demonstrate that the impact of a firm's efforts to reduce customer churn for controllable reasons is mitigated by the prevalence of uncontrollable ones, resulting in a “damper effect” on the return from a firm's retention marketing efforts. We use data from a provider of land-based telecommunication services to demonstrate how the competing-risk model can be used to derive a measure of the incremental customer value that a firm can expect to accrue through its efforts to delay churn, taking this damper effect into account. In addition to varying across customers based on geodemographic information, the magnitude of the damper effect depends on a customer's tenure to date. We discuss how our framework can be used to tailor the firm's retention strategy to individual customers, both in terms of which customers to target and when retention efforts should be deployed. 2012-11-13T15:40:35Z 2012-11-13T15:40:35Z 2011-08 2010-09 Article http://purl.org/eprint/type/JournalArticle http://hdl.handle.net/1721.1/74625 Braun, M., and D. A. Schweidel. “Modeling Customer Lifetimes with Multiple Causes of Churn.” Marketing Science 30.5 (2011): 881–902. en_US http://dx.doi.org/ 10.1287/mksc.1110.0665 Marketing Science Creative Commons Attribution-Noncommercial-Share Alike 3.0 http://creativecommons.org/licenses/by-nc-sa/3.0/ application/pdf Institute for Operations Research and the Management Sciences (INFORMS) SSRN |
| spellingShingle | Braun, Michael Schweidel, David A. Modeling Customer Lifetimes with Multiple Causes of Churn |
| title | Modeling Customer Lifetimes with Multiple Causes of Churn |
| title_full | Modeling Customer Lifetimes with Multiple Causes of Churn |
| title_fullStr | Modeling Customer Lifetimes with Multiple Causes of Churn |
| title_full_unstemmed | Modeling Customer Lifetimes with Multiple Causes of Churn |
| title_short | Modeling Customer Lifetimes with Multiple Causes of Churn |
| title_sort | modeling customer lifetimes with multiple causes of churn |
| url | http://hdl.handle.net/1721.1/74625 |
| work_keys_str_mv | AT braunmichael modelingcustomerlifetimeswithmultiplecausesofchurn AT schweideldavida modelingcustomerlifetimeswithmultiplecausesofchurn |