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Predicting and measuring customer lifetime values for apartment tenants

Author

Listed:
  • Jian Wang

    (The Rainmaker Group)

  • Murtaza Das

    (The Rainmaker Group)

  • Amar Duggasani

    (The Rainmaker Group)

Abstract

It is of great benefit for an apartment community to predict the customer lifetime value (CLV) for each tenant. This prediction can be used not only to identify the most profitable residents, but also to make better pricing decisions, especially when optimizing renewal rents for expiring leases. CLV has been studied extensively in many industries such as service and retail. However, to our knowledge, there is no literature specifically addressing the estimation of CLV for apartment tenants. In this study, we propose an approximate approach to predicting the lifetime length and value for apartment tenants as well as their renewal probabilities. The model was estimated and tested based on a real dataset from 68 apartment companies in the US. The resulting prediction accuracy was particularly satisfactory for the tenants who did not renew or only renewed once.

Suggested Citation

  • Jian Wang & Murtaza Das & Amar Duggasani, 2016. "Predicting and measuring customer lifetime values for apartment tenants," Zeitschrift für Immobilienökonomie (German Journal of Real Estate Research), Springer;Gesellschaft für Immobilienwirtschaftliche Forschung e. V., vol. 2(2), pages 103-120, October.
    • Handle: RePEc:spr:gjorer:v:2:y:2016:i:2:d:10.1365_s41056-016-0015-0
    DOI: 10.1365/s41056-016-0015-0
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    References listed on IDEAS

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