Targeting Customers With Statistical And Data-Mining Techniques  

Oleh:

Drew, James H. ; Mani, D. R. ; Betz, Andrew L. ; Datta, Piew

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Journal Of Service Research vol. 3 no. 3 (Feb. 2001), page 205-231.
Fulltext: 205.pdf (168.84KB)

Isi artikel

Operationalizing a relationship management program requires a retention strategy that is sensitive to an individual customer’s position in the service life cycle, while being financially sound for the provider. To this end, estimating a customer’s hazard function and remaining tenure with the company can lead to important insights into marketing tactics and constitute fundamental building blocks for methods of targeting important customers. The authors describe a way of estimating these quantities using a combination of statistical and data-mining techniques. The resulting customer hazard information leads to a generalization of lifetime value (GLTV) that explicitly accounts for company actions and their success in relationship management.

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