Targeting Customers with Statistical and Data-Mining Techniques
Abstract
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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Various thinking AI can be used for targeting.
“Existing studies show that various thinking AI can be used for this purpose.”
From A strategic framework for artificial intelligence in marketing (2021) · cites this paper as Drew et al. 2001
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A strategic framework for artificial intelligence in marketing
Huang, M.-H., & Rust, R. T. (2021) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-020-00749-9 · Cited by 2,059 · see citing works
“Examples include targeting customers using a combination of statistical and data-mining techniques (Drew et al. 2001), screening and targeting cancer outreach marketing using machine learning and causal forests (Chen et al. 2020), optimizing promotion targeting for new customers using various…”
BackgroundData mining in business services
Olson, D. L. (2007) · Service Business · doi:10.1007/s11628-006-0014-7 · Cited by 34 · see citing works
- Authors
- Drew, J. H., Mani, D. R., Betz, A. L., & Datta, P.
- Affiliations
- Verizon (United States) (US)
- ORCID
- Mani, D. R.
- Venue
- Journal of Service Research
- Publisher
- SAGE Publications
- Published
- 2001-02
- Volume
- 3
- Issue
- 3
- Pages
- 205-219
- ISSN
- 1094-6705 (ISSN-L)
- 1552-7379
- OpenAlex
- W2151969307
- Cited by
- 71
- References
- 0
- Citations by year
- 2024: 1 · 2022: 1 · 2021: 1 · 2020: 3 · 2018: 3 · 2017: 1 · 2016: 1 · 2015: 3 · 2014: 2 · 2013: 5 · 2012: 7
- FWCI
- 17.37
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Service Research (publishedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Marketing › Customer churn and segmentation
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Customer Service Quality and Loyalty
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Market Behavior and Pricing
- Keywords
- customer targeting, customer retention, relationship management, customer lifetime value, hazard function estimation, service life cycle, marketing activities, customer churn
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