Ask or infer? Strategic implications of alternative learning approaches in customization
Scott Fay,
Deb Mitra and
Qiong Wang
International Journal of Research in Marketing, 2009, vol. 26, issue 2, 136-152
Abstract:
Learning about a customer's preferences is a critical first step in the customization process. Broadly, firms adopt two alternative learning approaches: (1) ask, i.e., solicit preference information directly from the customer (S-Learning), or (2) infer, i.e., deduce preference information based on past observations of the customer as well as those of other customers (O-Learning). Most existing research on customization strategy focuses on a firm's marketing mix decisions, implicitly assuming away how the firm learns about customers. We contribute to this literature by examining how a firm's use of a specific learning approach impacts competition, particularly its rival's choice of learning approach. We find that O-Learning provides a credible signal for relaxing price competition, while S-Learning does not. Further, S-Learning by a firm creates a disincentive for rivals to also invest in S-Learning. We survey business customers and find significant evidence supporting our theory. We conclude with several managerial implications of our theory including how a firm can optimally select its learning strategy in order to impact its competitive environment.
Keywords: Customization; Personalization; Learning; Competitive strategy; Customer relationship management (search for similar items in EconPapers)
Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S016781160900024X
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:ijrema:v:26:y:2009:i:2:p:136-152
DOI: 10.1016/j.ijresmar.2008.12.003
Access Statistics for this article
International Journal of Research in Marketing is currently edited by Roland Rust
More articles in International Journal of Research in Marketing from Elsevier
Bibliographic data for series maintained by Catherine Liu ().