The Value of Different Customer Satisfaction and Loyalty Metrics in Predicting Business Performance

Neil A. Morgan () and Lopo Leotte Rego ()
Additional contact information
Neil A. Morgan: Kelley School of Business, Indiana University, 1309 East Tenth Street, Bloomington, Indiana 47405-1701
Lopo Leotte Rego: Tippie College of Business, University of Iowa, 108 PBB S320, Iowa City, Iowa 52242-1994

Marketing Science, 2006, vol. 25, issue 5, 426-439

Abstract: Managers commonly use customer feedback data to set goals and monitor performance on metrics such as “Top 2 Box” customer satisfaction scores and “intention-to-repurchase” loyalty scores. However, analysts have advocated a number of different customer feedback metrics including average customer satisfaction scores and the number of “net promoters” among a firm's customers. We empirically examine which commonly used and widely advocated customer feedback metrics are most valuable in predicting future business performance. Using American Customer Satisfaction Index data, we assess the linkages between six different satisfaction and loyalty metrics and COMPUSTAT and CRSP data-based measures of different dimensions of firms' business performance over the period 1994–2000. Our results indicate that average satisfaction scores have the greatest value in predicting future business performance and that Top 2 Box satisfaction scores also have good predictive value. We also find that while repurchase likelihood and proportion of customers complaining have some predictive value depending on the specific dimension of business performance, metrics based on recommendation intentions (net promoters) and behavior (average number of recommendations) have little or no predictive value. Our results clearly indicate that recent prescriptions to focus customer feedback systems and metrics solely on customers' recommendation intentions and behaviors are misguided.

Keywords: customer satisfaction; marketing metrics; marketing strategy (search for similar items in EconPapers)
Date: 2006
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (91)

Downloads: (external link)
http://dx.doi.org/10.1287/mksc.1050.0180 (application/pdf)

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:inm:ormksc:v:25:y:2006:i:5:p:426-439

Access Statistics for this article

More articles in Marketing Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().