1. The Untested Assumption: Can a Net Promoter Study Be Used to Improve Net Promoter Score?
- Author
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Bettencourt, Lance A and Houston, Mark B
- Subjects
CUSTOMER feedback ,CONSUMERS ,BUSINESS revenue ,RESEARCH personnel ,CUSTOMER satisfaction ,PSYCHOLOGICAL feedback - Abstract
Despite scholarly critiques, use of the Net Promoter Score (NPS
® ) continues to grow in popularity among firms. Even researchers who criticize NPS recognize its potential for predicting desirable customer behaviors and revenue growth. However, a firm's goal in measuring NPS is not to simply assess it, but to be empowered to improve that score. This goal begs an important question: Does a "net promoter" study provide the insights that a firm needs to improve their NPS? The critical, but untested, assumption in NPS use is that the insights gained from open-ended customer comments in a net promoter study can be used to set improvement priorities that will increase future NPS likely-to-recommend ratings. Through two distinct studies, one in a business-to-business context with auto dealership decision-makers and one in a business-to-consumer context with vehicle repair customers, we investigate this assumption. Our results reveal that the critical untested assumption of a net promoter study is questionable. The convergence is low to moderate between open-ended priorities from a net promoter study and predictors of the standard 'likely-to-recommend' NPS question. We also find that the convergence between customers' open-ended priorities and their stated and derived priorities from closed-ended responses is higher for NPS detractors and passives than promoters, but it is still only moderate. The strength of this convergence of priorities is also impacted by the wording of the questions used to elicit customers' open-ended priorities. Firms using open-ended comments to set priorities should ask customers, especially detractors, to identify areas for improvement. In addition, they should supplement open-ended customer feedback with closed-ended questions to get customers' performance ratings in relation to their specific needs. [ABSTRACT FROM AUTHOR]- Published
- 2024
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