Abstract
Many business organizations measure customer loyalty by using a question suggested by Reichheld (2003) —“likelihood to recommend the company to friend or colleague (LTR, 0=extremely unlikely, 10=extremely likely)”. The LTR question can determine a customer’s status as a detractor (LTR=0-6), a passively satisfied customer (LTR=7-8), or a promoter (LTR=9-10). Although this measure of customer status has been widely used in industry, no quantitative method so far has been introduced to analyze the underlying predictors of customer status as detractors, passively satisfied customers, or promoters. This study bridges the research gap by advocating Generalized Ordinal Logistic Regression (GOLR) as a viable statistical approach for identifying predictors for transforming customer status into a higher level (i.e., pulling customers out of the pool of detractors and driving them into the pool of promoters). Using online shopping as a research context, we found that GOLR outperformed traditional linear regression in identifying important predictors of customer status and in testing whether predictors have increasing or decreasing marginal effects on improving customer status to a higher level. Based on the results of GLOR, companies can make full use of the LTR question and design appropriate strategies for improvement.
Highlights
In both the industry and academic realm of consumer research, customer loyalty is usually measured on a five or seven point Likert-like scale
To help organizations achieve a better understanding of the Likelihood to Recommend (LTR) measure, Reichheld further proposed a net promoter score (NPS), which is calculated by subtracting the percentage of detractors from the percentage of promoters, and suggested that NPS should be the only number that companies need to grow because this score has been found to be strongly correlated with the growth rates in many industries (Reichheld, 2003)
Improving the “Communication” function of the website has a significant effect in pushing customers away from Detractors, and providing sufficient amount of “Trust Information” has a significant effect in converting customers into Promoters
Summary
In both the industry and academic realm of consumer research, customer loyalty is usually measured on a five or seven point Likert-like scale. The method is to ask the LTR question: “How likely are you to recommend the company to your friend or colleague?” Customers respond to this question on an eleven point Likert-like scale ranging from extremely unlikely (0) to extremely likely (10). Responses to the LTR question help determine a customer’s status as a promoter, passively satisfied customer, or detractor. Satisfied customers are those who rate 7 or 8 on the scale. Detractors are those who respond with 0 through 6. To help organizations achieve a better understanding of the LTR measure, Reichheld further proposed a net promoter score (NPS), which is calculated by subtracting the percentage of detractors from the percentage of promoters, and suggested that NPS should be the only number that companies need to grow because this score has been found to be strongly correlated with the growth rates in many industries (Reichheld, 2003)
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
