Understanding the Joint Value of High-Frequency Service Metrics and Post-Purchase Perception
48 Pages Posted: 16 Jul 2015 Last revised: 7 Aug 2020
Date Written: August 1, 2020
The advent of digitization has allowed firms to collect high-frequency data - subjective and objective - to monitor their service performance. This paper proposes a methodological framework to help firms understand the value of collecting these data. We apply the framework to novel high-frequency, individual-level, cross-sectional and time-series measures of subjective post-purchase perceptions and objective operational metrics from a quick service restaurant and an auto rental company. Our approach allows for the quantification of statistical and economic significance of collecting high-frequency subjective service data in the presence of the objective counterpart. The value of collecting subjective data is estimated to be around $9.1 million at a 20% change in objective metrics and is found to be the highest for frequent customers who have not provided ratings frequently. We also find the presence of both within- and across-individual selection in survey response, and the bias stemming from within-individual selection can be more than twice as large as that from across-individual selection. These results advance the literature on measurement and management of service performance and provide insights to managers for forecasting and resource allocation.
Keywords: service quality, high-frequency data, within-individual selection, across-individual selection
JEL Classification: L1, L8, M3
Suggested Citation: Suggested Citation