PurposeDespite widespread acknowledgement of the importance of employees to the success of service firms, research into how well frontline service staff understand service remains scarce. This study aims to investigate what constitutes good customer service from the viewpoint of frontline service employees and to explore gender differences in particular.Design/methodology/approachThe data were collected from 876 frontline employees across a wide range of service industries. An automated text analysis using Leximancer explored general and gender‐specific patterns in employees' customer service understanding.FindingsIrrespective of gender, frontline service staff share the perception that the pillars of good customer service are listening skills, making the customer happy, and offering service. Males have a more functional, outcome‐oriented interpretation of customer service; females focus more on the actual service interaction and emotional outcomes.Practical implicationsBy acknowledging gender‐based dissimilarities in the customer service understanding of frontline service employees, the efficiency of recruitment and training processes will be enhanced.Originality/valueThis study contributes to limited work on service models of frontline staff and shows that gender can explain some differences. This study also adds another dimension to the understanding of gender effects in services, beyond its influence on customers' quality perceptions and behaviours. The results are important for services marketing research and for managers in charge of recruiting and training frontline service staff.
This chapter deepens understanding of holistic case-based modelling of customers' thinking-doing brand experiences using grounded theory studies. The chapter includes an empirical study to illustrate the method. The reported study includes applying the 'long-interview method' and 'theoretical sampling' in completing personal, face-to-face, interviews of travel parties when just ending their visits to a Canadian Province. The empirical analysis focuses on acquiring process data held in the minds of customers i.e., the analysis illustrates emic-based storytelling of what was planned and what actually happened, leading to what specific outcomes. Achieving such holistic, case-based, views of customer decisions and behaviour provides a rich, deep and nuance-filled understanding of the causes and consequences of such behaviours.
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