NPS

This metric was introduced in response to the perception that other tools were poor predictors of customer satisfaction and loyalty. Driven by the demands and information needs of practitioners, this tool leveraged trends such as the emergence of low-cost technology that facilitated rapid completion and analysis of online or mobile surveys, as well as the need to address the problem of declining survey response rates (Nunan, Reference Nunan2024).

This technique is based on asking consumers a single question: ‘How likely are you to recommend [insert organization name] to a friend, colleague, or family member?’ It is thus a tool characterized by quick application or implementation, high simplicity in use and analysis – key factors contributing to its popularity (Klaus & Maklan, Reference Klaus and Maklan2013). Since its initial publication, it has been regarded as a standard for measuring and enhancing customer loyalty (Faltejskivá, Dvoráková, & Hotovcová, Reference Faltejskivá, Dvoráková and Hotovcová2016), especially relevant to service organizations (i.e., servitizing organizations and those operating in traditional service sectors) (Lacohee, Souchon, Dickenson, Krug, & Saffre, Reference Lacohee, Souchon, Dickenson, Krug and Saffre2024).

Currently, it serves as an evaluation method that has been extensively used by organizations (Lewis & Mehmet, Reference Lewis and Mehmet2020) of varying types, with an estimated 70% of customer experience (CX) professionals utilizing NPS® as a key metric (Dorsey, Temkin, & Quaadgras, Reference Dorsey, Temkin and Quaadgras2024). Among its countless applications, studies have used it to evaluate mental health services for older adults (Wilberforce, Poll, Langham, Worden, & Challis, Reference Wilberforce, Poll, Langham, Worden and Challis2019), communication in retail (Eger & Mičík, Reference Eger and Mičík2017), higher education (Kara, Mintu-Wimsatt, & Spillan, Reference Kara, Mintu-Wimsatt and Spillan2021), and the complaint resolution process in the banking services sector (Pandey, Reference Pandey2016), among others. Within the sports industry, studies have focused on sporting events (Murillo, Carles, Llop, Moya, & Planas, Reference Murillo, Carles, Llop, Moya and Planas2016), tennis technical training services (Lara-Bocanegra, Bohórquez, & García-Fernández, Reference Lara-Bocanegra, Bohórquez and García-Fernández2022), retail sports equipment stores (Happ, Scholl-Grissemann, Peters, & Schnitzer, Reference Happ, Scholl-Grissemann, Peters and Schnitzer2021), fitness apps (Rodríguez, García-Fernández, Valcarce-Torrente, Bernal-García, & Gálvez-Ruiz, Reference Rodríguez, García-Fernández, Valcarce-Torrente, Bernal-García and Gálvez-Ruiz2023), and also in the context of sport services. Dalmau-Torres et al. (Reference Dalmau-Torres, Gargallo-Ibort, Tamayo-Fajardo and Nuviala- Nuviala2022) determined the convergent validity of the tool among sports service users, while Jiménez-Jiménez et al. (Reference Jiménez-Jiménez, Vidal-Vidaplana, Núñez-Sánchez and Faus2024) used this tool to show differences based on sociodemographic variables, representing a novel approach in the literature.

One of the fundamental characteristics that explain its widespread use lies in the analysis of responses. Customers are offered a scale ranging from 0 to 10, where scores between 0 and 6 are identified as detractors, scores between 7 and 8 as passives, and scores between 9 and 10 as promoters. The indicator is calculated by subtracting the percentage of detractors from the percentage of promoters (NPS® = percentage of promoters – percentage of detractors). However, a significant bias exists due to the impact of each country’s specific culture on the scoring range. According to Chen, Lee and Stevenson (Reference Chen, Lee and Stevenson1995), cross-cultural differences result in variations in response styles, which carry both theoretical and methodological implications. For instance, a score of 8 in academic grading in countries like the Netherlands or Spain is equivalent to an ‘A’ (the highest possible grade) in countries such as the United States or the United Kingdom. In this context, a study conducted by Temkin and Quaadgras (Reference Temkin and Quaadgras2021) across 18 countries revealed differences in how respondents answered the NPS® question. The ranges varied from 7% to 59% for detractors, 22% to 51% for passives, and 10% to 71% for promoters. Notably, only six countries (including Spain, the context of this study) had a percentage of passives equal to or exceeding that of promoters. Consequently, and as highlighted by De Jong, Steenkamp and Veldkamp (Reference De Jong, Steenkamp and Veldkamp2009), different cultures utilize response scales in distinct ways.

However, despite the widespread use of this tool, the literature has questioned its application by highlighting various issues, such as the relationship between the resulting score and company growth (Keiningham, Cooil, Andreassen, & Aksoy, Reference Keiningham, Cooil, Andreassen and Aksoy2007), variations in response types based on the demographic characteristics of the respondent (Kasch, Reference Kasch2016; Situmorang, Reference Situmorang2017), the respondent’s gender (Eskildsen & Kristensen, Reference Eskildsen and Kristensen2011), or even the method of administration, such as text messages or phone interviews (Van Der Heijden, Reference Van Der Heijden2017). Additionally, the results do not provide information on what an organization is doing well, strategic guidance on potential improvements (Fisher & Kordupleski, Reference Fisher and Kordupleski2019), or what actions to take to improve, and it does not consider ‘passive’ customers as a meaningful category (Fisher & Kordupleski, Reference Fisher and Kordupleski2019).

For this reason, Keiningham, Rust, Lariviere, Askoy, and Williams (Reference Keiningham, Rust, Lariviere, Askoy and Williams2018) refer to the concept of ecological fallacy (or the zoning effect) in the use of this technique, identifying two main issues: (a) it is primarily a measure of attitude toward recommending rather than actual word-of-mouth behaviors (East, Hammond, & Wright, Reference East, Hammond and Wright2007), and (b) the notion of net promoter has been criticized for its reliance on unverified testimonials (Baehre, O’Dwyer, O’Malley, & Lee, Reference Baehre, O’Dwyer, O’Malley and Lee2022). Additionally, considering that NPS® reflects loyalty, responses are highly influenced by recent events (attitudinal) and are thus significantly shaped by specific circumstances. Consequently, the responses provided at any given time fail to account for the multidimensionality of the attributes involved in delivering a service and overlook the multidimensionality of loyalty.

IPA

It is a technique proposed by Martilla and James (Reference Martilla and James1977) to evaluate a series of attributes related to automobile sales services with the goal of improving customer service and increasing vehicle sales. Provides an indirect approach to measuring satisfaction, enabling a simple and functional graphical representation of the strengths and areas for improvement of a given product or service (Abalo et al., Reference Patti, van Dessel and Hartley2006). Consumers tend to evaluate service performance based on a set of attributes, making it relevant to assess the importance of each one to weigh its performance and obtain an indirect measure of consumer satisfaction (Ferreira & Veloso da Silva, Reference Ferreira and Veloso da Silva2011). For this purpose, a series of indicators or attributes (related to products or services) are defined and evaluated before purchase or consumption, representing the importance assigned to each indicator. These attributes are then reassessed after purchase or consumption, reflecting their perceived performance. According to Oh (Reference Oh2021), this approach allows for establishing a series of causal relationships.

In this way, the selection of attributes to be evaluated can vary significantly and is adaptable to each specific context, allowing organizations to focus on the elements they deem necessary in their service delivery process. This helps identify the components that require greater attention within the organization. However, as Martilla and James (Reference Martilla and James1977; p. 79) point out, ‘determining which attributes to measure is critical, as overlooking factors that are important to the customer will severely limit the usefulness of the importance-performance analysis’. The analytical methodology of this technique involves cross-referencing the results obtained from the evaluation of both the importance and performance of a series of attributes. This process produces two perpendicular axes in a two-dimensional space, generating four quadrants on which the different attributes are distributed (Serrano, Rial, Sarmiento, & Carvalho, Reference Serrano, Rial, Sarmiento and Carvalho2014), corresponding to varying levels of priority.

Thus, this is an analytical technique that, after identifying areas for improvement, enables the optimization of resources and the design of action plans aimed at enhancing satisfaction – an essential factor for improving loyalty, according to specific literature in the context of sports services (Gálvez-Ruiz et al., Reference Gálvez-Ruiz, Calabuig, Grimaldi-Puyana, González-Serrano and García-Fernández2023; Sevilmis et al., Reference Sevilmiş, Doğan, Gálvez-Ruiz and García-Fernández2024). However, despite being a technique widely used in various contexts due to its simplicity of application, low cost (Ábalo et al., Reference Ábalo, Varela and Rial2006; Murillo & Saurina, Reference Murillo and Saurina2013), and the ease with which results can be interpreted (contributing to highly intuitive decision-making implications), it has certain weaknesses (Arbore & Busacca, Reference Arbore and Busacca2011). These include the implicit assumption that the relationship between attribute performance and overall customer satisfaction is linear and symmetric (Matzler, Bailom, Hinterhuber, Renzl, & Pichler, Reference Matzler, Bailom, Hinterhuber, Renzl and Pichler2004), or the relative arbitrariness of the graphical representation – specifically, the determination of the threshold distinguishing the high from the low areas for both importance and performance (Picón, Varela, & Braña, Reference Picón, Varela and Braña2011). This issue is addressed by using the general average calculated for each attribute (Deng, Reference Deng2007; Weerasinghe & Malkanthi, Reference Weerasinghe and Malkanthi2022), a quadrant centered on the data instead of the average score of the scale, or a quadrant centered on the scale. Additionally, the indiscriminate use of existing methods for customer acquisition and retention purposes is noted (Arbore & Busacca, Reference Arbore and Busacca2011). Specifically, in the field of sports services, it has been applied in contexts such as golf (Kwon & Chung, Reference Kwon and Chung2018; Serrano-Gómez, García-García, & Rial-Boubeta, Reference Serrano-Gómez, García-García and Rial-Boubeta2023), fitness centers (León-Quismondo et al., Reference León-Quismondo, García-Unanue and Burillo2020; Rodríguez et al., Reference Rodríguez, García-Fernández, Valcarce-Torrente, Bernal-García and Gálvez-Ruiz2023), and sporting events (Parra-Camacho, Añó, Ayora, & González-García, Reference Parra-Camacho, Añó, Ayora and González-García2020).

The applicability of these tools has received varying levels of acceptance and adoption in service management, and similarly, their use for research purposes has also been highly diverse. Therefore, based on the above, the objective of this study was to evaluate user satisfaction at a sports center through the NPS and IPA techniques. This will allow, on the one hand, to compare the information provided by each of them, and on the other hand, to determine which is most effective for establishing management strategies by the organization.

Discussion and conclusions

The evaluation of sports services through consumer perception is a common tool in sports services management, because if we want to manage, we must measure (Faltejskivá et al., Reference Faltejskivá, Dvoráková and Hotovcová2016). Thus, in this study, the evaluation tools NPS® and IPA were used to evaluate the satisfaction of users at a sports center. Both techniques are applied in numerous contexts, including sports, and specifically in sports or fitness centers (e.g., Dalmau-Torres et al., Reference Dalmau-Torres, Gargallo-Ibort, Tamayo-Fajardo and Nuviala- Nuviala2022; León-Quismondo et al., Reference León-Quismondo, García-Unanue and Burillo2020; Rodríguez et al., Reference Rodríguez, García-Fernández, Valcarce-Torrente, Bernal-García and Gálvez-Ruiz2023). While studies employing the NPS® tool can be found in the scientific literature, its use is more common in organizations where results are analyzed internally. As Nunan (Reference Nunan2024) states, the NPS does not derive from the legacy of scientific research, but is governed by the demands and information needs of professionals, or as Patti, van Dessel and Hartley (Reference Patti, van Dessel and Hartley2020) indicate, there is little empirical support for assessing the relationship between NPS score and company or brand performance. In contrast, the IPA tool has a longer academic trajectory and relies on a methodological foundation based on several theoretical contributions, particularly multi-attribute or expectancy-value models (Picón et al., Reference Picón, Varela and Braña2011), and has been applied in various contexts within the sports industry (e.g., León-Quismondo et al., Reference León-Quismondo, García-Unanue and Burillo2020; Rodríguez et al., Reference Rodríguez, García-Fernández, Valcarce-Torrente, Bernal-García and Gálvez-Ruiz2023; Zamorano-Solís & García-Fernandez, Reference Zamorano-Solís and García-Fernandez2018).

The information reported from the NPS® tool evaluation indicated that slightly more than 40% of respondents were promoters, while the detractor and passive groups each showed percentages close to 30%. Although Faltejskivá et al. (Reference Faltejskivá, Dvoráková and Hotovcová2016) state that this tool can be used as a service management system which can influence the enterprise performance too, the results provided are merely descriptive, as they fail to identify key drivers. According to Fisher and Kordupleski (Reference Fisher and Kordupleski2019), it provides no data on what to do to improve but rather serves as one way of calculating one customer loyalty score. Examining the percentages by response type, each score within the full range of responses from detractors (0–6) was below 10%. However, it should be noted that the scale does not differentiate between those giving a score of 0 and those giving a score of 6, treating the entire range equally (Schulman & Sargean, Reference Schulman and Sargean2013). This range consists of seven options, which is significantly broader than the ranges for passives and promoters, each with only two response types. This distinction represents a notable difference in the scoring distribution of detractors compared to passives and promoters. Considering the formula used to calculate the NPS® value (number of promoters – number of detractors), this disparity introduces an imbalance that could negatively impact the ability to achieve a high NPS® score. This issue has led to the development of numerous variations of this measurement system (Faltejskivá et al., Reference Faltejskivá, Dvoráková and Hotovcová2016), primarily due to cultural differences between countries. For instance, Americans are known for giving more ‘extreme’ scores, whereas Europeans are more reserved in their scores (Raats & van der Zwan, Reference Raats and van der Zwan2015). Consequently, some authors propose reconsidering the division of scores for application in Europe, suggesting that scores from 0 to 5 be classified as detractors, 6 and 7 as passives, and 8 to 10 as promoters (Dobronte, Reference Dobronte2012).

On the other hand, it is important to consider the lack of specific information provided by the NPS® tool, as it relies on a single question related to satisfaction. In this regard, Teixeira and Mendes (Reference Teixeira and Mendes2019) point out that combining all customer experiences into a single summary judgment leads to missed opportunities. Moreover, the relationship between satisfaction and loyalty is not linear (Schulman & Sargean, Reference Schulman and Sargean2013). Another issue to consider is the lack of attention to the perceived value of the service (or the attributes of the organization’s service offerings), which prevents understanding, for instance, what is being done better or worse than competitors. This omission is significant, as perceived value has been established as a key indicator of superior business performance (Fisher & Kordupleski, Reference Fisher and Kordupleski2019) and has shown a positive and significant influence on future intentions in studies conducted within the Spanish fitness industry (Baena-Arroyo, Reference Baena-Arroyo2017; García-Fernández et al., Reference García-Fernández, Gálvez-Ruiz, Fernández-Gavira and Vélez-Colón2016). Additionally, market changes, such as the use of technology in general and artificial intelligence in particular, the expansion of self-service, or the automation of processes to improve efficiency and reduce labor costs (Patti et al., Reference Patti, van Dessel and Hartley2020), are transforming the way services are delivered. Consequently, these changes affect both the service experience and satisfaction, yet the NPS® tool has not evolved to adapt to these new contexts. Therefore, as Lacohee et al. (Reference Lacohee, Souchon, Dickenson, Krug and Saffre2024) argue, single-item measures obscure the complex nature of service evaluations, whereas multidimensional measures can help organizations identify what they are doing well and where improvements are needed. Consequently, as highlighted above, evidence points to the misuse of NPS®, along with its failure to provide clear, detailed, or actionable data (Patti et al., Reference Patti, van Dessel and Hartley2020).

In relation to the results obtained using the IPA tool, this study employs a scale composed of 11 attributes specifically developed ad hoc by the staff of the sports center where this research was conducted. This scale includes a series of attributes that represent points of interaction between the client and the organization, and which are crucial to user satisfaction with the sports service provided. Thus, unlike the questionnaires commonly used in the sports services sector to evaluate service quality, elements that the organization considers important in the service delivery process were used. Therefore, and unlike the relative rigidity of the NPS® tool, the design of the attributes can be adapted to different specific contexts and organizations.

In this specific case, the evaluation using the IPA tool made it possible to identify the strengths and areas for improvement of a particular service (Ábalo et al., Reference Ábalo, Varela and Rial2006), based on the three groups categorized by the NPS® tool (detractors, passives, and promoters). Client segmentation has been a procedure used in various studies evaluated with the IPA methodology, such as the one conducted by León-Quismondo et al. at an equestrian event (Reference León-Quismondo, García-Unanue and Burillo2020) or the one by Lara-Bocanegra et al. at a specialized center for tennis sport technification (Lara-Bocanegra et al., Reference Lara-Bocanegra, Bohórquez and García-Fernández2022). However, in this study, the same participants who evaluated using the NPS® tool subsequently assessed a series of attributes using the IPA tool. No references were found in the literature that employed the same sample of participants for evaluation with two different tools, thus contributing a novel study to the specific literature on sports services.

The results show how the placement of different attributes varies depending on each group, a result of assigning different levels of importance and evaluation according to whether the participants are detractors, passives, or promoters. This situation allows the organization to adopt a service management strategy with differentiated action plans that facilitate targeting each group of users. While the results showed that several attributes were considered the most important for all three groups (‘Cleaning’, ‘Incident_resolution’, and ‘FR_equipment’), the highest ratings focused on different attributes (‘Att_RS’, ‘Center_schedule’, ‘Att_FR’). The attribute ‘Cleaning’ was the only one among the most important that also received a higher rating. This attribute holds significant sensitivity for users of sports facilities and services, as it involves the use of equipment or locker room areas. However, this result contrasts with the negative discrepancy found in the study by León-Quismondo et al. (Reference León-Quismondo, García-Unanue and Burillo2020), conducted in fitness centers, and in the study by Lara-Bocanegra et al. (Reference Lara-Bocanegra, Bohórquez and García-Fernández2022), applied to a specialized center for tennis sport technification.

Considering that the number of attributes with an importance score higher than 4 was generally low, decreasing from detractors (four attributes) to promoters (two attributes), the favorable discrepancies in evaluation increased from detractors to passives, and from passives to promoters, rising from 3 to 6, respectively. This result indicates a high level of user demand, even within the promoter group. This is reflected in the graphical representation for the three groups, where despite a shift toward the quadrant aimed at maintaining good performance for a series of attributes (e.g., ‘Incident_resolution’, ‘FR_equipment’, ‘Att_FR’, ‘Cleaning’), as a result of higher ratings from detractors to promoters, most attributes remain in the area designated for focusing efforts, although the level of discrepancy decreases from detractors to promoters. With the exception of the attribute ‘Att_RS’, the other two attributes related to the organization’s staff (‘Incident_resolution’, ‘Att_FR’) are located in the area designated for focusing efforts. The same applies to more tangible elements (e.g., ‘FR_equipment’ and ‘Center_schedule’) and the activity offerings (‘GA_schedule’), aspects commonly employed in the dimensions of employees, facilities, and programs, respectively, in studies evaluating perceived quality conducted in the fitness industry (e.g., Gálvez-Ruiz, Boleto-Rosado, & Romero-Galisteo, Reference Gálvez-Ruiz, Boleto-Rosado and Romero-Galisteo2015; García-Fernández, Gálvez-Ruiz, Vélez-Colón, Ortega-Gutiérrez, & Fernández-Gavira, Reference García-Fernández, Gálvez-Ruiz, Vélez-Colón, Ortega-Gutiérrez and Fernández-Gavira2018; Montero-Vieira & Ferreira, Reference Montero-Vieira and Ferreira2018; Walker, Farren, Dotterweich, Gould, & Walker, Reference Walker, Farren, Dotterweich, Gould and Walker2017). Depending on the specific context, these aspects have been shown to carry different weight in quality assessments.

In conclusion, the use of the IPA tool for evaluating users of sports centers facilitates the collection of information on a series of attributes that are critical for the organization, thereby providing a strategic orientation that aids in the development of action plans aimed at improving relevant aspects within the value proposition and optimizing available resources. However, as the process requires two responses for each evaluated attribute, it is essential that the implementation of this tool adheres to criteria of aesthetics (gestural design and visual appeal) and functionality (user experience) to ensure broad participation in a simple and efficient manner.

Practical implications

The results obtained in this study have significant implications for sports services management, for managers of sports facilities. Firstly, the flexibility of the IPA tool in designing attributes contrasts with the rigidity of the NPS® tool. In this regard, developing the IPA tool requires an internal analysis to determine which attributes to include based on the specific context. The appropriateness of these attributes will provide relevant information for an adequate assessment of their performance and, consequently, better optimization of the resources employed by the organization. Secondly, the results obtained from a continuous evaluation will allow for a deeper understanding of the organization’s value proposition, understanding that said proposition must evolve alongside users, trends, service offerings, equipment, and other factors. As a result, it provides greater attention and control over service delivery and the processes involved. Thirdly, identifying areas for improvement (discrepancies between importance and evaluation) will enable the development of specific action plans. Depending on the particular attribute, these plans will facilitate and encourage collaboration among different members of the team to establish actions aimed at maintaining or improving processes. These actions could include communication initiatives, process modifications, the introduction of new services, etc. Given the flexible nature of the tool and the periodicity of its application, these measures could positively impact the workplace environment. Finally, fourthly, the combination of these two tools could be very useful for sports club managers as it would allow them to improve service as well as customer experience, thus boosting customer loyalty. This increase in loyalty is a key factor for success and competitive advantage in such a competitive sector.

In summary, managers need to favor innovative and creative approaches to problem solving (Ratten, Reference Ratten2024), and this combination of NPS and IPA approach can be of great help for enhancing sports service management.

Limitations and future directions

Among the limitations encountered in developing this study, the first is the lack of generalization of the results, as they were applied solely to one sports center. In this regard, and related to this limitation, there is significant complexity in obtaining data on NPS® tool evaluations over such a broad timeframe, as well as in securing the organization’s willingness to adopt an evaluation method unfamiliar to them. This also required the participation of staff members to develop the attributes. Therefore, as a future direction, the attributes of the designed tool could be provided to other work teams within the same organization (which operates sports centers in different cities across Spain) to refine the tool with potential new attributes, provided these are applicable to all the organization’s sports facilities. In a subsequent phase, the same evaluation process could then be conducted in other centers. This would undoubtedly offer the opportunity to identify areas for improvement and establish actionable plans applicable across the company. Additionally, the conclusions may be limited by the type of organization used in this study. Therefore, future studies could explore the attributes to be used in other business models (e.g., public, low-cost, boutique, etc.). Secondly, there was a limited sample of participants who responded to the IPA tool. The ease and speed of responding to the NPS® tool’s single question (rated on a scale of 0–10) contrasts with the IPA tool, which requires two responses for each included attribute (one for importance and one for evaluation). As a future direction, subsequent studies could integrate the IPA tool into the organization’s app, incorporating an attractive design to encourage participation. Additionally, to maintain the use of both tools, the IPA evaluation could be activated after a specific period of using the NPS® tool (e.g., 5 months of NPS® usage followed by 1 month of IPA usage). This approach would enable periodic evaluations, allowing for the monitoring of attribute evolution and the effectiveness of action plans. However, this would necessitate the inclusion of specific inclusion and exclusion criteria in the app. Lastly, a larger sample of participants for the IPA tool, combined with the inclusion of basic sociodemographic information, would allow for better segmentation when analyzing results and establishing action plans. In this regard, the study by Jiménez-Jiménez et al. (Reference Jiménez-Jiménez, Vidal-Vidaplana, Núñez-Sánchez and Faus2024) demonstrates that different sociodemographic variables can influence user perceptions, although they note a gap in the literature regarding variables such as user seniority, prior registration, or frequency of attendance, for example.

Finally, this study also provides a starting point for future research exploring the intersection of sports management and emerging technologies. As technological advancements shape the sports industry, future studies could examine how tools like artificial intelligence, data analytics, and mobile platforms can improve service quality and customer satisfaction. Technological innovation plays a crucial role in the sports industry, as organizations face increasing competition, the integration of technology is becoming essential for improving operations and enhancing service delivery. Therefore, combining technology with innovation offers a strategic advantage, and future research in this area is essential for understanding its full impact on sports management, particularly as the industry continues to evolve and adapt to new technological trends (Ratten, Reference Ratten and Ratten2019). In summary, exploring the potential challenges these technologies present for both practitioners and researchers would offer important perspectives.