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In 2003 Reichheld published an article in HBR, in which he claims that the net promoter score (NPS), is the only number you need to grow, and the only number you need to manage customer loyalty. The purpose of this paper is to demonstrate that the NPS is inferior to the standard measures of loyalty used by the American Customer Satisfaction Index (ACSI) and EPSI rating.

In 2006 a customer satisfaction survey of the entire insurance sector in Denmark was conducted. The survey design was based on the questionnaires from EPSI rating and ACSI supplemented with insurance-specific questions, consumer sentiment questions and the basic Net Promoter Question. The sample consists of approximately 2,000 observations.

The analyses presented in this paper show that the NPS it not what it claims to be: the one number you need to grow. The NPS is found to be a very poor predictor of both customer loyalty and customer satisfaction. The measure is very sensitive to changes in the underlying distribution, and finally the precision of the NPS was found to be low compared to other measures of loyalty, and it is not possible to predict the NPS categorization and hence it is hard to say precisely, how organizations can influence corporate growth based on the NPS.

The analysis is only conducted on data collected in a Danish business-to-consumer setting. More research is needed to shed light on the performance of the NPS across cultures as well as in a business-to-business setting.

The paper demonstrates the dangers of using the NPS as an input to managerial decision making. Organizations are far better off using a standard customer loyalty measure such as those employed by the ACSI or EPSI instead of the NPS.

Previous studies of the NPS have not replicated the methodology directly. Either there have been differences in scale length or in wording. The authors have constructed an experiment in the Danish insurance industry that answers some of the questions concerning the NPS without the shortcomings that most of the previous studies have suffered from.

This study aims to determine the NPS score of state academic libraries users in Indonesia, the relationship between user loyalty and NPS scores and the relationship between user satisfaction with NPS.

The method used in this research is quantitative explanatory method, which surveyed the relationship between satisfaction, loyalty and NPS variables based on the development of previous studies and existing theories. The population in this study were students visiting the state university library in Surabaya, Indonesia, namely Library A, Library B, Library C and Library D. The total number of samples taken was 200 divided equally to each of the universities, with 50 respondents respectively. Data collection was done with a questionnaire.

The Result shows that NPS value for academic library in Indonesia was 8. (1) The probability value of satisfaction with NPS is 0.18 (greater than 0.01) so H1 is rejected, meaning that satisfaction has no significant effect on NPS, (2) The probability value of satisfaction with loyalty is < 0.01 so that H0 is accepted. This means that satisfaction has a significant effect on loyalty and (3) The probability value of loyalty to NPS is < 0.01 so that H0 is accepted. This indicates that loyalty has a significant effect on NPS.

To get user satisfaction, libraries need to improve facilities and services in accordance with the characteristics and needs of users, so that user expectations will be met and achieve satisfaction. When user satisfaction has been fulfilled, user loyalty to library products will be formed, so the NPS score will increase which is manifested by users recommending the library to others. This research has limitations, namely that the object of research is only in public higher education centers, so for generalization it is necessary to add research objects such as private college libraries, public libraries or school libraries.

Research on loyalty by using NPS has not been done much especially in Indonesia. This study also examines the relationship between satisfaction and loyalty on NPS scores.

Executives need a more advanced tool for examining consumers' loyalty, one that provides a sharper, more precise view. this paper aims to introduce such a tool.

The paper looks at Bain's Net Promoter Score (NPS).

The paper finds that the tool needs to focus not on satisfaction and market share but on consumer advocacy, which is key to creating enthusiastic consumers who come back to buy offerings again and again – and are happy about doing it. Bain's NPS can reveal whether consumers identify emotionally with a brand and feel listened to and understood by the company that makes it. NPS scores help identify groups of consumers who feel well served by your product and groups that do not, whose needs you can then probe further. NPS opens a window into how well mass brands are actually serving profitable consumer segments, as opposed to catering to a statistically “typical” consumer who exists only in theory.

Because NPS scores help uncover determinants of future behavior, they provide a much better basis for spotting product weaknesses, evaluating a brand's health and helping gauge whether new products will succeed.

By producing and evaluating NPS data on a regular basis, organizations can institutionalize a cultural shift, making consumer metrics just as practical and auditable as financial metrics like profit and return on equity. They can make performance in the eyes of consumers just as critical a goal as financial performance.

The purpose of this study is to present and explain a new customer segmentation approach inspired by failure mode and effect analysis (FMEA) which can help classify customers into more accurate segments.

The present study offers a look at the three most commonly used approaches to assessing customer loyalty:net promoter score, loyalty ladder and loyalty matrix. A survey on the quality of restaurant services compares the results of categorizing customers according to these three most frequently used approaches.

A new way of categorizing customers through loyalty priority number (LPN) is proposed. LPN was designed as a major segmentation criterion consisting of customer loyalty rate, frequency of purchase of products or services and value of purchases. Using the proposed approach allows to categorize customers into four more comprehensive groups: random, bronze, silver and gold – according to their loyalty and value to the organization.

Survey will bring a more accurate way of categorizing customers even in those sectors where transaction data are not available. More accurate customer categorization will enable organizations to use targeting tools more effectively and improve product positioning.

The most commonly used categorization approaches such as net promoter score, loyalty ladder or loyalty matrix offer relatively general information about customer groups. The present study combines the benefits of these approaches with the principles of FMEA. The case study not only made it possible to offer a view of the real application of the proposed approach but also made it possible to make a uniform comparison of the accuracy of customer categorization.

The aim of this paper is to examine the effects of the disconfirmation of expectations of crowding and mall accessibility, on stress and two marketing outcomes, satisfaction and promoter scoring.

Data were obtained through two face-to-face surveys from mall shoppers that answered them at two different moments of their shopping experience, before entering the mall and before leaving it. Results are obtained from 230 customers that answered the two questionnaires.

The findings suggest that stress indirectly influences customer promoter scoring through satisfaction, while disconfirmation of expectations influences it directly and indirectly.

These results also suggest that stress and disconfirmation of expectations about crowding and accessibility are important in determining promoter scoring. To reduce stress and increase satisfaction and promoter scoring, managers should focus on exceeding customers' expectations about mall accessibility and on ensuring that customers experience a lower level of crowding than they expected.

The article examines Net Promoter Scoring, an outcome that has attracted managers' attention but little is known about its antecedents. The paper provides evidence of the effect of disconfirmation of expectations and negative emotions on promoter scoring.

Attitudes, perceptions, and intentions of a firm's customers, which can be captured via customer feedback metrics (CFMs), provide valuable information about the state of a firm's customer base. CFMs can help capture the impact of marketing actions on future customer behavior and future firm performance, and thus can help make marketing become more accountable. CFMs have received much attention in marketing research and business practice since the 1970s. In this chapter, we provide a short historical overview of the development of, and research about, CFMs, we classify the different types of CFMs, we highlight the empirical findings of the drivers and consequences of CFMs, and we explore how CFMs can be integrated in a firm's customer dashboard in order to make marketing more accountable. We furthermore explore some of the challenges in accurately measuring CFMs, and in the end of this chapter, we provide information on how to capture CFMs in the age of social listening via modern tools involving text-, voice-, and video-mining.

The purpose of this paper is to evaluate the usability of the National Library of Turkey website developed for all citizens in the country to retrieve information available in a wide range of areas.

The evaluation performed by 57 undergraduate university students involved the identification and analysis of usability problems in the selected website. The assessment process was mainly based on Nielsen’s Heuristics. The data obtained in the evaluation process were enriched using the System Usability Scale (SUS) and the Net Promoter Score (NPS) to conduct a more detailed analysis.

The participants identified many usability problems concerning the evaluated website and considered it as having low usability characteristics. The most violated heuristic item was found to be “consistency and standards” whereas the least violated heuristic item was “match between system and the real world.” The total number of the usability problems in heuristic evaluation correlated significantly and negatively with the SUS and the NPS results indicating that the more participants identified usability problems, the less they considered the website as usable and recommendable.

The participants were not usability experts, however they were selected from among the students who received the Human Computer Interaction course to ensure that they had sufficient information and experience concerning the evaluation of a website with heuristics. Besides, the study was limited to a small number of university students. The implication is that results of this study have potential to guide libraries, which plan to adapt themselves to the digital world by delivering web services, by addressing critical points influencing users’ points of views toward library websites and their usability evaluation result.

Depending on the changes in user habits regarding the retrieval of information, libraries have made considerable investments in web technologies to meet their users’ demands, and recently, digital libraries have begun to take over physical libraries. Users always need to perform tasks efficiently, effectively and satisfactorily when using websites. As one of the most crucial sources of digital materials, library websites are expected to have usable characteristics that satisfactorily meet user requirements. Therefore, the practical implication is that the findings of the study will guide designers, developers and practitioners in the development of library websites.

In the context of usability evaluation of digital libraries, this is the first study to analyze effects of usability problems identified by users during the heuristic inspection on their overall evaluation score and willingness to recommend the website to their friends or colleagues.

The term ‘strategy’ is one of the most frequently used terms in business, and its application in marketing is particularly common. Company strategy, market strategy, marketing strategy, sales strategy, promotion strategy, distribution strategy, low pricing strategy – it would take a long time to list all of them. Although this term is so commonly in use, its definition is not as straightforward and it can be interpreted in different ways. In comparison with tactical decisions, strategy is much more significant for an organisation as it brings long-lasting consequences. It is implemented by higher level managers on a regular basis, and it is based on external, often subjective information, so decisions – especially at the time they are made – are difficult to evaluate.

Taking into consideration the fact that strategy refers to a long-term rather than a short-term period, strategic decisions serve as the basis for undertaking operational activities. However, marketing refers to the market and the competition. It is possible to claim that marketing strategy is trying to find an answer to the question to which path an organisation should follow in order to achieve its goals and objectives. If, for example, a company has a goal to generate a profit of PLN 1 million by selling 100,000 pieces of a product, the market strategy should answer at least the following two questions:

1. Who will be our target group, for example, who will purchase the 100,000 pieces of the product?

2. Why is it us from whom a potential buyer should purchase the product?

Who will be our target group, for example, who will purchase the 100,000 pieces of the product?

Why is it us from whom a potential buyer should purchase the product?

The target market will be defined if a reply to the first question is provided. The second question identifies the foundations of competitive advantage. These two issues, that is, target market and competitive advantage are the strategic marketing issues. You cannot change your target group unexpectedly while competitive advantage is the basis for changing decisions regarding prices, promotions and sales.

This chapter describes the measures of marketing activities which refer to strategic aspects and testify a company’s market position – the measures of the performance of target groups and competitive advantage. Readers’ attention should be also focused on the indices that are less popular in Poland and, therefore, may be underestimated. It seems that some of them, for example, the index of marketing resources allocation and the marketing risk index, provide a lot of valuable information and, at the same time, make it possible to show the value of marketing investments. Their wider use in the near future is only a matter of time.

Marketers' sustainability is highly dependent on providing their customers with a memorable experience. This experience manifests the care taken by marketers while interacting at every stage of customer's journey from need recognition to post-purchase behaviour. Customer experience's (CX) significance demands that it be measured succinctly to monitor it at various levels, beginning at the customer level and extending to the financial outcome of this interaction(s). This study has attempted to conduct the same, by measuring Net Promoter Score of the customers and the financial ramifications of good/bad CX. Evidence of financial implications of good/bad CX has been presented through secondary research. Customer level study was empirically conducted at two well-known retailers of India, one in the footwear category and the other in general merchandise. Finally, some successful examples from the Indian retail sector have been added to highlight the significance and impact of Indian retailers' measures to enhance their customers' experience.

In the transformed information environment, the impact and value of the services are not adequately shown using the traditional library metrics. It needs to be supplemented with user-centered ways of measurement. The paper aims to discuss these issues.

The paper is a case study of the new Finna service and the measurement challenges it presents.

The standards guiding the measurement and evaluation of libraries cannot offer a “cook-book” for the organizations to follow. The paper suggests that as a one possible response to this, the Net Promoter Score can be used as one indicator in measuring the impact of new services.

The findings of the paper are preliminary, because so far there is not a wide experience of the use of NPS in libraries. This calls for further study. The results are encouraging, but more testing is needed with different services.

NPS has not been widely used in libraries before.