MAXIMUM POTENTIAL SCORE (MPS): AN OPERATING MODEL FOR A SUCCESSFUL CUSTOMER-FOCUSED STRATEGY

Abstract

One of marketers' chief objectives is to achieve customer loyalty, which is a key factor for profitable growth. Therefore, they need to develop a strategy that attracts and maintains customers, giving them adequate motives, both tangible (prices and promotions) and intangible (personalized service and treatment), to satisfy a customer and make him loyal to the company. Finding a way to accurately measure satisfaction and customer loyalty is very important. With regard to typical Relationship Marketing measures, we can consider listening to customers, which can help to achieve a competitive sustainable advantage. Customer satisfaction surveys are essential tools for listening to customers. Short questionnaires have gained considerable acceptance among marketers as a means to achieve a customer satisfaction measure. Our research provides an indication of the benefits of a short questionnaire (one/three questions). We find that the number of questions survey is significantly related to the participation in the survey (Net Promoter Score) or NPS. We also prove that a the three question survey is more likely to have more participants than a traditional survey (Maximum Potential Score or MPS). Our main goal is to analyse one method as a potential predictor of customer loyalty. Using surveys, we attempt to empirically establish the causal factors in determining the satisfaction of customers. This paper describes a maximum potential operating model that captures with a three questions survey, important elements for a successful customer-focused strategy. MPS may give us lower participation rates than NPS but important information that helps to convert unhappy customers or just satisfied customers, into loyal customers.

Headnote

ABSTRACT: One of marketers' chief objectives is to achieve customer loyalty, which is a key factor for profitable growth. Therefore, they need to develop a strategy that attracts and maintains customers, giving them adequate motives, both tangible (prices and promotions) and intangible (personalized service and treatment), to satisfy a customer and make him loyal to the company. Finding a way to accurately measure satisfaction and customer loyalty is very important. With regard to typical Relationship Marketing measures, we can consider listening to customers, which can help to achieve a competitive sustainable advantage. Customer satisfaction surveys are essential tools for listening to customers. Short questionnaires have gained considerable acceptance among marketers as a means to achieve a customer satisfaction measure. Our research provides an indication of the benefits of a short questionnaire (one/three questions). We find that the number of questions survey is significantly related to the participation in the survey (Net Promoter Score) or NPS. We also prove that a the three question survey is more likely to have more participants than a traditional survey (Maximum Potential Score or MPS). Our main goal is to analyse one method as a potential predictor of customer loyalty. Using surveys, we attempt to empirically establish the causal factors in determining the satisfaction of customers. This paper describes a maximum potential operating model that captures with a three questions survey, important elements for a successful customer-focused strategy. MPS may give us lower participation rates than NPS but important information that helps to convert unhappy customers or just satisfied customers, into loyal customers.

Keywords: Relationship Marketing, Net Promoter Score (NPS), Maximum Potential Score (MPS), customer-focused strategy, customer satisfaction survey.

RESUMEN: Uno de los principales objetivos de los responsables de marketing de las empresas es lograr alcanzar la lealtad del cliente, sin duda, un factor clave para el crecimiento rentable de las mismas. Por tanto, necesitan desarrollar una estrategia que atraiga y mantenga a los clientes, dándoles motivos adecuados, tanto tangibles (precios y promociones) como intangibles (servicio y trato personalizado), para satisfacerlos y hacerlos leales a la empresa. Por consiguiente, encontrar una manera de medir con precisión la satisfacción y fidelidad de los clientes es muy importante. Las encuestas de satisfacción de los clientes son herramientas esenciales para escuchar a los clientes. Los cuestionarios cortos tienen un alto grado de aceptación como instrumento de medida del grado de satisfacción del cliente. Nuestra investigación proporciona una idea de los beneficios de un breve cuestionario (uno / tres preguntas). En este sentido, vemos como el número de cuestiones de una encuesta está significativamente relacionado con la participación en la encuesta (Net Promoter Score) o NPS. También demostramos que un cuestionario de tres preguntas es más probable que tengan más participantes que las encuestas tradicionales. Nuestro objetivo principal es analizar un método de análisis para predecir el potencial de la lealtad del cliente. Para ello, tratamos de establecer empíricamente los factores que determinan la satisfacción de los clientes. Este artículo describe un modelo para capturar con tres cuestiones, los elementos principales de una estrategia exitosa centrada en el cliente. Maximum Potential Score o MPS nos puede dar tasas de participación más baja que (Net Promoter Score) o NPS (encuestas de una sola pregunta) pero nos ofrecerá información importante que ayudará a convertir a los clientes insatisfechos e incluso a los satisfechos, en clientes fieles.

Palabras clave: Marketing Relacional, Net Promoter Score, Maximum Potential Score, estrategia enfocada al consumidor, encuesta satisfacción cliente.

1. Introduction

1.1. Relationship marketing

Relationship Marketing is an area of research, which, currently, is of great importance from an academic point of view as well as from the standpoint of daily management practice. There is a new competitive environment with fresh challenges caused by markets maturing and fragmenting, customers becoming more demanding and competition becoming fiercer. To meet these challenges, it is essential to win over new customers and retain them, focusing on long-term relationships and customer loyalty. Accordingly, academic researchers have begun to study loyalty.

In this situation, it is essential to carry out academic and empirical research that allows results to be obtained and then applied in the management area. The goal of Relationship Marketing is the maximization of loyalty, within a set of annual profitability restrictions, aiming at the achievement of an increase in the long-term value of the company. Typical measures taken are listening to customers, individualized communication, disinterested concern, or individualized products. Their aim is to create compromise and trust, which has an effect on purchase behaviour and increase mutual satisfaction between companies and customers, leading to long-term relationships, customer loyalty and sustainable competitive advantage.

In the area of customer management and according to the Relationship Marketing philosophy, we also must emphasize other measures such as: use the customers' opinions to make them loyal and to offer them service guarantees that generate customer confidence.

Economic literature in this field very often puts stress on companies' ability to choose from different strategic alternatives, highlighting those that focus on market participation. Concern for market participation is linked to attracting new customers due to market growth and increased participation. Main features of a relationship marketing strategy are set out in Figure 1.

With regard to typical Relationship Marketing measures, we can consider listening to customers, where the importance of collecting information from each customer to discover their opinion, attitude and behaviour towards the company, can help to achieve a competitive sustainable advantage. Listening to customers, through links and reaction speed to achieve a competitive sustainable advantage and customer loyalty:

a) The established relationship between the company and its customers creates links that serve as a shield against the arrival of new competitors.

b) Intimate customer knowledge will help the company react in time and avoid losing its group of customers.

1.2. Satisfaction, loyalty and growth

High customer loyalty is one of the most important indicators of good performance in companies. Since customer satisfaction is directly linked to customer loyalty, it is not the same. Satisfaction relates to the results of a process; loyalty relates to a relationship-one that can actually survive a negative product or service process." (Bleuel, 2003). In other words, customer loyalty can safely predict the degree to which repeat sales will occur, while customer satisfaction cannot.

Because loyalty is so important to profitable growth, measuring and managing it makes good sense. Unfortunately, existing approaches have not proved to be very effective (Reichheld and Markey, 2011).

Many of the published studies of loyalty have been conducted in Europe (Mauri, 2003; Wright and Sparks, 1999; Worthington and Hallswarth, 1999; Worthington, 1996). Behaviorally oriented researchers like Soman (1998) and Kivetz and Simonson (2002) have studied the effect of incentives on customers' decisions. Numerous studies have pointed out effective means of generating customer loyalty delighting customers (Lee, Lee and Feick, 2001; Oliver, 1999) or delivering superior value derived from excellent services and quality products (Parasuraman and Grewal, 2000). Zhang, Krishna, and Dhar (2000), Kim, Shi and Srinivasan (2001), and Kopalle and Neslin (2003) have proposed analytical models to study the impact of loyalty strategies.

Although empirical research on customer loyalty is not extensive (Bellizzi and Bristol, 2004), it has long been regarded as an important goal (Reichheld and Schefter, 2000). The method seems to provide good results, above all because it benefits the better consumers of a specific brand (Uncles, Dowling and Hammond, 2003).

Field studies show that 77% of sales are due to the 30% of the most loyal customers and that it is usually much more expensive to attract a new customer than it is to keep an old one (Barroso and Martín 1999). Therefore, it is to marketers' advantage to get to know the customers better, to communicate with them more often, and to achieve a degree of loyalty that ensures a profit. In face of this situation, it is worth for marketers to consider loyalty strategies.

This kind of long-term relationship can benefit customers as well as marketers (Buchanan and Gillies, 1990; Reichheld and Kenny, 1990; Reicheld and Sasser, 1990). For the relationship to be mutually beneficial, customers must be able to clearly identify what adds value for them. Customers will not engage with that that does not add value to their consumption experience. One of the objectives of this paper is to shed some light into the needs that are preferred by customers.

Research has linked survey responses to actual customer behavior and ultimately with company growth. An entire approach to customer surveys, is based on simplicity that directly links to a company's result (Reichheld, 2003). Reichheld introduced the idea of a Net Promoter Score (NPS), a loyalty metric, where a single survey question can, in fact, serve as a useful predictor of growth. But the question is not about customer satisfaction or even loyalty. Rather it is about customer's willingness to recommend a product or service to someone else. In fact, in most of the industries the percentage of customers who were enthusiastic enough to refer a friend or colleague-perhaps the strongest sign of customer loyaltycorrelated directly differences in growth rates among competitors (Reichheld, 2003).

Firstly, this paper presents the results of one study that investigates the opinion of consumers in two countries with respect to different kind of surveys. Secondly, an additional contribution of our research to the extant literature (Dréze and Hoch, 1998; Sharp and Sharp, 1997; Lewis, 2004; Bellizzi and Bristol, 2004; Reichheld and Markey, 2011) is that we investigate a model that complements the net promoter score to help companies to convert unhappy customers or just satisfied customers into loyal customers.

We analyze the degree of influence of a number of questions on the propensity to participate or not in surveys. We also identify a three question survey that once assumed the number of respondents may be lower, the information we received can be of great value for marketers attempting to identify the reason why the company or brand cannot increase the loyal customer rate. The main goal is to analyse the opinion of the target sample toward customer satisfaction in the company's field. After the necessary data had been gathered, it has been subjected to a statistical process, in order to discover the current situation. The results allow us to know the Net Promoter Score and the possible ways of making this score higher. Thus, we are in a position to identify what the growth potential of the Net Promoter Score is (Maximum Potential Score).

2. Survey rate and survey lengh

Customer satisfaction surveys are essential tools for listening to customers. It is generally assumed that questionnaire length has a significant effect on survey response rate. It is one of the most frequent reasons sample members give when refusing to participate in a survey. In face-to-face surveys 61% of all refusals could be due to anticipated length (Burchell and Marsh, 1992). It is really important to do as much as possible to reduce nonresponse and encourage an adequate response rate (Alreck and Settle, 1995).

According to survey length and, before we present and analyze our model, our desired goals from the information to be gathered are as follows:

1. Examine the propensity of customers to answer a survey

2. Analysis of the degree of satisfaction of the target customers and customer loyalty.

We present the results of two studies that investigate the opinion of consumers in two countries with respect to different kind of surveys (long questionnaire/short questionnaire): study 1 (U.S. sample) and 2 (Spanish sample).

2.1. Study 1: United States

Method 1: Long questionnaire

The study was based on a survey of 280 consumers carried out in a major U.S. metropolitan area. Respondents were intercepted in the downtown area and asked to fill out a survey about customer satisfaction. The survey included items regarding individuals' shopping frequency, attitude toward shopping, loyalty card possession and use, as well as the card's perceived influence on customer loyalty. The survey also included socio-economic variables such as age and education level. The methodology for the collection of information has been the personal opinion poll. The poll was made up of "closed questions", according to the aims of the research. The information requested was about the degree of satisfaction toward the service. Respondents' average was 6%. A total of 71% of the sample reported was satisfied with the service. Only 11% consider themselves as loyal customers.

Method 2: Short questionnaire

The study was based on a 3 questions survey carried out in a major U.S. metropolitan area. Respondents were intercepted in the downtown area and asked to fill out a survey. The survey included only 3 questions regarding customer satisfaction. The information requested was about the degree of satisfaction toward the company and loyalty. Respondents' average was 21%. A total of 78% of the sample reported was satisfied with the company. Only 15% consider themselves as loyal customers. To validate the findings of study 1, we conducted a second study in a different country (Spain).

2.2. Study 2: Spain

Method 1: Long questionnaire

The method was similar to study 1. A survey of 260 consumers was carried out in a major Spanish metropolitan area. Respondents were intercepted in the downtown area and asked to fill out a survey. The survey included items regarding loyalty. The survey also included three of the demographic variables we found to be significant predictors of loyalty card possession in study 1 (age, education, and location of residence). Respondents' average was 9%. A total of 69% of the sample reported was satisfied with the service. Only 14% consider themselves as loyal customers.

Method 2: Short questionnaire

A 3 questions survey was carried out in a major Spanish metropolitan area. Respondents were intercepted in the downtown area. Respondents' average was 28%. A total of 74% of the sample reported was satisfied with the company. Only 17% reported they were loyal customers to the company.

2.3. Results and discussion

The influence of the survey length on the decision of answering a survey is high and customer satisfaction is rarely sufficient by itself to generate loyalty if other choices are open to the customer.

The percentage of respondents is especially high when the survey is short (21% - 28%). Respondents' average was 6% and 9% when we used a traditional survey. A significant percentage of the sample (69% -78%) is satisfied with the company or brand.

Most interviewees who were satisfied do not consider themselves loyal to the company or brand. The percentage of loyal people is much lower than the mean of satisfied people. More precisely, 11% -15% of the people from the US study, answer in a positive way. In other words, they consider themselves loyal customers. This percentage is lower than the average of respondents who were satisfied with the company or brand (71% - 78%).

In the Spanish case, 14% -17% of the people revealed they consider themselves loyal to the company. This percentage is lower than the average of the satisfied interviewees (69% - 74%).

The validity of our findings is confirmed because we replicate them across countries: study 2 (Spanish sample) provided similar results to study 1 (U.S. sample).

3. Net promoter score, or NPS® and maximum potential score or MPS®

3.1. Net Promoter Score (NPS®)

Frederick Reichheld (2003) introduced the idea of a Net Promoter Score (NPS). NPS is a loyalty metric where customers are surveyed on one simple question as a basis for profitably measuring and managing customer loyalty. By substituting a single question for the complex box of the typical customer satisfaction survey, companies can actually put consumer survey results to use and focus employees on the task of stimulating growth (Reichheld, 2003). They are asked to rate on an 11-point scale the likelihood of recommending the company or brand to a friend or colleague.

Reichheld continued to spread that influential message (e.g. Reichheld 2004, 2006a, 2006b, 2006c) independent from other researchers (Marsden, Samson and Upton, 2005). The philosophy behind NPS, is based on the perspective that every company's customers can be divided based on the rating into three categories: Promoters, Passives, and Detractors. Promoters are those who respond with a score of 9 or 10 and are considered loyal enthusiasts who will keep buying and refer others, increasing revenues and profits, fueling growth. Loyalty can be measured by the number of "net promoters" a company has (Reichheld, 2004). Passives (score 7-8) are satisfied but they are not enthusiastic customers who are vulnerable to competitive companies or brands. Finally, Detractors (score 0-6) are unhappy customers. They can damage the company or brand through negative word-of-mouth.

This index ranging from -100 to 100 establish a customer's satisfaction with a product/service, and their likelihood to recommend a company's products or services to others. It is used as a measure of customer's overall satisfaction and the customer's loyalty to the company or brand. Reichheld calculates the Net-Promoter Score by subtracting the percentage of detractors from the percentage of promoters.

Convert passives or detractors into promoters is the ultimate objective for increased profits or revenues. Reichheld is a powerful voice in the area of loyalty, his ideas about NPS is a sufficient basis for many companies. For other companies and researchers (Grisaffe, 2007; Schneider et al. 2007), this score does not provide all the information needed to achieve success. Some authors believe that "A single item question is much less accurate and more volatile than an index of 3 questions" (Hill, Roche and Allen, 2007).

Because, the ultimate objective here is to convert customers who were less than happy or unimpressed into promoters, we create a new model: Maximum Potential Score that captures with a three questions survey, the causal factors to move the one number upward, improve and help to provide the best customer experience possible.

3.2. Maximum Potential Score (MPS®)

As we have confirmed throughout our study, the customer satisfaction surveys tend to be completed to a lesser degree according to the number of questions asked to the customers. The reasons for this evidence are varied. The waste of time experienced by the survey respondents, the lack of a direct reward for their effort and even the wish to preserve their privacy are factors that lead them to refuse to participate in this kind of surveys as the amount of questions increases. And, therefore, the participation ratio in customer satisfaction surveys quickly decreases.

On the other hand, it must be noticed that the longer the surveys are, the more information they provide. Nevertheless, such theoretical evidence fails to prove itself in practice when we take the participation ratio. As a consequence, a "trade off" is established between the amount of information asked to the customer and the number of customers who actually complete the survey.

The NPS has become a world reference in measuring customer satisfaction due to the fact that it has managed to reach a maximum ratio of customer participation by summarizing in just one sentence what NPS considers most important: the customer's tendency to act as a company promoter. On the one hand, it measures the fundamental facts; on the other hand, it only asks one question.

Furthermore, it uses such a simple algorithm to calculate the indicator that it may give a sensation of information loss. On a scale from 0 to 10, in other words, out of 11 possible answers, they only take into account three possibilities, classifying the 11 answers into three categories: promoters (10,9), neutral (8,7) and opponents (6,5,4,3,2,1,0). The algorithm responds really well to the concept to be measured, that is, the customer's tendency to act as a company promoter which, as a result, requires a high degree of satisfaction (9, 10).

However, we assume that the NPS only measures the current state of the company. That is to say, it is a great tool for describing the BE, but it does not go into the world of the MUST BE. The NPS is a truly useful tool when it comes to assessing the current state, and so being able to compare ourselves to other companies or our own in different stages over the course of time.

The NPS gives up any attempt of knowing the actions that would improve the situation of the company in the future. This weak point is the one we intend to resolve with the concept of Maximum Potential Score (MPS). As we have previously indicated, it will be necessary to increase the number of questions for that purpose and, consequently, to decrease the ratio of customer participation as well. Yet, just as it is the case with the NPS, by finding a Paretian combination for a question, we establish a Paretian solution with just three questions, in such a way that the amount of information gathered is the highest possible.

From a conceptual perspective, the MPS can be considered as the gradient of NPS, meaning that it is constituted by the first partial derivatives of NPS with respect to the most relevant and direct actions the company can take so as to improve their service. The derivative is the mathematical concept through which we know the increase taking place in a function when we elevate the value of one of the variables on which it depends. When we elevate the value of just one variable, while keeping the rest values constant, we are dealing with the partial derivative in relation to that variable. Lastly, when we gather all the variables together, we establish the gradient of the function.

The mission of the MPS is not merely to find out what the current state of the company is, but to know which actions would help it improve as well as to determine which ones will enable us to achieve the maximum NPS. That is, by knowing the gradient of the NPS and according to its result, we can introduce improvements in those fields where the derivative is higher.

3.2.1. MPS Questions

Since the MPS is the gradient of the well-known NPS, the questions to be asked in order to calculate it include the same question employed by the NPS. Thus, the questions would be:

1. How likely is it that you would recommend [your company] to a friend or colleague?

For this first question, we will calculate the NPS as we know it. It will serve as evaluation of our initial situation/starting point. The possible answers will be, just like in NPS, any number between 0 and 10, both inclusive.

2. How would you improve our services? Select one option.

In this second question, we will make the customer opt for one of the options suggested for the improvement of the company services. He or she will have to choose only one action. We must bear in mind that we are trying to discover the partial derivatives of the NPS, which implies that we will improve just one of the aspects to be improved, keeping the others constant.

The company must have chosen the aspects of their offered services that need to be analysed previously, giving the client no more than 4 options.

3. Once the improvement is done, how likely is that you would recommend [your company] to a friend or colleague?

Finally, for the third question, we will establish the hypothesis that the chosen improvements have been properly introduced and so we will ask the first question again. The result will be the NPS potential of the company provided it changes each one of the aspects taken into account in the second question. The answer, as stated before, will be a number between 0 and 10.

3.2.2. Calculating de MPS

The calculation of the MPS is made by considering the three answers, each of which gives way to a 3option vector. We would proceed as follows:

1. Calculation of the NPS

For the first question, as commented in previous sections, we will calculate the NPS as we know it. Therefore, we will organise the answers into three blocks:

a. Promoters. They are the customers who have answered with a 9 or a 10 to the question.

b. Neutrals. They are the customers who have answered with a 7 or 8 to the question.

c. Opponents. They are the rest of the participants.

The vector of options of each customer would have its first component: the block where he or she stands according to the number of the answer. Let's assume the answer has been 8, so the vector would be: (Netral, , ). Note that the second and third components are not still known.

2. How would you improve our services? Select one option.

In the second question, the company has chosen no more than four actions to improve the services offered to customers. The respondent can choose only one of them. These options are useful to determine the partial derivatives that the company wants to analyse. We will set 4 possible answers under the numbers 1, 2, 3 and 4.

The vector of options would already be formed by two components: the NPS and the option chosen in the second question. Let's assume it is the first one. The vector would be: (Neutral, 1, ). Note that the third component is not still known.

3. In the third question, we get an answer between 0 and 10 again, which would be the result of a hypothetical NPS had we resolved the option chosen in the second question. Consequently, the calculation method is exactly the same as that of the first question.

We have completed the vector of answers for each customer with the three components; if we assume that the customer answers the third question with a 9, he or she would become a promoter and the vector of his or her answers would be the following: (Neutral, 1, Promoter)

Once we have a results matrix composed of the vectors of each customer, we will move on to calculate the Maximum Potential Score (MPS) in three steps:

STEP 1. We calculate the NPS based on the first answers provided by the customer.

The percentage of customers divided by their total is calculated for each one of the groups. Lastly, the percentage of opponents is subtracted from that of the promoters, without taking into account the percentage of neutrals. As a result, we will obtain a percentage of between - 100% and 100%, that is, the possible cases in which all the clients were opponents or all of them were promoters, respectively.

These first calculations give us the starting point or initial situation of the company.

STEP 2. We will select the customers who have been upgraded to a higher category, whether it is from neutral to promoter, from opponent to neutral or from opponent to promoter. Such observations must be divided into four groups, depending on the answer given to the second question.

STEP 3. We will calculate a hypothetical NPS (HNPS) that actually is a regular NPS into which we incorporate the new answers of just one group. This results in 4 HNPS, the hypothetical NPS in case we resolved the 4 options of the second question separately

[HNPS(1), HNPS(2), HNPS(3), HNPS(4)].

STEP 4. Lastly, we will select the highest HNPS obtained in (III)

Max [HNPS(1), HNPS(2), HNPS(3), HNPS(4)].

When choosing the highest HNPS, we will distinguish between the times when the same number of customers has been upgraded but not all of them have done so by selecting the same option.

Let us see an example of two opposite cases: in the first one, 8% of the customers are upgraded to a higher category, but in such a way that we observe how 2% selects option 1, 2% selects option 2, another 2 % selects option 3 and the last 2% selects option 4. The improvement is scattered among the alternatives, and so the MPS should be lower.

In the second example, the number of customers being upgraded to a higher category is identical yet, in this case, all of them do it after choosing the same option as the rest in the second question. Even when we are talking about the same degree of improvement as in the previous case, customers are identifying unanimously the kind of action that would potentially improve their NPS this time. In our view, the MPS must be higher so that such characteristics are shown.

In the second case, the MPS has a value of 18%. This indicator will give us the growth potential of the NPS (from 10 to 18) and, additionally, the improvement option that can provide us with it.

Anyhow, the system does not only provide the company (MPS) with a number, but also with a HNPS vector that might help prioritise the actions for improvements implemented in their services, according to the output (the HNPS) and the means required to perform each action. This way, an efficiency test can be set for each one of the improvements.

The remaining challenge ahead is to create a method for establishing the three questions composing the MPS in a way that the expected reduction of the number of answers given by customers is as slight as possible.

4. Maximum Potential Score. An empirical Analysis

The study was based on a 1-3 questions survey carried out in a Spanish metropolitan area (North of Spain). Respondents were intercepted in the downtown area and asked to fill out a survey. The survey included only 1-3 questions regarding customer satisfaction:

1-How likely is it that you would recommend [the company] to a friend or colleague?

2-How would you improve our services? Select one option.

3-Once the improvement is done, how likely is that you would recommend [the company] to a friend or colleague?

The information requested was about MPS questions toward the company. Respondents' average was (73NPS, 84MPS). Around 70% of the sample reported was very satisfied with the company (promoters), less than 1% detractors.

To validate the findings of study 1, we conducted a second study in a different area (South of Spain).

The study again was based on a 1-3 questions survey carried out in a Spanish metropolitan area (South of Spain). Respondents were intercepted in the downtown area and asked to fill out a survey. The survey included again only 1-3 questions regarding customer satisfaction. The information requested was about MPS questions toward the company.

Respondents' average was (34NPS, 50MPS). A total of 50% of the sample reported was very satisfied with the company (promoters). Only 20% detractors.

Department Store versus Supermarket

The study was based on a survey of 530 consumers (235 Department Store, 330 Supermarket).

The study was carried out in a Spanish metropolitan area close to a Department Store. Respondents' average in this case was (50NPS, 65MPS). The study was carried out afterwards in a Spanish metropolitan area close to a Supermarket. Respondents' average was (77NPS, 87MPS).

As we said, this method does not only provide the company (MPS) with a number, but also with an information that might help prioritise the actions for improvements implemented in their services, according to the output.

5. Conclusions

Our studies provide a reason why marketers should use short questionnaires. The percentage of respondents is especially high when the survey is short (21-28%). Respondents' average was 6% and 9% when we used a traditional survey. The validity of our findings is confirmed because we replicate them across various countries: study 2 (Spanish sample) provided similar results to study 1 (U.S. sample). In the process, we identify that most interviewees who were satisfied do not consider themselves loyal to the company or brand.

The Net Promoter Score is a loyalty simple metric that measures the willingness of customers to recommend a company's products or services to others, illustrates the strength of the organisations engagement with its customers (or employees) and shows the trend in that score over time. Reichheld calculates the Net Promoter Score by subtracting the percentage of detractors from the percentage of promoters. He considers that loyalty can be measured by the number of "net promoters" a company has. But not only is it important to know what the situation is, but also how to improve the number of promoters, gain loyal customers and generate profitable growth. Because the ultimate objective is to convert customers who were less than happy or unimpressed into loyal or promoters who will increase revenues and profits, we create a new model: Maximum Potential Score.

Our results have important implications for marketers. We describe a maximum potential operating model that captures important elements for a successful customer-focused strategy.

This paper contributes to our understanding of a type of marketing strategy that has gained in popularity among a great variety of consumer brands. Simply applying the model does not lead to success. Companies must follow a discipline and create a company culture that drives customer loyalty and profitable growth. This research provides a best practice framework for how companies should collect, and act on customer feedback to optimize benefits.

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