Profitable Hotel Guest Management: The Factors Involved in and the Importance of Following a Guest Relationship Approach in the Irish Luxury Hotel Sector

Table of Content

i. table of Figures

ii. Index of tables

iii. Abbreviation

A. Preamble
1. Introduction
1.1. Industry Rationale
1.2. Outline and Methodology

B. Literature Review
2. Objectives of the CRM approach
3. The development of Customer Relationship Management
4. The forms of CRM
4.1. Types of Operational CRM
4.2. Types of Analytical CRM
4.3. Communicative CRM
4.4. Review of Types in CRM and collaborative CRM
5. Perspectives on the Supplier and Customer Relationships
5.1. The role and need for loyal relationships in a commercial context
5.2. The meaning of the relationship factor from the hotel perspective
5.3. The meaning of the relationship factor from the guest/ client perspective
6. Development of Information Technology
6.1. CRM Databases and Database Marketing:
7. The need of segmentation in CRM
7.1. Benefit segmentation
7.2. Calculation method and techniques of customer value
7.2.1. Calculative models
7.2.1.1.Calculative method I: ‘Lost-for-Good’ Model (Jackson, 1985)
7.2.1.2.Calculative method II: Customer lifetime valuation by Dywer (1989)
7.2.1.3.Calculative method III: Customer lifetime model and its application by Berger and Nasr
7.2.1.4.Calculative method IV: Resource allocation model
7.2.1.5.Limitations of the calculative methods
7.2.1.6.Activity-Based Costing/ ABC analysis in CRM
8. Hotel marketing and best practices
8.1. Social Media and CRM in the Hotel sector
9. Service Environment in the Hospitality Industry
9.1. Internal Marketing
9.2. Complaint Management and Service recovery

C. Methodology chapter
10. Empirical Research and techniques
10.1. Research Question:
10.2. Research Problem Area:
10.3. Research Objectives:
10.3.1 .General Objectives:
10.3.2 Specific Objectives
10.3.3. Research Hypothesis
10.4. Significance of the research
10.5. Empirical Research
10.6. Research Methodology and Methods
10.7. Approaches to Research
10.8. Approach to Primary Research
10.9. Data collection method(s):
10.10.Quantitative Research and Qualitative Research
10.11.In-depth Interviews – qualitative research
10.11.1. In-depth interview guide
10.11.2. Logistics of the Interview
10.11.3. Language and Conversation
10.12.Questionnaire – Quantitative research
10.13.Producing the online survey
10.14.Eliminating problems by pre-testing
10.15.Research Population and Sampling
10.16.Ethical Issues
10.17.Limitations of the research
10.18.Analysis and coding

D. Empirical Research in Execution
11. Analysis
12. Conclusion and Recommendation

E. Empirical Research and Hindsight
13. Learning styles
13.1. Reflection on learning
13.2. Learning outcomes
13.3. Writing style
13.4. Project and time management
13.5. Qualitative and quantitative research
13.6. Data analysis
14. Bibliography
15. Appendix
Appendix I. Summary of all parties in the Population
Appendix II.
Appendix III: The meaning of relationships
Appendix IV: Recency, Frequency and Monetary Value Method / (RFM) Method

i. Tables of Figures

Figure 1: Hotel Bedroom Growth 1996-2009 (by Irish Hotel Federation, 2010)

Figure 2: Hotel room Occupancy (by Irish Hotel Federation, 2010)

Figure 3: CRM value chain (by Buttle, 2005)

Figure 4: the transition to relationship marketing (by Christopher, Payne and Ballantyne, 2007)

Figure 5: CRM Components (by author)

Figure 6: Analytical CRM (by author)

Figure 7: Hospitality service and communication system (Lovelock and Wirtz, 2007)

Figure 8: The Wheel of Loyalty (by Lovelook and Wirtz, 2007)

Figure 9 : Framework for Customer Metrics and Their Impact on Financial Performance (by Gupta and Zeithaml, 2006)

Figure 10: Managing the co-creation of value (Payne et al. 2008)

Figure 11: Logical structure of the service and causes of variability (adapted from Edvarsson, 1998) – (by Erto, Vanacore, Staiano, 2011)

Figure 12: Customer Database process (by Rutherford and O'Fallon, 2006)

Figure 13: The Customer Pyramid (by Zeithaml et al., 2001)

Figure 14: Resource allocation mode (by Blattberg and Deighton (1996)

Figure 15: Conceptual model - service employee and service climate influence on customer perception (by Solnet and Paulsen, 2005)

Figure 16: The Service Triangle (by Zeithaml et al., 2008)

Figure 17: Service Profit Chain (by Heskett and Sasser,2010)

Figure 18: The research onion (by Saunders, Lewis and Thornhill, 2006)

Figure 21: Semi Structured and unstructured Interviews (comparison) – (Wengraf ,2001)

Figure 22: Seven steps in research (by Cavehill University, 2010)

Figure 23 Revenues increase with individual customers after implementing a relationship approach.

Figure 24 Loyal customers, by your experience, are also higher spenders.

Figure 25: Your hotel enjoys a higher profit margin from loyal customers.

Figure 26: Which of the following do you implement to keep a relationship with a guest active?

Figure 27: Which practical benefits do you see in the customer retention approach?

Figure 28: Loyal customers, in your experience, are also higher spenders.

Figure 29: Investments in the field of customer satisfaction seem to make your guests more loyal.

Figure 30: Investments in the field of internal marketing seem to increase the quality of service.

Figure 31: Does your hotel have a mission statement?

Figure 32: Does the hotel offer regular training for service employees?

Figure 33: The hotel invests money to continuously train their employees.

Figure 34: Does the hotel facilitate training in one or more of the following?

Figure 35: Employees in our hotel are empowered.

Figure 36: Your employees are able to solve queries and complaints themselves.

Figure 37: Your organization seems to invest into learning and constant improvement.

Figure 38: Your hotel furthers a culture of learning.

Figure 39: The hotel management communicates to your employees to learn from mistakes.

Figure 40: Does the hotel use information from the guest database to estimate the value of a customer?

Figure 41: How does the hotel validate the value of its guests?

Figure 42 Kolb' learning styles - 1984, retrieved from www.businessballs.com

Figure 43: From Transactional to Relationship Marketing

ii. Index of tables

Table 1: GNP in current prices 2007 to 2009 (by Irish Hotel Federation, 2010)

Table 2: Price development in Irish Hotels (by Con Quigley, 2010)

Table 3: Comparison of quantitative and qualitative data — (by White 2005, p.107)

Table 4: Table for determining sample size (Krejcie and Morgan, 1970, p.56)

Table 5: 4 and 5 Star Hotels in Ireland

iii. Abbreviation

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A. Preamble

1. Introduction

Most literature on marketing contains an exhaustive discussion on the topic of relationship marketing and this concept is now well understood by every marketer. However, valuing customer relationships is usually viewed more vaguely as being a general, desirable and virtuous factor. Like many fields in marketing, there has been a failure to justify adopting such an approach based also on its inherent financial control measures. In this increasingly globalised marketplace (the hospitality sector), it can strike as odd that scholars and researchers have overlooked the differences in CRM handling that exist among different cultures.

The aim of this dissertation is to make a contribution to closing the gap between marketing and management perspectives in terms of customer profitability, especially in the luxury hotel sector with regard to their international customer/guest base. The gap is to identify by the management and accounting which customers are profitable and to translate these insights into marketing activities. Companies can control their customer relationships and make sophisticated decisions about which customer relationships should be finished and which are worth retaining, a practice known as Customer Equity.

The objectives of this work include:

- Identify how investment in customer retention create a Return on Investment
- Allocating marketing spending ratios for long-term profitability
- Identify the methods that managers can use to create customer loyalty
- Explain the links between customer loyalty, customer equity and relationship marketing.
- Estimate the role of quality factors within service delivery and after-sales service as above and how they affect customer retention
- Identify the effect of after-sales service as above quality on customers’ expectations and its impact on customer satisfaction

CRM outline is seen by some as an extended database containing useful information about customers that could be used to help extend sales, while others see it as a tool specifically designed for use on a (one-to-one) basis with each of their customers (Peppers and Rogers, 1999).

To implement CRM successfully the TQM, HRM and IT management need to ensure organisational alignment (Reinartz et al., 2004). Building on this statement, Buttle (2004) spells out that: “CRM needs to be established in three layers: companywide, factional and customer facing”.

1.1. Industry Rationale

The Federation of Irish Hotels (Failte-Ireland, 2004) encouraged their members to maintain profitable relationships with their guests. The Irish hotel market needs its international guests and urgent action is needed if the industry is to recover (Tourism Opportunity, 2010). Aiden (2008) points out that: “The Irish hotel sector relies heavily on the domestic economy for much of its room sales. In 1997, 46% of all rooms sold at Irish hotels were to guests of Irish origin, but in 2007 this figure had increased to 60%. This dependence on the domestic market indicates how the current economic climate will have a more significant impact on hotel occupancy levels and, ultimately, turnover than in previous years”. The tourism sector in Ireland has declined as shown in Table 1. There was a decline of 29.65% in the number of overseas visitors between the first quarter of 2008 and the first quarter of 2010 (Irish Hotel Federation, 2010). Table 2 presents how Dublin hotels have been affected since 2008, particularly the Average Day Rate (ADR) and the effects on the Revenue Per Available Room (RevPAR) (Con Quigley, 2010).

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Table 1: GNP in current prices 2007 to 2009 (by Irish Hotel Federation, 2010)

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Table 2: Price development in Irish Hotels (by Con Quigley, 2010)

Furthermore, 5.6 million overseas visitors were estimated to have arrived in 2010. Down from 6.5 million in 2009 and 2.2 million down from 7.7 million arrivals in 2007 (Tourism Opportunity, 2010). However, the four- and five-star hotel sector has been able to maintain its guest numbers (McEnroe, 2010). One of the reasons for this is that these hotels have focused on individual guests from abroad. McEnroe, from the Irish Examiner, reported the following about Irish hotels in December 2010: “While many have taken measures to reduce costs, some hotels have also introduced loyalty cards and points systems to encourage repeat business”. The report continues by adding: “While the luxury hotels have seen corporate bookings fall and reduced staff working hours, it started a loyalty card for customers last month”. Nevertheless, the stated data can mask an underlying issue, for the long-term performance of the industry in Ireland. One needs to bear in mind that the guests become more knowledgeable and critical and post their experience on travel sites like “Tripadvisor” (www.tripadvisor.co.uk / www.tripadvisor.com) .1 Social Media). The goal of focussing on customer retention appears to be the solution for profitability, even while the overall market section in which they operate is suffering. During the Celtic Tiger the number of rooms increased, while the demand for such decreased since the recession (see figure xxx) (Irish Hotel federation, 2010).

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Figure 1: Hotel Bedroom Growth 1996-2009 (by Irish Hotel Federation, 2010)

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Figure 2: Hotel room Occupancy (by Irish Hotel Federation, 2010)

An oversupply of 15 000 beds can be reported (RTE news, 2009). The closure of leading hotels helped to decrease the oversupply (CityOccupancy Hotel Index by Savills, 2010). One reason for this oversupply is that hotels were able to secure a huge or full tax relief for their cost of capital for property (Brennan, 2010). The oversupplies lead to a market-wide battle on Average Daily Rate (ADR). A drop of 7.4% for the four-star market in 2010 helped to boost occupancy by 4.5% (CityOccupany by Savills, 2010). From a micro-economical perspective, this may be wise in the short-run. Price cuts are yielding to lower revenues, but more possible transactions (Con Quigley, 2010). The Relationship approach can support remedy for the long-run however. The presentation of the supply and demand in the Irish hotel sector shall indicate the competitive environment in which the hotel as situated. CRM can be a solution for face these issues.

1.2. Outline and Methodology

At the beginning of this paper, in the third chapter, an overview of the development of CRM is presented. The recurrent theme in the subsequent two chapters will be the importance of the basic concepts of CRM. These themes will be accompanied by a discussion of the development of the different forms of CRM. After considering the basic structure, chapter four will discuss the organisational information management aspects of CRM, such as databases. This chapter will give an overview of how to organise sales force activities, database integration and the usability of electronic data. Basic concepts and models denoting the process of electronic CRM will be demonstrated and discussed in detail. Chapter five explains the objectives and mutual benefits of a customer relationship from both a hotel and guest perspective.

The role of technology and databases will be discussed in chapter six. Based on the previous five chapters, chapter seven will explain how to segment and how to place a value on hotel guests via segmenting and calculation systems.

In addition, the importance of external and internal marketing will be emphasised in conjunction with best marketing practices for hotels, such as social media and complaint management, in chapters seven and eight.

Continuing from the theoretical chapters mentioned above, the focus in chapter nine will be on the empirical research which is included in this dissertation, explaining how the empirical study was conducted in terms of methodology and research tools. The research hypothesis will be stated and explained. Chapter ten will present analysis and discuss the findings from the qualitative and quantitative research.

The finding and analysis of the empirical research are found in chapter eleven. In addition, chapter twelve will present conclusions and recommendations. This includes advice for further investigation and research in this field.

Last, but not least, the researcher will review his own learning experience during the process of conducting this dissertation. Literature Review

B. Literature Review

2. Objectives of the CRM approach

Lovelock and Wirtz (2007) state that: “When Customer Relationship Management (CRM) systems are implemented well, they provide managers with the tools to understand their customers and tailor their service, cross-selling and retention efforts, often on a one-on-one basis”. CRM can help to identify profitable (or the “right”) customer groups. Furthermore it helps to identify which customers to abandon in the long-term (Newell, 2000). It has to represent the ability to maintain and establish profit maximising relationships with guests (Zablah, Bellenger and Johnston 2004). The means of identification can be qualitative (e.g. loyalty) or quantitative (the measurement of their contribution margin) (Dyche, 2002). In most cases, reducing guest turnover by creating relationships with the guests is considered an ideal solution (Eriksson and Akerman, 1999). Although substantial literature exists in this area, there has been relatively little discussion of the distinction between the segmentation of loyalty among customers. Loyalty is measured by two components: behaviour and attitude. Behaviour is tendency towards repeat visitation, but on its own has been found to be an inadequate measure of loyalty (Backman and Crompton, 1991). Hotels need to ensure that relationships are mutually-beneficial. The CRM value chain (Buttle, 2004) process explains the mechanisms in archiving customer value and profitability. This CRM framework is not only a process, but also identifies the supporting conditions for CRM operations.

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Figure 3: CRM value chain (by Buttle, 2005)

(Note: the primary stages and supporting conditions are discussed in throughout the literature review).

3. The development of Customer Relationship Management

Transaction marketing originated from economic exchange developed during the Industrial Revolution. (Vargo and Lusch, 2004). Cristopher, Payne and Ballantyre (2007) state that:”as industries have matured, there have been changes in market demand and competitive intensity that have led to a shift from transaction marketing to relationship marketing.” Relationship marketing explains marketing practice better than do those of the transactional approach (Berry, 2002). Relationship Marketing is within the literature found in conjunction with service marketing and the development thereof (Gilmore, 2003). The difference between transactional and relationship marketing lies in the basic characteristic of how the marketing is structured. Marketing concepts are evolving from transactional to relational (Webster, 1994). On the one hand, in transactional marketing the duration of the contact is short and the organisational goal is to make a sale. Therefore, the company’s focus on service is minimal as well as the customer contact being fleeting (Berry and Parasuraman, 2004). Attracting, developing and retaining customer relations is the long-term relationships and developing indicators of customer profitability seem important if a company is to remain profitable (Rust et al., 2003, Christopher,Payne and Ballantyne, 2007) – (see figure 4). CRM is already the most common marketing practice in the finance sector (Alexander and Colgate, 2000). As companies using this approach began to save on marketing, which is often used as a measure for successful customer targeting, managers had to invent a technique to optimise not only their spending, but also to identify which customers are not profitable (Berry and Parasuraman, 2004). In transaction marketing, audits take place to establish which communications campaign is the most effective. However, in relationship marketing the key issue is estimating which customers create the highest return on investment (Winer, 2001).

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Figure 4: the transition to relationship marketing (by Christopher, Payne and Ballantyne, 2007)

4. The forms of CRM

Whilst operative Customer Relationship Management (CRM) focuses mainly on consistent service provision (ideally not sedentary) and the technology for implementing a CRM system, analytical CRM instruments deal with the methodology of data analysis (e.g. customer segmentation). Last, but by no means least, communicative CRM focuses on data gathering and the related transfer of data. All three forms need an integrated managerial approach to hotel CRM (Sigala, 2005).

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Figure 5: CRM Components (by author)

4.1. Types of Operational CRM

The tools of operational CRM serve to support all customers – they support all business processes via the provision and integration of data. The data obtained is very useful for marketing, sales and customer service. Not only do these departments depend on such data, but contribute valuable information as well; it is a two-way process (Meyer, 2002). The focal point in this type of CRM is the customer data, which is processed in real time (Ghiani, 2003). Such real time operation systems are based on the customer purchasing cycle. Via the real time, online and non-sedentary provision of data, all employees are able to provide uniform service to the customer, as all data undergo synchronisation (Reynolds, 2002). However, many hotels also use offline databases with direct mail and an analytical focus as well. Therefore, a difference exists between the real time interactive demands of e-business and some aspects of CRM, which are handled offline (Goldberg, 2003).

Customer Service and Support (CSS): This concept is known as “one face to the customer”. The organization wants to obtain information in order to establish uniform service delivery to the customer (Battle, 2008). Therefore, operational CRM automates and improves the customer-facing and customer-supporting business processes.

Sales Force Automation (SFA): CRM can automate the collection and distribution of all sales-related information. However, in recent years the costs associated with sales forces have gone up, whilst their output has been steadily decreasing (www.optimum-outcomes.com, 2010). SFA technologies give a competitive edge to many organisations by offering improved productivity (Pullig et al., 2002).

Automated Marketing: These tools can be used to create automated and customised marketing campaigns for different guest segments. This includes the creation of lists and tracking campaign results. According to Winniger (2007): “Databases should be used to track incentive points, ancillary products needed, and the communication frequency with the customer”.

4.2. Types of Analytical CRM

The main difference between operational and analytical CRM is that analytical CRM is the only means by which a company can maintain a progressive relationship with a customer throughout the customer’s relationship with the hotel (Dyché, 2002). However, the background of the senior executives also provides guidance for the hotel on whether to adopt a more operational or more analytical CRM approach (Lo, Stalcup, Lee, 2009). Data that is gathered, captured and stored using operational CRM will be processed using analytical CRM. Here management gathers information for the segmentation and clustering of customers (Buttle, 2008). Payne (2005) explains that: “The information management process provides a means of sharing relevant customer and other information throughout the enterprise and ‘replicating the mind of the customer’”. The customer data analysed serves on the one hand as foundation by which to determine the approach towards the customer and on the other hand, it determines the re-assignment of customer-related internal processes. Analytical CRM uses knowledge in a strategic way as customer knowledge is a meaningful economic resource (Drucker, 1996). Using information for strategic decision-making is a key tool for gaining a competitive advantage (Tzokas and Saren, 2002). Analytical CRM creates a paradigm shift as segmentation takes place not in an external market situation, but by means of internally gathered data (Paiva et al., 2002). This implies a shift from traditional mass-marketing to so-called customer-centric orientation, which in return creates a competitive advantage (Bose, 2002). This customer data gives a breakdown of the former purchasing behaviour of the customer/s (including amount and value). The action data identifies which marketing activities relate to the customer and which have been sent to him/her. In this regard, the analytical CRM helps the automated marketing process in operational marketing. The reaction data summarises the communications that were initiated by the customer. Dyché (2002) states that: “Performing analytical CRM means understanding how your customers interact with you”. This demonstrates the concrete overlap between operational and analytical CRM: Analytical CRM supports operational CRM activities. Data management is therefore the starting point, especially for a company with global customers (Sumathi and Sivandan, 2006). Data mining enhances the strategic analysis of large quantities of guest data in order to identify meaningful patterns and relationships (e.g. Groth, 2000). Each component influences the other. For instance, analytical CRM drives the decision-making in operational CRM for the deployment of marketing, sales and customer service resources (Reynolds, 2004). As, at root, an analysis of the customer value is taking place in this process, Buttle (2001) established a CRM value chain to estimate customer profitability, with two main strands (see figure 3). These include five primary stages (customer portfolio analysis, customer intimacy, network development, value proposition development and management of customer lifecycle) and the supporting conditions (leadership and culture, data and IT, people, and processes). In contrast, creating value for the guest (i.e. the benefits that customers receive from the price paid and the various sacrifices customers make) is achieved through primary and supporting CRM activities (Zeithaml, 1988). On !! of the challanges is to verify the costs and revenues to guest in different segments or at a different position along the customer lifecycle (Lovelock and Wirtz, 2007). In conclusion, analytical CRM is meant to support the understanding of the hotel guest via the analysis of guest-related data (Ranjan and Bhatnagar, 2010).

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Figure 6: Analytical CRM (by author)

4.3. Communicative CRM

Grönroos and Finke (2009) believe that: “Relationship communication is any type of marketing communication that influences the receiver’s long-term commitment to the sender by facilitating meaning creation through integration with the receiver’s time and situational context." Communicative CRM draws together all traditional and modern communication channels. Furthermore, it incorporates the control, support and synchronisation of all communication channels with the customer (Belz, 2011). Within the conceptual framework of CRM, it is advantageous to offer various channels of communication to the customer (Holland, 2001). Here especially social media and the internet play an important role (Essler, 2009). In addition, mobile applications play an important role in the communicative CRM processes of hotels (Stitz, 2009). Brink and Berndt (2009) state that: “The Importance of Communication in the Implementation of CRM Communication within the organisation is essential in the implementation of the CRM strategy”. At the same time, it is important that the hotel approaches the customer through the channel he/she prefers (Arter, 2010). Egger et al. (2007) explains that: “Tourism is considered to be a highly information-intensive business and there can be no doubt that information and communication technologies (ICTs) have made an impressive contribution in recent years, by influencing and forming the market in an innovative way at both the process and product levels”. Incoming and out-going communication processes need to be integrated into one system, in order to collate information pertaining to the exchanges between the hotel and the guest (Kolbe, Österle and Walter Brenner, 2003). An integrated, multi-channel approach should be introduced so that the guest can communicate and interact with the hotel via various channels (Arter, 2010).

4.4. Review of Types in CRM and collaborative CRM

Payne (2005): no need to bold type authors “A significant problem that many organisations deciding to adopt CRM face stems from the great deal of confusion about what constitutes CRM”. The aforementioned types of CRM indicate interconnectedness between analytical, operational and communicative CRM. These correlations call for integration into a unified structure, the so-called collaborative CRM approach (Vogt, 2009). Collaborative CRM is a frictionless and consistent interaction between the guest and the hotel via various channels of communication (Knöpp and Helling, 2006). Berry and Kent (2007) state that:” a strong service brand is build and sustained primarily by customer interactions with the provider.” However, this definition misses the holistic idea underpinning collaborative CRM. In broader terms, it invokes the efficient handling of communications, the systematic transfer of guest information into one system, and gains from the synergy potential (Kracklauer, 2003). Furthermore, it is a system that tackles the challenges along the whole value chain (Porter), as it does not just focus on the customer and the market, but on the suppliers as well. Dietz (2005) clarifies that: “Cooperation is the cornerstone of value creation, and collaboration in the supply chain could open up new opportunities for profitability”. A holistic managerial approach to hotel CRM, incorporating the aspects of information and communication technology, internal marketing and external relationship management (e.g. of customers, suppliers or even competitors), and knowledge management is required (Sigala, 2005, Lovelock, 1996). Conceptually speaking, however, a cross-departmental, cross-functional, process-based conceptual system covering five generic processes including strategy development, value creation, multichannel integration (Lovelockand WIrtz, 2007) – see figure7, information management and performance assessment is needed in order to implement a unified and collaborative CRM process (Payne and Frow, 2005), via the supervision and support of the top - management (Grönross, 2003), as presented in figure 7 as well.

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Figure 7: Hospitality service and communication system (Lovelock and Wirtz, 2007)

5. Perspectives on the Supplier and Customer Relationships

“the result should be a win–win situation, where profits are earned through the success and satisfaction of customers, and not at their expense.“

5.1. The role and need for loyal relationships in a commercial context

Kumar, Sunder and Ramasehan (2011) believe that: “With the changing business climate, firms are beginning to embrace the concept of managing customers rather than products. This leads managers down the path of customer centricity”. All organisations have relationships with their customers. Anderson (1994) believes that: “In business-to-business settings, dyadic relationships between firms are of paramount interest. Recent developments in business practice strongly suggest that to understand these business relationships, greater attention must be directed to the embedded context within which dyadic business relationships take place”. However, the general concept of business-customer relationships is not a new one. One only has to read the ancient Middle Eastern proverb “As a merchant, you’d better have a friend in every town” (Grönroos, 1994), to appreciate the importance attached to loyal relationships in a commercial context throughout history. At root, CRM is inextricably linked to the marketing concept (Kotler, 1967). Therefore, initiating business relationships, in the sense of establishing and maintaining useful social and customer contacts, is as old as trade itself (Ballantyne, 2009).

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Figure 8: The Wheel of Loyalty (by Lovelook and Wirtz, 2007)

In order to meet these challenges, Lovelook and Wirtz (2007) advise: ”to emphasise the importance of focusing on desirable customers, and then taking pains to build their loyalty through well-conceived relationship marketing strategies, including delivery of quality service” (compare figure 8 and follow on the 9.1 on Service).However, initiatives in service quality management are implemented but fall short to meet most of the set objectives (Lovelock, 2001).

(For further details on literature in section 5.1, see Appendix III. The role and importance of Relationship from a business perspective are discussed further.)

Based on this paradigm shift, the Nordic school was established (Grönroos: 1994, 1995; and Gummesson, 1987). In defining the term ‘relationships’, researchers were entering uncharted waters. The available literature bases its content on the assumption that the reader is familiar with and aware of the significance of the term ‘relationship’ in a business setting (Zolkieski, 2004). The term ‘relationship marketing’ is frequently used in business literature (Palmer, Lindgreen and Vanhamme, 2005). Personal relationships are defined as “ties between individuals that know each other well and have developed a kind of common language for smooth interaction” (Mainela, 2007, p.94). Relationships lead to the establishment of social bonds. Williams et al. (1998) believe that: “the process of interpersonal orientation or bonding helps in understanding buyer-seller relationships”. Social bonds can be established and emerge in a business and marketing setting. It can further be asserted that an act of exchange, such as a business transaction, carries with it additional implications (Stone and Mason, 1997). This may lead to the conclusion that a transaction or transactions are the first stage in establishing a deeper relationship. Holiday (2000) consequently states that: “Marketing experts say this demands a greater emphasis on customer life cycle patterns – how the customer needs evolve over time – versus the closing of a deal at a particular moment to meet a sales goal”. (See section: Customer life cycle). However, a good interaction, or even a series of interactions, does not guarantee a relationship and loyalty (Hasan, 1996).

5.2. The meaning of the relationship factor from the hotel perspective

Sigala (2004) explains that: “As travellers are becoming more price-sensitive, less brand loyal and more sophisticated, Customer Relationship Management (CRM) becomes a strategic necessity for attracting and increasing guests’ patronage”. In addition, Kalwani and Narayandas (1995) state that: “Suppliers (e.g. hotels) who are able to create long-term relationships achieve higher profitability, by reducing their discretionary expenses, compared to their competitor who works with a transactional approach”. This profitability is based on different factors. Suppliers benefit from being able to better plan and forecast production schedules, coordinate deliveries and undertake joint promotions (Easton and Araujo, 1994). Barut et al. (2002) identify other benefits as well, including quicker response to customer demands, lower inventories along the supply chain, and lower costs associated with the service delivery within the hotel. Hotels can reduce transaction costs, including both the direct costs of managing relationships and the possible opportunity costs of making poor management decisions (Rindfleisch and Heide, 1997). In essence, the relationship between a hotel and a guest reduces the operational costs involved in setting up a transaction. However, establishing and maintaining a relationship is costly as well. Blois (1996) points out that: “Much of the cost of implementing a relationship marketing policy relates to the activities which are the consequence of the decision to carry out such a strategy. A hotel needs to evaluate with whom to engage in further relationships, as not all relationships are beneficial. RM provides a stronger, longer-term customer benefit that is more difficult for competitors to match and it thus becomes more difficult for competitors to enter the market (Hakansson, 1982). Within a hotel/guest relationship, both parties are able to benefit from this approach to Relationship Marketing. On the one hand, the hotel can better tailor its services to meet different customer demands and needs, and thereby gain a sustainable competitive advantage. On the other hand, the customer gets better service matching their individual criteria. Consequently the guest satisfaction level can increase (Hughes, 2003).

5.3. The meaning of the relationship factor from the guest/ client perspective

The result of a study by Jain (2005) state that hotels need to “strongly emphasise the need for humanising people, process and technology to build an emotional bond with customers” in order to increase profitability. Guests are establishing relationships with their accommodation and vacation suppliers because it enables them to be more efficient and more effective (Kalwani and Narayandas, 1995). By developing relationships with hotels, guests can achieve cost savings through reduced search and evaluation costs (Hakansson, 1982), reduced transaction costs and the learning effects and relationship-specific economies of scale (Gundlach et al., 1995). However, the primary reason for establishing relationships with suppliers is that customers realise that suppliers can create value for them. Developing long-term relationships can improve access to markets and provide more reliable market information (Low, 1996). Buyers may become less price sensitive and suppliers may benefit from higher prices (Kalwani and Narayandas, 1995). Research indicates that guest satisfaction is an excellent predictor of repurchase intentions in the hospitality sector (Petrick, 2004, p.397). Gupta and Zeithaml (2006) confirm that: ”Satisfaction is expected to lead to repurchase behaviour, which translates to increased sales and profits. Guests’ evaluation of service comprises two basic distinct dimensions: service delivery and service outcome (Mattila, 1999, p.42). If hotels are able to make guests feel significant and private information about guests is handled well, then long term supply/bookings are secured. Internally this means that customer care is maximised and sudden spikes in demand are managed. In figure 9 Gupta and Zeithaml (2006) express that the influence and inter-dependence of marketing actions (what firms do) and customer metrics like customer perception (what customers think) and what customers do (behavioural outcomes) affect the actions and the financial performance of the service provider.

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Figure 9 : Framework for Customer Metrics and Their Impact on Financial Performance (by Gupta and Zeithaml, 2006)

Although the belief that customer satisfaction leads to loyalty is widely accepted, it appears to be a myth, as demonstrated by research (Hanso, 2007). Keiningham et al. (2005) prove that: “Customer revenue was found to correlate negatively with customer profitability for unprofitable customers and positively for profitable customers”. Contrary to former expectations, each activity must be carried out and linked effectively to achieve optimum overall performance. Reducing guest turnover by creating relationships with the guests is often a recommended pursuit (Eriksson and Akerman, 1999). Due to the complexity of the guest experience, guests are likely to search for evidence of value and satisfaction from three distinct sources: 1) people; 2) process and 3) physical environment — or what has been known as the ‘services cape’ (Mattila, 1999). When guests use a service they process more information than hotel managers often realise (Berry et al., 2006). A relationship with a hotel reduces the risk of re-purchase for the customer and adds a social dimension to the transaction (Mattila, 2001). Guests can experience personal service in a familiar environment and have their needs for recognition and security met. The relationship helps protect the emotional wellbeing of the guest in which he/she participates (Aikten, 2006). The service experience becomes simplified as a regular series of encounters facilitate the implementation of a customised service (Miyoung and Haemoon, 1998). Sheth and Parvatuyar (2000) assert that: “an alternative paradigm of marketing is needed, a paradigm that accounts for the continuous nature of relationships among marketing actors”. A new trend, according to Gummersson et al. (2010), is: “to move from mainstream service management (1970-2000s) to a new approach synthesised in the service-dominant logic (2000s). Since the beginning of this century, hotels are interested in implementing a service-dominant logic. In this process the guest becomes a co-creator of value (Lusch and Vargo, 2006). Service-dominant logic is the proposition that customers become co-creators of value (Payne et al., 2008), which changes the business strategy (Grönross and Rayald, 2011).

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Figure 10: Managing the co-creation of value (Payne et al. 2008)

Figure 10 summarises the role of emotions in the customer co-creation and the involved process. Edvardsson et al. (2010) says that: “From a service logic perspective, the customer has an important role in both service production and innovation”.

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Figure 11: Logical structure of the service and causes of variability (adapted from Edvarsson, 1998) – (by Erto, Vanacore, Staiano, 2011)

6. Development of Information Technology

The nature of Services is changing via using technology (Bitner, 2001). Saren (2011) states that:”IT effects are felt throughout marketing practice, impacting on such diverse areas as analysis and decision making, monitoring and control, communications, distribution channels, service and promotion.” Heizer and Render (1999) point out:”Technology improves productivity in the hospitality sector and makes a difference”. The fundamentally product-entered concept of brand equity is being increasingly challenged by the principles of customer equity (Blattberg and Deighton, 1996). The accelerated development of IT utilised for the supply of necessary data and information to management, has gone hand in hand with developments in corresponding marketing metrics. The necessary forerunners were the “business intelligence system” as well as Enterprise Resource Planning (ERP) systems. Soffer, Golany and Dori (2003) state that: “Enterprise Resource Planning (ERP) systems are off-the-shelf software packages that support most of the key functions of an enterprise, such as logistics, sales, and financial management.” These systems found their way into major cooperations by the end of the eighties. Cooney, Pratt and Olsen, (2011) state that:” As recently as the mid to late nineteen eighties, traditional business applications comprising an organization's information infrastructure used data that either resided in proprietary file structures or was easily represented by the relational database model, in either event resulting in an ever proliferating set of non-integrated, heterogeneous systems. “The integration of operative and analytical information systems encouraged the automation of decision-making processes. Hogan et al. states that emerging technologies have enabled firms to personalise products, customer service, communications and even pricing in ways that were undreamt of just a few years ago. In the following section two fundamental principles of CRM data systems will be presented. However, it should be cautioned that increasing data could complicate the decision-making process and affect it negatively (Van Bruggen, Smidt and Wierenga, 2001). Although there is noticeably more to Relationship Marketing than technology, one needs to bear in mind that it plays a crucial role (Reinartz et al., 2004). Therefore, hotels need to gather customer information about current and future customers and strategically apply this information for further marketing activities (Johnson, 2004); however, hotel management often fails to set strategic objectives and neglect to define measurement categories. This phenomenon limits the success of Information technology in CRM (Newell, 2004).

6.1. CRM Databases and Database Marketing:

Lancatser and Massingham, (2010) say that: “Database marketing describes a way of organizing a company's total marketing and sales processes.” Database Marketing is pertinent to and important in the hospitality and tourism sector as a marketing tool (Callan and Teasdale, 1999). CRM describes an organisational- and departmental-wide cross-cutting use of information technology, to establish a corporate strategy aimed at creating valuable customer relationships, which delivers financial success (Meyer, 2007). The above definition is crucial as it highlights the main point of CRM: “To create valuable customer relationships”. On the one hand, to establish a relationship is the first challenge; however, to establish one with value, another. Therefore, CRM is a Management of mutually beneficial relationship(s) from the seller's perspective (LaPlaca, 2004). Identifying the right targets and selecting the right messages is not always easy or obvious (Paas, 2009). Wide-ranging client databases are a derivative from transactional marketing databases, which enable marketers to follow up on customer behaviour, including their reactions to marketing activities (Boone et al., 2008). However, nowadays database marketing influences transactional marketing (Roger and Teasdale, 1999). Gathering guest data is the starting point for a hotel that decides to estimate the value of its clientele by evaluating the electronically stored data (Boone et al., 2008). This allows the hotel to select prospective clients for specific marketing offers and enhances opportunities for customer base segmentation (Paas, 2009). Hotels have a wealth of information, due to legal requirement (e.g. personal data of guests) (Bowie and Buttle, 2004) Thus, database marketing has improved the ability to target narrow market segments, see figure 11 (Paas, 1999). The developments in Information Technology during the last twenty years have allowed for the establishment of fully guest-orientated hotels. Guest-related data can not only be stored more conveniently at less expense, but it is retrievable everywhere, as it is not tied to a given physical location. However, a sophisticated IT strategy may not be seen as a sufficient CRM Strategy (Meyer, 2007). The processes that surround the incorporation of data mining into the operations of a marketing department can be complex (Levin and Zahavi, 1996). Hsu (2002) points out that: “A hotel will log each visit by a customer in its guest history file. Tracking customer transactions is fairly straightforward for hotels, because they begin to keep track of who its customers are”. Database Marketing is mostly a tool for CRM use. It has a different focus than Yield Management or Direct Marketing, even though databases are used in these techniques as well.

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Figure 12: Customer Database process (by Rutherford and O'Fallon, 2006)

Using Database marketing may lead to higher profitability, as sales increase and the acquisition costs decrease. Figure 12 conceptualises this phenomenon. The CRM programme improves relationships and leads to guest loyalty. Data mining gathers qualitative information for cross-selling, targeting and market research (Rutherford and O'Fallon, 2006). In this context, management needs to design programmes that enhance share-of-wallet, up-selling and cross-selling (Lovelock and Wirtz, 2007).

7. The need of segmentation in CRM

“Therefore test, who wants to bind himself forever, whether heart will find right heart.

The elation is short, the remorse is long.” - Friedrich Schiller, Song of the Bell

To segment customers based on their profitability is necessary, via the gathering of guest data. The process of dual value creation is supposed to create more value to the guest by the data taken from him (Payne and Flow, 2005). Mostly calculative systems help the hospitality sector to archive this. Management has to bear in mind that loyal (or the “right”) customers will not necessarily be the highest spenders (Reinatz et al., 2004). A conservative customer, for example, is likely to stay loyal to a familiar service, but is not necessarily likely to spend large sums on individual transactions. This is because the customer is used to the product and service. Customers can be divided into four groups of profitability patterns (see section: Goals of CRM) (Zeithaml et al., 2001):

- Platinum customers: heavy users, less price-sensitive, ready to try out new products
- Gold customers: demand sales discounts for their loyalty
- Iron customers: make up the mass of the demand but are erratic and have a low profitability
- Lead customers: the costs exceed the income

The following graph explains the different segments in a simplified way:

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Figure 13: The Customer Pyramid (by Zeithaml et al., 2001)

However, most techniques and components to measure the guest value (cross-selling, customer lifetime value, customer migration, retention and acquisition), are important but lack a direct connection to the dual value-creation (Boulding, 2005).

7.1. Benefit segmentation

Companies generally divide by geographic, demographic, socio-economic, and psychological characteristics to segment the market, although these are not efficient predictors of future purchasing behaviour (Singh and Minhas, 1996). Singh and Minhas (1996) assert that: “To correct this shortcoming, benefit segmentation by factor analysis has been used for the first time to group building society customers in relation to their particular attitudes and behaviour”. However, one of the most challenging issues in CRH is for hospitality managers to understand the behaviour of their guests (Reid and Bojanic, 2010). In other words, a market segment should be identifiable, meaning that it can be targeted (with products, services or market offerings); measurable, in terms of size or attractiveness; accessible and able to be served with various stimuli and/or marketing (Rizal, 2003). The focus needs to be on why the guest wants a service, and not, for example, who buys it, as in a demographic variable (Zineldin, 2000). Benefit segmentation can be used in collaboration with several other closely related segmentation bases (Weinstein, 2004). The strongest argument, however, for implementing and using benefit segmentation is based on cause-and-effect factors rather than descriptive factors (Botschen et al., 1999). Yet, as simple as this approach appears, scholars like Hoek et al. (1996) believe that: “Despite sophisticated approaches to market segmentation, the selection of variables on which such studies are based involves subjective judgments”. Furthermore, the initial choice of variables is in itself a categorisation of data that has no quantitative guidelines and which reflects the marketer’s judgments in relation to the segmentation (Everitt, 1974). The limitations of this method can resemble those found in lifestyle and psychographic segmentation and the related research (Weinstein, 2004). In the international context, the differences between collective and individual cultures can complicate this method as well (Agarwal, et al., 2010). Although benefit segmentation may appear to be suitable within the context of one culture, if one attempts to apply it to an international scenario involving multiple cultures, different values can distort the validity of the study (de Mooij, 2003). These limitations include the lack of a theoretical foundation, lack of cross-cultural validity and shortcomings in its ability to predict behaviour. The derivation of so-called basic lifestyle dimensions is unclear as well (Grunert and Brunsø, 1993). However, benefit segmentation has led to valuable insights into tourism and hospitality research in the past. Nevertheless, careful development of the benefit statements used as the segmentation base, informed choice of the timing, regular conducting of benefit segmentation studies to account for market dynamics, and conducting them separately for different seasons, are all factors for improvement (Frochot and Morrison, 2000). In addition, researchers using consumption benefits as a segmentation basis must determine which benefits to measure and select appropriate means of assessing their relative importance to respondents (Fuller et al., 2005). Benefit segmentation has been noted as being better at predicting and explaining behaviour than other measures, which merely describe it, such as personality and lifestyles, volumetric, demographic or geographical measures (Loker and Perdue, 1992). The focus should be on those customers who are able and willing to influence the customer value and the overall profit the most. Therefore, customers are categorised by their customer value. Benefit segmentation encompasses the whole of the customer base and can easily be adjusted to individual sectors and organisations. By utilising and identifying segments based on their importance, a hotel is able to treat guests differently and to optimise and tailor the marketing and sales budget (Grunert and Brunsø, 1993). A hotel needs to question relationships that appear to be unprofitable or minimally profitable in terms of trade-off between revenue, cost and net profit. The so-called “ jay - customers”, refer to dysfunctional guests who deliberately or unintentionally disrupt service in a manner that negatively affects the organisation or other hotel guests (Lovelook, 1994). Calantone and Johar (1984) point out that: “Attempts to segment the travel and hospitality market by showing how different factors influenced choice in different seasons. Results showed that benefits sought for each season differ, and people seeking a combination of benefits during one season may not be the same people seeking the same benefits during another season.”

7.2. Calculation method and techniques of customer value

“What’s a customer worth? The company that can answer this question precisely is the company with an edge in the customer-based, technology- and information-intensive economy of today. But how can an asset as intangible as customer value be measured?”

(Blattberg et al., 2001)

A key concept in CRM is a good measurement process (Payne and Frow, 2005). Venkatesan and Kumar (2004) note that: “Customer Lifetime Value (CLV) is rapidly gaining acceptance as a metric to acquire, grow, and retain the “right” customers in CRM.”In order to enforce the customer lifetime value approach, the actual value of a customer to a particular hotel needs to be identified. The higher the value of a customer, the higher the disbursement in marketing towards that customer. There is a double significance to the practice of assessing customer value: On the one hand it contributes to corporate success and on the other hand it helps identify the investment-worthiness in terms of the desired provision. While traditional marketing budgeting is based on periodical measures over more or less arbitrarily decided lengths of time, it is often used in managerial accounting. The CLV is a measure based on investment theory. It estimates the financial worth of a customer for the entire “lifetime” of the relationship (Bruhn et al., 1998, p.183). A hotel needs to bear in mind that different forms of customers exist.

Many hotels sell their contingent of rooms to business clients, to private customers or to resellers. The different guest categories feature a range of customer characteristics which need to be considered in order to drive customer equity and loyalty (Osenton, 2002, p.21).

7.2.1. Calculative models

This CLV method finds its roots in management accounting and views CLV as a business ratio of in- and outgoing payments. The business ratio can be calculated by adding together the income from expected business relationships, and subtracting the expected costs (Heidemann et al., 2008). The expected relationship can also be translated into the retention rate. The retention rate is the calculated probability that an individual customer will become and remain loyal to a hotel, based on previous spending behaviour (Dwyer, 1997).

Overview: The following four calculative models are based on a deterministic approach. The pioneer model is Jackson’s (1985), which laid the calculative foundation for later models to emerge. The second model is by Dwyer (1989), who illustrated the calculation of CLV for both customer retention and a migration situation. Berger and Nasr (1998 and 2001) presented five mathematical models of the CLV (four of them involving customer retention and the fifth involving customer migration) and launched a statistical programme model for the CLV to help managers decide on optimal distribution of the promotion budget. Blattberg and Deighton (1996) offered a mathematical model of the CLV by using an infinite horizon to help managers decide the optimal balance between customer acquisition spending and customer retention spending.

7.2.1.1. Calculative method I: ‘Lost-for-Good’ Model (Jackson, 1985)

This kind of model is based on customer segmentation, or the allocation of customers into one of two extremes of behaviour groups: “always – a-share” or “lost – for – good” (Jackson, 1985). The so called “lost – for – good” customer relationship is of short duration and these customers are likely to switch to other providers easily, without any hassle. This kind of customer is highly significant in traditional transaction marketing. This implies that “always – a-share” customers are to be characterised by the long-lasting loyalty attitude. This can be based on the high switching cost for the customer (Jackson, 1985). The “lost – for – good” customer satisfies all of his/her needs via one provider, at least for a while. On the other hand, an “always – a-share” customer prefers to satisfy his/her needs through various providers and gives the hotel only one share of interest.

Hotel guest and switching costs: Butcher et al., (2001) proposed a four-dimensional model of loyalty: positive word-of-mouth, a resistance to switching, identification with the service (i.e. expressing a sense of ownership and belongingness about service providers visited regularly, such as “my hairdresser”), and a preference for a particular service provider over the competition.

Switching costs: In the most severe cases, switching costs lead to the termination of the relationship and the parties involved will seek an alternative relationship, even though high switching costs have been incurred(Rust, Lemon, Zeithaml, 2006). The high termination costs may, at times, even lead to dependence upon each other, rather than termination (Spekman and Strauss, 1986; Frazier et al., 1988).

The “lost – for – good” situations can best be solved by viewing them as typical “customer retention” issues. The implicit assumption is that customers are “alive” until they “die”, after which they are lost for good. Rust (2004) argued that the “lost – for – good” approach incorporates CLV because it does not allow defected customers to return. Others (Dréze and Bonfrer, 2005) argue that customers can be treated as a renewable resource. Although one needs to recognise the high complexity of the issues involved in customer retention, Oliver (1997) argues that: “Profitability can be shown to follow from not only the direct effects due to quality, satisfaction and loyalty, but also the mediated effects of quality and satisfaction through loyalty”. Defining quality is critical to effective and efficient operations (Heizer and Render, 1999), therefore the call for service quality needs to influence the entire corporate strategy(Berry and Parasuraman ,2004)This implies that the model focuses on a retention strategy in order to keep the customer with the hotel, vis-à-vis “always – a-share” situations, which can be managed via customer migration. The hotel can differentiate between both groups of customers by using the number of past purchases in order to predict future purchasing behaviour. The differentiation is based on the retention rate calculated. The future consumption pattern can be estimated based on the former purchasing behaviour of a customer. By choosing this method, it is possible to incorporate the randomness of the purchasing behaviour of a customer into the CLV calculation (Dywer, 1997). Customer lifetime value is a useful measure for determining the customer segmentation, predicting customer actions and evaluating customer loyalty (Baxter 2005). However, the model is based on a limited and consistent lifespan for the customer relationship (Buhl, 2009). In addition, the model has been criticised for the fact that the relevant cash flow is assumed to occur in the same period as the related purchase (Buhl, 2009). Furthermore, the similarity in each period is seen as a constant, and is based merely on the period in which the purchase was finalised (Buhl, 2009). However, the assumption that a hotel can use the purchase history, including recency, to predict purchase behaviour for the future, is overall plausible (Berger and Nasr, 1998).

7.2.1.2. Calculative method II: Customer lifetime valuation by Dywer (1989)

Dwyer applied Jackson’s taxonomy to direct marketing and demonstrated implications for lifetime valuation (Berger and Nasr, 1998). A customer retention model is used to model “lost – for – good” situations. Whereas Jackson (1985) was criticised for the assumption that cash flows and purchases take place in the same period, Dywer (1989) sees them as an ongoing process. Retention rates express the probability that a customer will remain loyal for a certain period (Dwyer, 1997). Kemper (2010) says that: “they can be quantified, with causal analyses based on determinants such as satisfaction level, switching barriers, variety-seeking behaviour and competitors”. Dwyer’s (1989) method aimed at furthering the lifetime value (LTV) concept by developing an estimation of LTV for customer retention, and also for customer migration situations. In a customer retention situation, non-responsive signals can indicate the end of the firm’s relationship with the customer. However, customer migration situations are those in which non-responsive signals do not necessarily indicate the end of the relationship. Besides articulating this distinction between customer retention and migration, Dwyer (1989) listed several impediments in the use of LTV as well. One of the major challenges for hotels in customer migration situations is that the organisation may be unaware when the relationship is over (it is a unilateral decision by the customer). This particular concept tries to address the issue of guest acquisition spending. Dwyer (1989) points out that: “LTV provides a ceiling on spending to acquire new accounts”. Hansotia (1996) asserts that “to ensure that the customer acquisition programme brings in the right types of customers, who contribute to the value of the firm, it needs to be ascertained that each prospect’s predicted long-term value on conversion exceeds his/her acquisition cost”.

7.2.1.3. Calculative method III: Customer lifetime model and its application by Berger and Nasr

The CLV concept of Berger and Nasr (1998) is based on an estimation of the contribution margin generated by a customer in direct marketing, as well (see Dywer, 1989). In this model the acquisition costs are of less importance. Furthermore, fixed costs are not considered. Berger and Nasr discount the difference between revenues and the cost of sales. Similar to Dwyer (1989), Berger and Nasr (1998) used present values to model the values of individual customers. They consequently linked customer valuation to five different cases of customer behaviour. Annual cycles of customer purchases, adding shorter and longer cycles to assess individual CLVs, are presented. In order to estimate the CLV, the hotel needs to project the net cash flow that the hotel expects to receive from the customer over time. The second step is to calculate the present value of that stream of cash flow. In short, the CLV concepts represent an application of the principles of contemporary finance to the evaluation of customer relations (Doyle, 2000). Whereas Dwyer (1989) illustrates the calculation of LTV using two extensive numerical examples, Berger and Nasr provide mathematical equations for LTV for five situations. Four of these involve customer retention and one involves customer migration. Mathematical models explain the CLV in relation to contribution margins and production costs or cost of goods sold, and this model indicates that these factors (customer migration, contribution margin and re-purchase) are not constant as believed in other static models.

7.2.1.4. Calculative method IV: Resource allocation model

The model of Blattberg and Deighton (1996) offers the possibility of optimizing resource allocation. This model formulates a mathematical model for LTV, for the purpose of helping managers to settle on the optimal balance between customer acquisition spending and customer retention spending. Whereas the Berger and Nasr (1998) models apply only to customers, this model applies particularly to prospects. This is due to the fact that the model uses an infinite horizon. Their resulting equation for LTV is quite simple and easy to evaluate, and involves none of the summation factors on which the Berger and Nasr finite horizon models rely. In general, an estimation of the development of the acquisition rate as a function of acquisition expenses is required. This function follows an exponential equation and is compared to the U-shaped curve of the customer value in the first year of the relationship with the acquisition budget. By following the customer value maximum, the optimal acquisition rate can be estimated.

For the customer value maximum, the optimal acquisition rate can be estimated. For the subsequent periods, the retention rate substitutes the acquisition rate and the customer value is limited to the first rate.

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Figure 14: Resource allocation mode (by Blattberg and Deighton (1996)

The graphs in figure 14 outline the situation resulting from an increase of acquisition expenses from $5 to a possible $10, which is not advisable. With an outlay of $7,50 the maximum level of the customer value in the first year is reached. The retention budget in this case should be $15 (Blattberg and Deighton, 1996). Blattberg and Deighton (1996) state that: “The balance between acquisition and retention spending is never static”. Managers must constantly re-assess the spending points determined by the decision-calculus model, keeping in mind a host of considerations.

Limitation of these models: Berger and Nazr (1998) make the criticism that Blattberg and Deighton (1996) used their models to determine optimal acquisition cost (A) and optimal retention cost (R), but they did not consider a limited availability trade-off between acquisition and retention spending. However, the concept is beneficial as it considers the long-term value of prospective customers as a stable and relevant firm value compared to the financial metrics (Bauer and Hammerschmidt, 2005). Furthermore, issues arise when general advertising expenditure (e.g. for brand image or seasonal promotion campaigns) is assigned as retention costs (Berger and Nasr, 1998).

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