How an IFA Firm can Build Strong Foundations to Create a New and Long-Term Business Model in the Post-RDR Stage?


This chapter introduces the industry structure of financial advisers and the role of Independent Financial Adviser (IFA). Then, the discussion moves on to external influences in the IFA community in particular with insurance products. One of the most crucial factors is the legal environmental changes, dominating the current discourse among practitioners and academic researchers in the UK financial intermediary industry. Therefore, this chapter explains the background behind and consequences of the alternation of the legal framework. At the end of the chapter, it will exemplify one of IFAs proactively tackling the issues.

Industry Overview

Industry Structure

As depicted in figure 1, the structural background for providing financial advice possesses quite complex and multi-sourced hierarchies (Mintel, 2009a). Through product providers, insurance products are distributed and delivered to consumers in a direct or indirect way. Under the strong regulatory influence of the Financial Services Authority (FSA), three financial intermediaries, banks and building society, the firms directly authorized by FSA, and IFA networks compete in the financial advisory market. Recently, the number of directly authorized intermediaries has been constantly decreasing for three years since Jan 2006 (please see appendix 1). On the other hand, amongst the three groups, the most popular and dominant intermediary is Independent Financial Adviser (IFA) (Mintel, 2009a). According to Crawford (2008), the head of Insurance Advisory in Ernst and Young, more than 50% of UK customers seek their individual financial advice to their IFAs.

Basic overview of market for financial advice

FIGURE 1: Basic overview of market for financial advice

Source: Mintel 2009b

Trend of directly authorized intermediaries: decreasing number of firms

Appendix 1: Trend of directly authorized intermediaries: decreasing number of firms

Source: Mintel 2009b

Role of IFA

Generally, financial advice is not necessarily obtained from professional advisers. Informal sources of financial advice, such as family, friends, and employers could be the most reliable depending on individual. However, in respect with the complexity of financial products, the special knowledge in risk management, and privacy of individual asset, of necessity is a sophisticated professional advice with confidentiality. Professional advisory source can be classified into two: single or multi tied advisers and IFA. As a tied adviser restrict their advice within one or some of financial companies, the significance of IFA’s role in the financial intermediary lies in their sophisticated advice through matching individual needs and financial products available across the entire market (RDR, 2008).

Profound Influence of Macro Environments on IFA

External influence in the insurance market as well as the IFA community has been growing both in positive and negative ways. The three major factors amongst them are the economic downturn, aging population in the UK, and the tightened legitimate environment. First of all, the financial recession that started from the late 2008 has caused cancellation and withdrawal of insurance products due to lowered household income and increase in unemployment rate (Mintel, 2009a). Taking an example in life insurance products, gross premiums in the products halved from 2006 to 2009 due to the economic downturn (Mintel 2009b; please see appendix 2). Another external influence is increasingly aging population in the UK. The extended life expectancy signals people for preparing longer retirement period, which drives further importance of retirement planning (Angelini et al., 2009). Lastly, regulatory environments change, in particular with remuneration model, has been raising controversial issues in the business structures of the IFA community. The next sub-chapter details background of the legitimate change.

Premiums of all types of life policy, 2006-09

Appendix 2: Premiums of all types of life policy, 2006-09

Source: Mintel 2009b

Changes in the Legal Framework

RDR implementation in 2013

In 2006, the Financial Services Authority (FSA) revealed a new regulation and determined to implement Retail Distribution Review (RDR) at the end of 2012 (Financial Services Authority, 2008). One of the most drastic changes in RDR was to completely terminate commission-based incentives that have been the major payment method to IFA (Financial Services Authority, 2008). The primary reason for this is that customers tend to be charged unfair and unreasonable fees (Financial Services Authority, 2008 and Baugh, 2010). For example, under the current legal frameworks, insurance product providers can control an amount of commission incentives to IFA (Financial Services Authority, 2008 and Baugh, 2010). As a consequence, IFAs are likely to sell and push higher incentive products to their clients regardless of customer needs and preferences (Lewis, 2010). In this context, FSA has decided to implement fair and transparent mechanisms in IFA revenue through customer agreed remuneration. However, the RDR change has been causing controversial arguments in the insurance industry.

Expected consequences to IFA

According to Milner (2009), Paul Lothian, the Personal Finance Society president supports the establishment of the RDR in terms of raising quality of services and professionalism in the IFA sector. The president also criticizes that the current business model permits irrelevance between levels of commission payment and amount of effort (Milner, 2009). As an example, he addresses that many IFAs tend to charge enormous amount of commissions with little effort (Milner, 2009).

Some critics expect disastrous consequences in the post-RDR world. Blackmore (2009) states that Gareth Marr, former chief executive of Origen Financial Services Ltd., warned that the business model of IFA societies was heavily dependent on commission-based fees that RDR execution would result in the collapse of IFA communities. The former executive also supported his statement by £430m of huge one-time cost that will be caused by the transition of fee charging schemes (Blackmore, 2009) Thus, the remuneration changes drives many firms unprofitable; as a result, the remaining IFAs have to focus on only profitable clients (Holt, 2010 and Pearson, 2010)

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Expected consequences to Consumers

Jones (2009) insists that the implementation of the new legitimate policy would cause socio-economic split between customers who can afford paying fees and those who cannot afford them. One of the reasons behind the statement is that direct purchase from product providers not necessarily leads to cheap investments but rather forces consumers to choose more costly options in spite of asking consulting advice from an IFA (ibid.).

In addition, the new legislation could lead to costly measures and operational inefficiencies for an employer. Fuller (2010) suggests that ban of the commission-based payment would increase more responsibility for employers to administrate and maintain pension funds by their own. With the commission based schemes, IFAs have been providing extra services such as support for HR administration and implementation of pension programme (Fuller, 2010). Under the new environments, additional staff and educational costs for managing pension programme will be imposed on employers.

Year 2010 as Exploration Stage:

As shown in Figure 2, Pearson (2009) finds that the influence of RDR has followed the cycle of reaction to change. Starting from the shocking announcement of RDR, financial advisers showed rejection, viewing it as FSA’s warning message to IFAs (Pearson, 2009). However, the publication of the discussion paper in 2008, the realistic step to implementation, not only forced them to recognize serious consideration by FSA but caused objection and anger among IFAs (Blackmore, 2009). In addition, the global financial recession started from the late 2008 drove the advisers and the industry into crisis (Fuller, 2010). According to Pearson (2009), year 2010 should be the exploration stage where brand-new business models will be created to comply with RDR requirements. He predicts that these models will be eventually spread and adopted to the industry by the full-commitment to RDR at the end of 2012 (Pearson, 2009).

Personal Reaction to Change

Source: Pearson, 2009, p49

Figure 2: Personal Reaction to Change

JM Glendinnings (Pensions + Insurance)

Incorporated in 1972 and based in Leeds, JM Glendinnings Pensions + Insurance (JMG) is a representative division of JM Glendinning (Insurance Brokers) Ltd, and one of the leading insurance brokers in the Yorkshire area (JMG, 2010a). Their business specialty covers all types of insurance products from life cover to investment products such as Individual Saving Account (ISA), a tax-free saving account. Despite the negative impact of financial recession in the Insurance industry (Mintel, 2009b), JMG has been steadily growing their business for three years consecutively since 2007 (JMG, 2010b). The key to their successful performance are three fold: strategic focus on the local region, financial advice highly dedicated to their clients and active cross-selling across the organization (JMG, 2010c).

As for the remuneration change, the directors in JMG highlight positive aspects for their corporate future, seeking a more transparent and effective business model (JMG, 2010c). Since the RDR announcement, a preparation process has been undergone as they planned, including customer segmentation, identification of profitable customers, and a basic pricing model (JMG, 2010c). For the next step, their target is aimed for market research, especially for what existing customer needs and wants in the post RDR world in respect with their client segmentation.

Research Aim and Objectives:

This dissertation research attempts to answer the following research question through attaining the research objectives below.

Research Question

How an IFA firm can build strong foundations to create a new and long-term business model in the post-RDR stage?

Research Objectives

Dissertation Structure:

This dissertation starts with structures of financial intermediaries in the UK and macro environmental influence on the industry. Due to the focused attention on the legitimate changes, micro views in the industry are introduced including JMG, the sponsoring company to this project. The next chapter discusses empirical review on customer needs, satisfaction and loyalty, and practical industry discussions on the new legal framework.

Literature Review

This chapter describes customer value, a marketing method to clarify customer needs, and interrelationship of customer satisfaction, loyalty, Word of Mouth (WOM), and profitability. Firstly, it starts off by defining consumer value, and then explains external influencing factors (what influences consumers). Secondly, it will illustrate customer segmentations, methods for a firm to approach to customers. After that, it details the study of and correlation among customer satisfaction, loyalty, word of mouth effect. Empirical evidence in marketing has emphasized the importance of researching on customer segmentation aligned with understanding customer needs and satisfaction (Kotler & Armstrong 2006). Freytag and Clark (2001) articulate that an effective segmentation analysis will help companies to design marketing programs that maximize customer satisfaction. In addition, massive empirical research has been conducted about relationship between customer satisfaction and loyalty (Wangenheim and Bayo´n, 2006; Garver, 2009; Fornell et al., 2010). Furthermore, customers’ types of loyalty affect recommendation of WOM, an effective corporate strategy that positively affects profitability (Wangenheim and Bayo´n, 2006).

Consumer Value

Woodruff (1997) defines consumer value as customers’ preference and evaluation of products, its performance, and the effect after consumption in order to achieve consumer’s intentions. Similarly, Morris (1999) states that consumer value is determined in a context of comparative (individual preference in products), personal (various preferences among people), and situational (context dependant) factors, and plays a central role for planning and designing marketing strategy.

Kotler et al. (2008) undertakes a different approach, i.e. a customer evaluates a company’s product or service through considering two values: total consumer value and total consumer cost. First, total value perceived from a product, services, personnel and image determines total consumer value. Second, total consumer cost includes time and cost spent for purchase, energy and psychic cost consumed in the buying process. Subtraction of the two values is called consumer delivered value – actual determinant when a customer buys a product (Kotler et al. 2008).

External Determinant of Consumer Behaviors

Consumer behaviour can be influenced by many external factors. The figure 3 explains how a consumer is affected by external factors. Each source has different scale of influence on consumers as well as time duration and number of sources of consumer. Specifically, the diagram implies reference effect by employers and friends has longer-term impact than external conditions. Logically applying the theory to the financial intermediary industry, the referral impact from a friend may last longer than the global financial recession and legitimate changes; however, the theory contradicts in terms of the influence of extending life expectancy, which would persist on consumer behaviour for a longer period than the reference group. Simultaneously, the referral recommendation (e.g. by an employer) could be more specific in terms of designating the financial institution as well as financial products than external environmental influences. Regarding to number of sources, family-related concerns may be affected by several members within the family whereas the consumer belongs to one social class, and therefore the influencing source is only one.

Figure 3: External Influence on consumers

Source: Wilkie, 1994

· Culture: Sources that prevalently influence behaviours of all consumers such as beliefs, values, shared view in society

· Sub culture: Group of people who shares peculiar values and behaviours.

· Social class: social demographic values such as job, household income, education, etc.

· Family: groups with children-centred consumption behaviours

· Reference groups and friends: Reference group can be club members, athletes, career professionals. Advice and opinions observed in those groups affects consumers’ shopping behaviours.

· External conditions: economic factors e.g. inflation, unemployment, regulations, etc

· Marketing environment: Environment setting from corporate marketing activities such as advertisement

· Situational effects: specific short-period environments surrounded by consumers

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2.3. Segmentation

Wilkie (1994) refers segmentation as a structurally organized measurement to view the market and assess consumer activities in the marketplace. Consumer groupings derived from segmenting the market enable a firm to approach customers effectively and match its product and services with customer needs (Koyler et al., 2008 and Webber, 2009); therefore, it should provide a firm with their strategic guidance (Wilkie, 1984). By selecting suitable segmentation strategies, firms can increase their profitability (Lonial, Menezes, and Zaim, 2000) .The following sub-chapters introduce two strategic approaches to segmenting the market.

2.3.1. Positioning Segmentation

Kotler et al. (2008) explains positioning segmentation as a full list of competitive benefits that a firm can deliver to a customer, and functions as to affect consumer’s purchasing behaviors. The significance of this model lies in formulating a corporate competitive strategy (ibid.). As shown in the Figure 3, in the positioning segmentation, more for more and more for the same could be classified as differentiation strategy, and all the other as low cost strategy. Empirically, differentiation and low cost strategies have been critically analyzed. There is a great danger to be stuck in the middle between these strategies (Cronshaw, 1994). Porter (1990, p5) refers it as ‘the worst strategic error’ and he exemplifies the pitfalls of stuck in the middle by Laker Airways, which started out with low cost strategy without any extra benefits. As time passed, however, the airline company added more services and flight routes (Porter, 1985). The unclear strategy confused their customers, and eventually Laker Airways was thrown into bankruptcy (Porter, 1985). As an effective solution to the issue, Porter (1985) proposes that a company pursuing low cost strategy should undertake every not-costly measure to differentiate their products and services while any cost cutting methods that do not deteriorate quality of products and services should be executed to differentiation strategy.

Figure 4: Positioning Segmentation

Source: Kotler et al. 2008

More for more

More for more proposition creates substantial benefits to consumers such as high product quality and performance seen in Mont Blanc stationary and Mercedes Benz automobiles; in return they charge higher price at the expense (Kotler et al., 2008).

More for the same

This proposition is a threat to a company pursuing the more for more strategy (Kotler et al., 2008). Highest product quality in an industry is available in a comparatively lower price.

More for less

This would be the most unbeatable proposition and some firms could realize this strategy. However, it will not be sustained in a long term because value creation usually can not be delivered without costly operational practices (Kotler et al., 2008).

The same for less

This approach enables to offer a better deal comparatively in a market such as price discounts in a whole sale industry (Kotler et al., 2008).

Less for much less

Lowest price is achievable through retaining fundamentals and omitting extras (Kotler et al., 2008). Typical example might be no frills strategy by Ryanair, a UK airline company.

*Blue and yellow parts represent losing propositions and a marginal proposition respectively.

The Three Practical Segmentations

As depicted in the following figure, the three levels of segmentation might be a more practical and detailed approach than positioning segmentation. Starting from either one of three levels, first defined is potential consumer segments, which then will be evaluated looking through one or two from the other two levels (Wilkie,1994).

Figure 5: Practical Segmentation

Source: Wilkie, 1994

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1. Segmentation by personal characteristics

By categorizing particular segments such as gender, ethnicity, lifestyles, etc, a firm can estimate consumer behaviours of the segment. Successful marketers combine psychographic and life-styles dimensions (Wilkie, 1994).

2. Benefit segmentation

Consumers characteristics and behaviours are traced back through analyzing types of benefits they sought. Taking example in a toothpaste market, lower price seeker can be classified as men who enjoy highly autonomy life and consume the product heavily (Wilkie, 1994).

3. Behavioural-measures segmentation

Behavioural similarity in purchasing a product creates preferable market segments for a firm (Wilkie, 1994). For instance, personal characteristics identified through evaluating heavy user group are vital clues for an efficient marketing program (Wilkie, 1994).

Wilkie (1994) states that segmentation by personal characteristics is very popular practice that recent marketers practically exercise. Garver (2009) partly agrees on this statement but points out the limitation of demographic segmentation – difficulty in tracking customer needs and wants. For market researchers, benefits in segmenting with demographic variables are its accessibility and cost efficiency (Schiffman and Kanuk, 2000). However, trapped by the benefits and popularity, many companies utilize demographic segmentation, resulting in the limitation of understanding client needs (Best, 2004). In order to embed real values in the demographic analysis, it is pivotal to integrate it with psychological and attitudinal study; by doing so, the demographic segmentation enables to capture actual consumer behaviour and promote business opportunities (Schiffman and Kanuk, 2000).

Wilkie (1994) regards benefit sought segmentation as an extremely popular method; and recently, Garver (2009) and Freytag & Clark (2001) suggest that the segmentation is one of the best marketing practices among marketing practitioners. Similarly, Best (2004) supports the suggestion by defining it as need-based segmentation, in which client groups are categorized based on their needs and wants, benefit sought, or attribute importance. He suggests that demographic profiles should be analyzed in accordance with the need-based segmentation (Best, 2004). What is more, empirical evidence has shown that need-based segmentation would help firms to improve efficiency and effectiveness in their marketing activities. (Albert, T.C. 2003)

Furthermore, Garver (2009) argues attribute importance is the most decisive factor in need-based segments due to limitation of the other two (client needs and benefit sought). To identify need-based segments, it should be inevitable to research on customer satisfaction analysis (Garver, 2009). Traditionally, customer satisfaction analysis has been conducted with the other two indicators; however, the result tends to be unsuccessful because most benefits and wants were considered to be imperative for customers (Garver, 2009). Therefore, he stresses practicality of attribute importance that can differentiate core benefits from other supplemental ones (Garver, 2009).

Empirically, marketing researchers have attached significance to segmentation based on consumer needs and wants in order to formulate reliable marketing strategies (Kotler & Armstrong 2006). Nevertheless, marketing specialists in the customer satisfaction study are likely to neglect information gathering to clarify need-based segments (Garver, 2009). Therefore, many marketing researchers suggest to implementing need-based segmentation along with customer satisfaction analysis (Garver, 2009, Albert, T.C. 2003, Greengrove, 2002)

Customer Satisfaction and Loyalty

Customer satisfaction is a relative value derived from differences between consumers’ expectation and product’s performance (Kotler et al., 2008). If the performance exceeds customer expectation, the consumer is satisfied (Kotler et al., 2008; Pecinová and Branská 2007; Oliver 1997). If the product performance is lower than the expectation, the consumer is dissatisfied (Kotler et al., 2008; Pecinová and Branská 2007; Oliver 1997). Bolton (1998) finds that the level of customer satisfaction is higher when a firm can retain long-term relationship with their clients than short term engagement with the recently acquired customers.

The level of customer’s perceived satisfaction at the previous purchase affects future buying behaviors of a consumer including the consumer’s willingness to pay (Johnson et al.,1995 and Fornell et al., 2010). In other words, consumers with high level of satisfaction express high willingness to pay (Homburg et al., 2005). Therefore, highly satisfied customers increase consumption of a product (Danaher and Rust, 1996), and moreover the pleased customers contribute to referral recommendation through word of mouth (WOM) – direct oral communication between consumers (Fornell et al., 2010).

On the contrary, Kotler et al. (2008) addresses that customer satisfaction does not necessarily lead to continuous purchase of a same brand. Supporting evidence of this argument is the consumer survey result in a packaged-goods segment, showing that almost half of the customers previously satisfied switched a product brand (Kotler et al., 2008). Further research on loyalty seen in brand switchers and stayers helps to provide the reasonable understanding of this survey results.

Stayers and switchers

Basic difference between switchers and stayers is past experience of switching a brand. Switchers are defined as consumers who have changed a product provider from one to another while stayers have never or not long switched a provider (Wangenheim and Bayo´n, 2006).

Customer behaviours in brand switching can be explained through two dimensions of loyalty. Ganesh et al. (2000) differentiates loyalty in two terms: active and passive loyalty. Definition of the active loyalty is the consumer’s proactive behaviours that stem from their efforts undertaken consciously and deliberately while the passive loyalty is defined as a reactive behaviour that is significantly influenced by perceived switching costs (Ganesh et al.,2000 and Wangenheim and Bayo´n, 2006).

In a relationship with previous product providers, switchers possibly have experienced dissonance, i.e. situations where a customer acknowledges the performance of a purchased product was lower than their expectation (Wangenheim and Bayo´n, 2006). On the contrary, stayers have less experience of negative gap between their expectation and the product’s performance; therefore, active effort strengthening their behaviours is not necessary (Wangenheim and Bayo´n, 2006). Hence, stayers possess less active loyalty than brand switchers (Wangenheim and Bayo´n, 2006).

The dissonance experience of consumers leads to their next behaviour to change a current brand (Mazursky et al., 1987). Due to the past experience of dissatisfaction, switchers should recognize low switching cost (LaBarbera and Mazursky, 1983). Therefore, stayers have higher switching cost, and thus perceive high passive loyalty in comparison with switchers (Wangenheim and Bayo´n, 2006).

Simply applying this logic to the Kotler’s example in the previous section, it could be reasonable to state that satisfied customers switched the brand due to their high active loyalty whereas the other half of satisfied customers were the stayers possessing high passive loyalty. Further analysis on switchers provides an insight into customer profitability.

Referral switchers and other switchers

The switchers can be classified into two levels: referral switchers and other switchers (Ganesh et al., 2000). Referral switchers are consumers who have changed a product provider in association with positive WOM while other switchers are customers who have chosen a provider through other channels such as advertising and direct mail (Wangenheim and Bayo´n, 2006).

WOM provides behavioural differences between stayers and switchers whereas customer satisfaction and loyalty demonstrates attitudinal aspects of the consumer behaviours (Wangenheim and Bayo´n, 2006). Reichheld and Teal (1996) andWangenheim and Bayo´n (2006) demonstrate that referral switchers show strong loyalty in their product provider.

When customers conduct decision making through high level of cognitive processes, they tend to contrast and overemphasize differences between actual values and their perceptions of the product (Wangenheim and Bayo´n, 2006). During the highly logically thinking process, contrast effects do not continue so long (Richins and Bloch, 1991). On the other hand, effectiveness of referral, i.e. recommendation efficacy influenced by other consumers, will persist longer than contrast effects, and the consumers enhance their loyalty by absorbing the positive referral effect during consumption (Oliver, 1997). Thus, active loyalty of referral switchers will be higher than other switchers (Wangenheim and Bayo´n, 2006).

Loyalty and Profitability

According to Reichheld and Teal (1996) and Reichheld, Markey, and Hopton (2000), subtle improvement in customer loyalty substantially increases profitability.Reichheld and Teal (1996) state that highly loyal consumers will increase profitability of a firm by their contribution to high priced products, high consumption, and positive referrals to other consumers. As referral switchers equip the highest active loyalty as well as the highest satisfaction and WOM recommendations among stayers and switchers (Wangenheim and Bayo´n, 2006), it might be expected that referral switchers would be the highest profitable consumers.

In contrast, Zhang et al., (2010) disagreed with the positive relationship between loyalty and profitability. Reinartz and Kumar (2003) pointed out that customer loyalty did not increase corporate profitability. In the similar way, Gupta and Lehmann (2005) expressed their sarcastic views to current marketing trends. They argue that companies intensively invest on client loyalty programs that yield fruitless results (Gupta and Lehmann, 2005).

As Gupta and Lehmann (2005) indicates, in recent corporate practices, there seems to be a war of loyalty program, i.e. too many company compete in a market to increase consumers “loyalty” and repeaters. In a situation that participating in loyalty programs is very much common, brand switching cost, especially for brand switchers, might be increasingly lowering. This assumption leads to the hypothesis that in the market with switching cost extremely thin, consumer behaviours seen in brand switchers with high active loyalty might not yield high corporate profitability. However, in a market with relatively high switching cost, it is expected that loyal consumers would contribute to the profitability of a firm.

IFA industry: seeking a new business model and client needs

In the post RDR world, many IFAs predict that financial advisers will not be able to operate their business as they used to (Critchley, 2010, Shelton, 2010). Some practitioners predict that total charging fees to the customer will not be changed (Critchley, 2010 and JMG, 2010c). However, in their business model, there seems to be a fundamental issue – unbalance between client needs and service offerings. According to the research to financial advisers, Davidson (2010) reports that 40% of the IFAs lost some of their top profitable clients due to mismatch their service and their client needs. He believes that meeting client needs is indispensable, rather than concentrating on sales expansion (Davidson, 2010). In the similar way, Shelton (2010) points out that what financial advisers perceive as valuable in their services is often different from what their clients really want. Legal & General (2010), a British financial company, highlights the misalignment based on their research. As Figure 6 shows, clients highly appreciate direct relationship with financial advisers whereas little value is attached to servicing and administration, which IFA spends their time the most (Legal & General, 2010). In accordance with the research result, possible implications can be assessed in two points: high client-needs services and underestimated services by client.

As for high valued services, an IFA firm should strengthen consulting services through enhancing client-specific knowledge and high relationship management with its client (Mass, 2010). In regard with research on insurance brokers and their corporate clients, Maas (2010) states that the future of insurance brokers lies in consulting services due to client-needs’ shifting away from transaction services. The figure 7 demonstrates employment strategy of insurance brokers, which more clients consider future focus on consulting services than contemporary focus. The other implication is justification to a simple corporate practice such as eliminating some work or lowering service level of low evaluated tasks. This interpretation may involve very risky decision because the grade-down could de-motivate existing profitable clients. Instead, Shelton (2010) suggests categorizing clients by the revenue income to IFA and differentiating services to each classified group. Many star players in the IFA industry recommend strategically focusing on their profitable clients as well as establishing simplified processes to deliver values to clients and (Davidson, 2010; Mark, 2010; Shelton, 2010).

Figure 6: Perceived Client Value vs Adviser Time Spend

Source: Legal & General, 2010

Figure 7: Contemporary and Future focus of the Broker’s Employment





*point: company without in-house broker; triangle: company with in-house broker

(Maas 2010, p6)

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Starting off with the definition of consumer value, this chapter described external influence on consumers, marketing segmentation, and customer satisfaction and loyalty followed by the business model discussion in the financial intermediary market. Each source of external influences can be measured by three dimensions, breath of influence, and time duration, and number of sources (Wilkie, 1994). One of the implications from the theory is external influence is more specific and shorter-term effect than reference group and friends. However, logical analysis produces the theory’s contradiction that some external influences may provide more general and longer term influence.

Segmentation chapter comprises two types of techniques: positioning and practical segmentation. In the positioning approach, possible customer segments are categorized in a mutually exclusive way by benefit and price, and the effective segments could be labelled as low cost and differentiation strategy. The re-categorization provides the theory’s pitfall – a risk to be stuck in the middle if the segmentation is wrongly operated. At the end, a solution for both strategies was introduced by referencing Michel Porter’s statement. In contrast, the practical segmentation helps to identify two popular methods: segmentation by characteristics and benefit sought. Although the first segmentation possesses a trap, it will be overcome by integrating it with psychological and attitudinal study (Schiffman and Kanuk, 2000). A benefit sought method, i.e. need-based segmentation, gives the instruction to marketers that demographic parameters should be analyzed based on customer needs (Best, 2004). The key value in the segmentation is attribute importance, with which real customer needs can be identified (Garver, 2009).

High customer satisfaction not only leads to high willingness to pay (Homburg et al, 2005) and increased product consumption (Danaher and Rust, 1996) but also produces positive effect on spreading WOM recommendation (Fornell et al., 2010). However, satisfied customers with active loyalty are not likely to continue purchasing a same brand due to their lower switching cost than stayers (Wangenheim and Bayo´n, 2006). Amongst switchers and stayers, referral switchers show the highest levels of active loyalty and satisfaction as well as WOM effect (Wangenheim and Bayo´n, 2006). If consumers with high level of loyalty are profitable to a firm as Reichheld and Teal (1996) insists, it might be assumed that referral switchers would be the most profitable consumer group. Nevertheless, the opposing view, i.e. no positive relationship between loyalty and profitability as Zhan et al. (2010) argues, could be true where switching costs are extremely high in particular for a high competitive market with intensive loyalty programs.

After the new regulation implemented in the IFA industry, there will be little space for continuing the same business model as IFA firms do currently (Critchley, 2010, and Shelton, 2010). One of the critical issues in the financial intermediary is differences between client perception and adviser time-focus. Filling the gap could be attained through two practical solutions. Firstly, in order to increase the quality of a high valued section such as presentation meetings, financial advisers should enhance consultation services (Maas, 2010). Secondly, it is imperative to differentiate services between profitable and non-profitable consumers (Shelton, 2010).


Research Overview and Philosophy

In order to identify clients needs, the most effective and popular method is market research (Des, 2010). In the process of the market research, reviewing existing data including data analysis takes a critical role (Des, 2010). As discussed with JMG directors, two existing resources to identify client needs were found: Experian Financial Strategy Segments (FSS) and JMG internal database. Experian is the credit bureau in the UK and FSS is the report that illustrates all their UK consumers profiles segmented into 13 groups, and developed to support financial institutions to provide their targeted customers with their financial services (Experian, 2010). The segmentation categories were already labeled on the JMG clients, and thus by analyzing FSS report, holistic research, i.e. total potential needs of JMG clients was realized. The data summary retrieved from the JMG database produced internal client purchasing behavior, where the level of customer satisfaction and loyalty could be observed. After consideration of the FSS analysis and internal data research, market research was designed and conducted. The following figure briefly summarizes feasibility of each method to the research objectives.

Figure8. Resource Feasibility to Achieve Objectives

As centered major problems involving in JMG, the sponsor of the project, the research methodology was focused upon action research, a philosophy that highlights the importance of achieving the research objectives through taking actions over a period of time and synchronizing practitioners’ needs and researchers (Saunders et al., 2009). The spiral of action research starts from clarifying a context and purpose, and then continues to the diagnosis phase, which determines planning processes and actions to be taken (Saunders et al., 2009). After the evaluation of the performed actions, further sub-spiral processes, diagnosis, planning, taking action, evaluating, will be pursued (Saunders et al., 2009). The following figure details each step of action research conducted in this dissertation.

Research Design

Design of Existing Data Analysis

To analyze client segmentation, FSS was readily available for analysis in internal network folders on JMG server. For the purpose of identifying client needs and loyalty, the JMG database, called FIRST, was always accessible at the JMG office. The database enables wide range of quantitative researches on client information from referencing, updating and creating financial records with clients to generating customized reports. FIRST has 53 categories and 646 sub-categories (please see appendix 1) although not every data was useful for data analysis. For instance, some useful data e.g. relationship start date with JMG showed “blank” (missing data) in many client database. Thoroughly selecting useful and feasible variables, client attributes (client name, age, FSS segmentation, etc) and product information (product name, purchased data, current status, etc) were designated for client analysis.

Appendix 1: Sample screen of FIRST (Query builder)

As discussed in Literature Review section, financial advisers will have to focus on profitable clients (Davidson, 2010; Mark, 2010; Shelton, 2010); therefore, client needs of un-profitable clients might not be relevant for strategy formulation in the post RDR stage. Basically the JMG managements also agreed on this except for one specific adjustment – excluding top 50 clients who JMG advisers regularly contact and are considered to require highly customized advice. Harmonized with the JMG directors’ preference, top 51-150 clients were selected for data base analysis.

Market Research Design

Market Research Typologies

Des (2010) introduces typologies to conduct market research: observation and communication (posting, email, phone, and face to face). Clearly, observation is not appropriate in this dissertation due to privacy of JMG clients. One of the methods reasonable to the purpose of this research was telephone interview; however, this turned out to be difficult to achieve at the time. This is firstly because a company staff equipped with corporate-specific and product knowledge had to be an interviewer so as to retain vulnerable relationship with clients. At the same time, due to time-consuming feature and the company situations (e.g. thinly allocated staffs), it was decided to exclude phone-interview from the methods in this survey. For the same reason, focus group (a facilitator leads a group of interviewees based on a previously designed structure) was dropped off from the project scope.

Questionnaire was also an attractive tool to investigate client honest opinions due to physical and psychological distance, with a straightforward structure once its design was completed. Other benefits were larger sample size and comparatively easier access to clients without breaching fragile client-relationship than interview and focus group. In spite of the long corporate history, conducting formal questionnaire to JMG clients was the first approach to ask feedbacks from clients.

Questionnaire Sampling

Email and posting address can be retrieved from the JMG database. After filtering only applicable information i.e. extracting not-appropriate clients such as no mail-shot clients, address missing, etc, created was the client contact list with total 1433 clients, comprising from 1133 and 300 for mailing address and email address respectively.

Henry (1990) introduces two types of sampling methods: non probability sampling (some clients have no possibility to be selected) and probability sampling (each client has possibility to be chosen). Combined with top51-150 purchasing behavior analysis, it was obvious that questionnaire samples from the targeted profitable clients would actualize further in-depth analysis and enhance reliability of the research. Moreover, in terms of convenience and cost efficiency, all the email address was considered to be fully utilized. For these two reasons, non-profitable sampling was inevitable to this survey.

Nevertheless, only sampling the targeted clients and email address holders might increase the biases in the survey. Therefore, profitability sampling was essential to be conducted apart from the two sampling methods. According to Henry (1990), probability sampling can be achieved in four ways: simple random sampling (each sample has equal possibility to be selected), systematic sampling (choose one random start and pick up every i th unit e.g. every 10th), stratified sampling (divide total sample size into designed strata, then conduct random sampling in each stratum), and cluster sampling (select samples from only designated clusters).

Due to the clearly defined segmentation and profitability focus, it might be ideal to examine samples with the proportion differentiated in each segment, hopefully achieving similar to the proportion of the total client population. In this sense, simple and systematic samplings were unsuitable because of high possibility to end up with undesired consequences e.g. selecting many samples other than the focused six segments. In contrast, cluster sampling could be a well-fitted method in terms of choosing only focused segments; however, this was not effective to reduce human biases by selecting certain groups. Consequently, after discussion with JMG managements, stratified sampling that enables to randomly choose samples from each stratus (segments), was decided to be the best fit for this research survey.

The distribution of questionnaire was designed in two ways: email and posting. The number of clients with email addresses stored in system reached to 300 including corporate and individual accounts. Whereas sending emails through JMG corporate email account was costless, the second class mailing costs 32 pence in one way and 64 pence including return mail cost. During the course of discussion with the JMG directors, one hundred of sample size in posting distribution was considered to appropriately satisfy the aim of the research. This is mainly because 400 accounts including both email and posting comprise almost 30% of total clients’ bank as well as the management preference, minimizing posting costs if reasonable. At the same time, posting was expected to be less in response than email. For these reasons, it was agreed upon the size of mailing clients.

Hence, the hybrid method of profitability and non profitability sampling was executed to questionnaire and the entire sampling methods were summarized in the following figure.

Figure9: Hybrid method of profitability and non profitability sampling

Questionnaire Design

A questionnaire design conducted to understand consumer behavior varies from firm to firm; however, most organizations are unsuccessful to yield fruitful results because of difficulty in relating with what customer know about product features and what actually customer wants. (Grunert et al., 1995; Reynolds and Gutman, 1988). One of the best methodologies to solve the issue is means-end chain (MEC) model (Wu and Fu, 2010). The key advantage of the model is to capture the perceptions of consumers during the process of their usage and consumption of a product and service (Grunert et al., 1995; Reynolds and Gutman, 1988). Indeed, it would be very problematic to analyze complex financial advisory processes from providing financial advice to actual “consumption” of insurance products.

In the MEC model, the consumers’ cognitive process is explained through three variables: product attributes, benefits, and values (Reynolds and Rochon 2001). The basic concept is that product attributes are means for consumers to realize their ultimate goals through consuming and utilizing product attributes (Gutman 1982). In the process of usage and consumption, product attributes create a certain benefits that achieve consumers’ desired ends in regard with value satisfaction of the products (Wu and Fu, 2010). Therefore, the three variables are considered to be inter-connected through the decision making process in consumers behavior (Wu and Fu, 2010; Gruber, Reppl, and Szmigin 2007). Furthermore, product attributes can be classified into concrete attributes (e.g. pricing and package) and abstract attributes (e.g. quality and design) (Snelders and Schoormans 2004). Similarly, benefits can be two fold: functional and psychological consequences such as helping to dress up attractively and satisfying my thirst respectively (Gutman 1982).

As discussed in Literature Review, measurement by attribute importance, i.e. ranking based questionnaire, is critical to successful satisfaction analysis (Garver, 2009). In this dissertation research, however, it was determined not to utilize attribute importance. This is firstly because it was discussed in the course of review with JMG directors that slight increase in uneasiness when answering questionnaire might escalate risks to deteriorate data quality. Simultaneously, it was very confusing for project members including the JMG managements to fill out a ranking questionnaire designed by major online survey providers such as Qualtrics, Survermonkey, the survey system of Leeds University, etc; thus, it was decided to use other forms (e.g. benefits) rather than attribute importance.

In the financial intermediary industry where financial products are already designed by product providers, product attributes could be more concrete rather than abstract. For example, the attribute could be variety of products’ choice that financial advisers can offer to their clients. Benefits of the intermediary are advisory services such as initial meetings to capture client needs, reporting, and ongoing review. Client values could be seen in the satisfaction level of financial advisers e.g. their knowledge, reliability, professionalism, etc. By offering those services, clients can achieve their desired end, i.e. matching their needs with the financial products through IFAs’ advice.

Synchronizing with themeans-end chain model, the questionnaire was designed to understand the level of client satisfaction, client behavioral differences between passive and positive loyalty, and the future probability of WOM recommendation. At the end of questionnaire, client feedbacks about remuneration changes in the post-RDR were enquired.In addition, the questionnaire was basically designed to collect quantitative data. The primary aim of the design is to ease respondents’ burden of answering questions and increase the response rate. The quality of the questionnaire was thoroughly reviewed by JMG directors. For opinion and recommendation based questions, qualitative data was also utilized. Please see appendix Questionnaire.


To sum up, three different techniques were employed: FSS segmentation analysis, client behavioral analysis by exploiting internal database, and market research on JMG existing clients. Deep exploration into the FSS report helps to indentify potential client needs in the divided segments. Effectively utilizing the FSS segmentation, internal data research was conducted on top 51-150 profitable clients. Market research was carefully selected to questionnaire due to fragile relationship with clients and the current resource issue inside JMG.

In order to synthesize with the database analysis, sampling in questionnaire included top51-150 clients. Due to cost effectiveness and accessibility, all the clients with email address were also selected for sampling. To reduce biases, probability sampling technique was employed. Total sample size was determined to be 400, 300 and 100 for email and posting respectively.

Initially, contents of questionnaire were designed in respect with the MEC model (attributes, benefits, and value). Along with the discussion in literature review, the questionnaire was developed so as to analyze the level of satisfaction and loyalty, and WOM effects as well as inquiries about the pricing model after the legitimate changes in 2013.

Findings and Analysis

The FSS report

Report overview

The FSS report finds 13 segments that represent consumer profile of the total UK adults. The significance of the report lies in direct or indirect implications of potential customer needs in each segment. It not only clarifies basic information (age, income, children, occupation, etc) in each segment but also combines them with client concerns, attitudes, and financial behaviors. As introduced in Literature review, Schiffman and Kanuk (2000) state that demographic profiles are exploited effectively along with analysis on psychological and behavioural analysis. While the FSS report directly exemplifies product preferences of consumers in some segments, the segmented profiles also help to investigate potential client needs regardless of the direct implication. Combining these factors altogether, identical consumer behavior is analyzed in mutually exclusive segments.

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Segmentation Focus

Although no segment is lack of importance, analyzing all the 13 segments equally is lack of focus. The following figure 10 shows wealth, UK proportion, JMG proportion in each segment. Focusing on wealthy segments with higher proportion than UK total proportion, identified were six strategic segments: . Total these groups comprise more than 70% of total JMG clients.

Figure 10: Proportion by FSS segments

(JMG, 2010)

Flourishing families are a customer segment with the highest population in JMG. Having a child-centered lifestyle, the families in the segment are concerned about their children’s future prospect (Experian, 2010). This indicates that they might be interested in savings account such as ISA. Besides, due to relatively young age (35-45) and their acknowledgement of mortgage risks, many of them are keen to purchase mortgage protection plan (Experian, 2010). Compared with Flourishing families, Credit-hungry families earn low incomes with tighter financial controls on a daily basis (Experian, 2010). As they are subject to heavy balance on their credits because of their high expenditure and lack of awareness of saving (Experian, 2010), there would be potential opportunities for financial advisers to provide proper monetary guidance for long term perspectives as per their needs.

The wealthiest and highest-salaried group is Gilt-edged lifestyles, who aged 40-50s and prioritize money as the highest in their life (Experian, 2010). As shown in above figure, the statistic that the JMG proposition of the group is higher by 10% than total UK proportion could simply imply tremendous growth opportunities for JMG. However, one behavior that may affect negatively on financial advisers is their astuteness which motivates them to self-research on investment opportunities in an online market. Through constantly contacting with clients and integrating financial advice with their personally collected information, IFAs’ financial advice could be sought more intensively by the affluent group than ever. Similarly, Mid-life affluence group is one of the wealthiest segments. In comparison with Gilt-edged lifestyles, the group went through more years in their lifecycle, still earning averagely good income. As mortgage has been almost paid off and their children have been grown up, the affluent group may be well prepared for a retirement stage (Experian, 2010). Thus, financial advice might be better focused on enhancing their pension plans and further saving options.

In contrast, modest mid years segment is placed in similar life cycle to the two affluent groups, and earns below-average income with financially dependent (Experian, 2010). As the segment is not sophisticated financial consumers and it intends to invest in further children’s education (Experian, 2010), financial advice of saving plans might be effective for consultation. Amongst the six segments, Advancing status is the most senior group, which can afford comfortable lifestyle due to their grown-up children and above-average income (Experian, 2010). Aged between 50 and early 60s, consumers in this group do not see necessity in purchasing financial investment products (Experian, 2010). Therefore, it might be fewer prospects to provide financial advice to them unless they have individual specific needs to financial products and services.

Please refer to appendix 2 for more detail description of each segment.

Appendix 2: FSS descriptions

Internal Database Analysis

Client purchasing behavior through database analysis

Fugure11: Purchased Products by FSS groups

· Pension: pension products that support clients’ retirement planning such as basic pension funds and flexible options at retirement.

· Life cover: insurance products that assures clients’ financial situations by paying lum-sum payment at death, injury, etc.

· Investment: investment products that can be expected higher returns and risks compared with other insurance products. ISA is also included in this category.

· Corporate: insurance products that reduce future risks such as shareholder cover and corporate pension funds.

As summarized in the Figure 11, all the purchased products by Top51-150 profitable clients were categorized in four features: pension, life cover, investment, and corporate. Basically, it can be observed that product needs vary depending on the Experian segments. As one of the distinguished demographics in Gilt-edged segment is senior executives and business owners, their preference of corporate products, in which the affluent group is the highest proportion amongst all the segments, is understandable. Similarly, the data result is reasonable in light of the observation that above the total average in investment products, i.e. more than 20%, are Group G, H and J – the top three wealthiest groups. Due to child-centered lifestyle of Flourishing family, life cover purchase is the highest out of all the other segments. In the similar way, the Modest mid-years segment shows the second highest proportion of life cover purchase; the primary reasons can be considered as below-average income to secure their future and their careful style of investment. Right before the retirement age, very conservative consumer behaviors in the Advancing status group is peculiarly seen in their preference of pension products. On the other hand, one of the consumer behaviors that do not match the Experian segmented profile is the dominant purchase of pension funds by Credit-hungry families. Occupied by heavy debts, the group lives the tightest lifestyles in financial among the six segments (Experian, 2010); therefore, a question arises if there would be affordability for them to invest in pension funds that will be paid out after their retirement. Possibly, this is because of the data source of this analysis, focused on profitable client groups in JMG. Therefore, the consumer behavior in Group F did not follow the general characteristics of FSS, and showed the highest pension product purchase amongst all the segments.

Appendix 4: Affluence and Life stage by FSS

Fugure12: Buying frequencies by FSS


Figure 12 describes unique purchasing behaviors of top 51-150 in each segment. Client 1, 2, and 3 denote a JMG customer group with purchasing record only once, twice, and more than three times respectively. (Please see appendix 4 for affluence and Life stage by FSS.) At relatively younger stage of life, i.e. Group E and F, client 1 group dominates the proportion. As the life cycle precedes further, the proportion of Client 2 and 3 group increases. For example, more than 80% of clients purchased financial products from JMG more than twice in Group G, H, I, and J.

On the other hand, Figure 13 shows average months to next purchase, i.e. the time-length of clients’ pose until their next purchase. Pi-Pk denotes the time spent from the i th purchase to the k th purchase. The first outstanding finding is that Client 2 purchases the 2nd product from JMG after more than 8 years spent since their first purchase. This does not necessarily represent that they have never contacted with JMG till the 2nd purchase; however, in a pre-RDR world where a commission based business model is standard, it might be clear that JMG has received no additional revenue income streamed from those clients for a long time.

The next finding in Figure 13 is that time spent to next purchase in Client 3 at P1-P2 is almost the half the length of Client2. This indicates that Client 3 might be clients with high loyalty to JMG, and the more they purchase financial products through JMG, the more frequently they contact with JMG and loyalty level enhanced. However, cautious analyzers may point out the opposing view such as the possibility that some segments could be significantly influencing total purchasing frequency of Client 2 and 3. Indeed, when analyzed by segmentation as in Figure 14, the client behavior at P1-P2 include some volatility in some segments, in particular with Group E and G. In fact, Client 3 in Flourishing families (Group E) tend to seek advice from JMG in less than one year since the first contact whereas the same behavioral group in Gilt-edged lifestyles (Group G) spend more than 8 years, one year more than the Client 2 in Group G. In the other segmentations, Client 2 holds the blank time twice as long as Client 3 does as observed in the total trend. Although slightly erratic tendency was discovered in Group G, it might be fair to state that Client 3 is likely to buy from the same brand, JMG and thus, the most loyal client group amongst Client 1- 3.

Along with the logical arguments, this implication, Client 3 as loyal consumers, was agreed in a presentation meeting with JMG directors. At the same time, all the participants also consented to the probability that consumer behavior of Client 3 would be the representative model of clients that drives profitability to JMG, and therefore the client needs should be further analyzed. The purchased product records by Client 3 are summarized in Figure 15.



Comparative analysis with Figure 11 produces insight on what loyal client needs. Total average shows slightly stressed focus on investment product. This result seems to be driven by Gilt-edged lifestyles, whose trends to purchase investment products increased 11%. The similar trends can be seen in Flourishing Families increased by 5 %. In contrast, more conservative behaviors can be seen in Mid-life affluence and Modest mid-years groups. This indicates that more concerns on their risk-adverse behavior to secure their retirement life. The most interesting behavior of Client 3 is seen in advancing status, the highest investment preference amongst the six. The oldest group is financial stable; therefore, they might afford to invest in this group of products.

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* JMG provides mortgage products; however, the product category is excluded due to the requirement of higher access level to the FIRST than my level.

Appendix 5

Appendix 6: Potential Client Needs: Total top 51-150

Appendix 5


Four weeks have been spent for data collection, and with effectively reminding clients through email reminder and phone calls, 92 responses out of 400 questionnaires were received. This means that the total response rate reached to 23% in total (18% and 25% in posting and email respectively). The answered data that respondents kept unmarked both in online and paper questionnaire were categorized as “N/A”. As for total demographics of respondents, the first and second majority age groups were 55-65 and 41-55 respectively; the combined total comprises 62% of total proposition. The salaried under £30,000 was the highest proportion while the other income ranges can be described as relatively equally distributed. Probably this is because those aged more than 55 years old, 57% of the total population, could include already retired clients. More than 53 % of respondents keep contact with a JMG adviser at least once in half a year, whereas the other half of the clients conducts spontaneous approaches, i.e. event-driven and client contact initiation.

Fugure16: Questionnaire Results: Demographics



Contact Frequency





Income: aged above 55

Figure 17 below demonstrates popularity of product categories and top three products among those groupings. The questionnaire result shows that pension is the most popular genre among the five product categories as the same trend can be seen in the database analysis of top 51-150 clients. Interestingly, led by product popularity of ISA and investment bond, investment products scored the second highest votes in spite of the global economic recession. Among corporate brands, a pension related product is the highest in client demand.

Fugure17: Client Needs: Product categories and Top 3 Products

Popularity of Product Categories

Top 3 Products

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As shown in Figure 18, most of the categories can be said to be of indispensable to clients if the top two ratings (very important and quite important) can be regarded as clients valued services. In demographics analysis, the data result described more than half of the respondents answered contacting more than once in half-yearly, but the figure shows regular contact is less valued than other advisory services. In contrast, clients highly value their financial adviser’s capability to grasp their needs. This supports the statement of Maas (2010) – necessity of focus on strengthening consulting services by satisfying client specific knowledge. Understanding client needs is the most valued service far beyond other criteria, and only the valuable additional service was accessibility to a dedicated point of contact as shown in Figure 19; therefore, these survey results may indicate that clients do not necessarily require regular contact, other reporting, reviewing, or analysis as long as financial advisers fully understand client needs and objectives and clients can reach the designated a financial adviser or a supporting staff as and when they wish to.

In general, the level of satisfaction was observed to be very high as shown in Figure 20 (satisfaction with JMG advisers) and Figure 21 (satisfaction with JMG company). It was a quite amazing result that the answered as the highest two levels were every respondent for JMG financial adviser and 96% of total respondents for JMG, except for a small portion of unmarked results. Strength of JMG advisers can be to accomplish their required tasks professionally in a friendly approach and with ambitions to support clients. Comparative weakness of advisers was managing client needs, which showed the lowest scores in “very satisfied”. This could imply that clients are not sure enough if their needs were fully reflected in their services; therefore, improvements should be encouraged in client needs management. On the other hand, the total financial advisory process of JMG such as administration and sales support was lower in satisfaction than that with JMG advisers, generating 2 % of dissatisfied ratings in after sales support, flexibility, and responsiveness. Still, the dissatisfaction rate is extremely low, and thus the two types of satisfaction diagram can suggest that the business model of JMG is counted on financial advisers rather than JMG as an organization.

In the question asked about RDR remuneration change to transparent, client-agreed business model, the respondants’ reaction was AAAAA. The new model sounds not expensive

RDR change is a transparent business model, so it should be fair and reasonable to consumers. However, 41% of clients feared that the new model seemed expensive, and would refuse to pay a “client-agreed” fee. At the same time, 39% of respondents think the RDR concept is difficult to understand. Taking it into consideration that the 67% responded want to know more, the questionnaire result implies that to satisfy clients’ thirst for knowledge of the transparent model, financial advisers should enhance their communication with their clients, in particular with how exactly RDR change will impact the clients.

Figure 23 describes how many clients have been loyal to JMG and identifies stayers and switchers. Firstly, the pink highlighted parts mean stayers, clients who never received financial advice before and after their relationship with JMG. Secondly, all the other parts are switchers who sought other sources of advice before or/and after their contacts with JMG. Among the switchers, there were clients shifted to stayers after the advisory experience with JMG, as shown in the blue highlighted part. In this dissertation, they will be called as loyal switchers.

As discussed in Literature Review, switchers show high active loyalty while stayers possess high passive loyalty (AAAAAA), and the highest active loyalty and WOM effectiveness is seen in referral switchers (AAAAA). Due to the dissertation centered on loyal clients, referral switchers were defined as the loyal switchers who answered that they were referred either by friend, relative, 3rd party, employer, or business-related contact. The rest of the switchers were a non-loyal consumer group who received financial advice from other advisers after becoming JMG clients. Thus, in this dissertation, the discussion and analysis focus on stayers, loyal switchers, and referral switchers.

Figure 23 shows differences of satisfaction level among stayers and loyal switchers, and referred switchers. In accordance with very high satisfaction level in total and to differentiate results of each question, the figure focuses on clients who answered “very satisfied” in each question and illustrates the differences of the proportion between total respondents and each loyal client group. The highlighted in blue and pink are questions with more than positive 5 % and less than minus 5 % differences. For example, stayers’ satisfaction level in knowledge and competence was 85%, i.e. 76% plus 9 %.

The most outstanding finding in the figure is that loyal switchers show higher level of satisfaction in every level both with adviser and JMG than total respondents. Similarly, stayers perceived higher satisfaction with their financial advisers, although JMG administration services were not very much satisfactory as financial advisers were. One of the most interesting findings in this analysis is that referred switchers were less satisfied than the total trend. Specifically, the satisfaction rating plunged sharply in adviser’s client-needs management, and JMG corporate responsiveness and administration support. This result contradicts AAAs statement – referred switchers perceive higher satisfaction than the other switchers and stayers.

On the other hand, the result asked if respondents would recommend JMG to a friend, colleague, or family is shown in Figure 24. 88% of total respondents were found to show positive recommendation effect, answering definitely or probably. Specifically, referral switchers expressed the second highest willingness to recommend JMG, slightly behind loyal switchers. Compared to the loyal and referral switchers, WOM effect of stayers showed almost similar rating to the total trend including slightly higher proposition of unmarked respondents.

Possible implications of these results could be that due to no contrast effect, i.e. no past comparison experience with other advisers, stayers do not have so high expectation to financial advisers that they possess high “blind” satisfaction. In addition, they were identified as senior group with 88% of their total population aged more than 55 (please see appendix 7). Therefore, it can be stated that high passive loyalty integrated with seniority yielded high satisfaction. On the other hand, loyal switchers showed much higher satisfaction and WOM recommendation than total respondents. They might have had dissonance with the past relationship with other advisers (AAAA), and switching cost was lower than stayers (AAAA). In spite of their lower switching cost, their new experience with JMG and its financial advisers could be sufficient enough to recover the past misalignment and satisfy their financial needs. Moreover, it is highly probable that their tremendous satisfaction levels have been attracting the clients and keeping them stable relationship with JMG. This could imply that they may have high passive loyalty, compared to non-loyal switchers who have switched after relationship with JMG.

Contradicting result with literature review, lower satisfaction by referral switchers, could be related with a corporate specific reason. Cross-selling financial products across JMG group, JMG corporate division has historically and constantly referred their clients to JMG (JMGd, 2010; result reporting meeting). Corporate clients who have purchased individual products should be highly loyal to JMG corporate division but not necessarily with JMG (JMGd, 2010). The historical multi-relationship effect could have driven their switching cost very high without requiring high satisfaction level with JMG. Further implication of this analysis might be their potential growth opportunities for JMG through reinforcing the satisfaction of referred clients, especially by increasing responsiveness and effectively capturing and managing client needs.

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As discussed in Methodlology section, this questionnaire was designed to identify which FSS group a respondent belongs to and if the respondent is Top51-150. One of the limitation in this research is the samAs the questionnaire sample is not

As a result of collection,

As shown in Figure 25, each FSS shows different clients’ needs in financial products. While Flourishing families and Credit-hungry families had equally distributed interests in all four financial genre, preferences in corporate and investment products were seen in Gilt-edged lifestyles.

Corporate product: it could be preference as employees, uncertain from this survey