Customer Relationship Management of Lloyds Banking
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Published: Wed, 07 Mar 2018
This chapter provides the brief introduction of research. Furthermore, it also discusses the aims, objectives of the research questions and scope of the study.
1.1 TOPIC OF THE RESEARCH
Customer Relationship Management of Lloyds Banking Group PLC; A Critical Evaluation
1.2 INTRODUCTION TO RESEARCH
Peter Drucker said, “The purpose of a business is to create customers”. Customer Relationship Management can be the single strongest weapon we have as manage to ensure that customers become and remain loyal. Customer Relationship Management, or CRM, is an essential part of modern business management. CRM concerns the relation between the organisation and its customers. Customers are the lifeblood of any company be it a global corporation with thousands of employees and a multi-billion turnover, or a sole trader with a handful of regular customers. CRM is the same in principle for both examples.
Globalization and technology improvements have pushed companies into hard competition. In this new era organisations are targeting on managing customer relationships, mainly customer satisfaction, in order to maximize revenues (Constantinos 2003). Today, marketing is not just developing, delivering and selling; it is shifting towards developing and maintaining equally long term relationships with customers (Buttle, 1996). This new business values is called relationship marketing (RM), which has involved significant interest both from marketing academics and practitioners (Gronroos, 1994).
The Greek philosopher, Epictetus said that “what concern me is not the way things are, but rather the way people think things are” (Szwarch, 2005, p.3). The concepts of consumer satisfaction were depending on the thinking of consumer. Research suggests that customer satisfaction, basic concept of relationship marketing, is important in achieving and retaining competitive advantage. Research studies have discovered that retaining current customers is much less expensive than attracting new customers (Desatnick, 1988; Stone et al., 1996; Bitran and Mondschein, 1997; Chattopadhyay, 2001; Massey et al., 2001). The best way to retain customers is to keep them satisfied, a number of studies have shown that customer satisfaction can guide to brand loyalty, repurchases intention and repeat sales (Day, 1984; Swan and Oliver, 1989; Oliver, 1999). Customer retention, in turn, seems to be related to profitability (Oliver, 1999).
Relationship marketing is becoming significant in financial services (Zineldin, 1995). If a bank develops and sustains a solid relationship with its customers, its competitors cannot easily replace them and so this relationship provides for a continued competitive advantage (Gilbert, 2003). Moriarty et al. (1983) has suggested relationship concept in the banking sector which states that banks can increase their profits by maximising the profitability of the total customer relationship over time, instead of looking for to get more profit from any single transaction. Perrien et al. (1992) observed severe competitive pressures that forces financial institution to restructure their marketing strategies by developing into long-term relationship with customers. And banking industry purely related to financial services, which needs to create the trust among the people.
This research is exploratory in nature and design. The data which is collected is going to be mostly primary data collected from the relevant persons within the bank. The data has gathered from the face to face interviews with the help of structured and semi-structured questionnaire with those persons. The above describe interviews has last 40 (fourty) to 45 (fourty five) minutes (approx). On the other hand the researcher has decided to collect primary data from random interviews of Lloyds Banking Group’s customers. Sample size is around 200 customers and of structured questionnaire.
But of course this research paper has relied on reviewing the various secondary data available from various researches such as books, magazines, website, previous research and publication etc. The collected data has been analysed by graphs, table and pi chart drawn from Microsoft excel.
1.3 AIM OF THE RESEARCH
The aim of the research is to study why CRM is important in bank, how the CRM works in banks and also the effectiveness of Lloyds Banking Group in obtaining long term customer relationship, customer loyalty, and customer satisfaction by the use of CRM. And also suggest feasible recommendations to Lloyds Banking Group to increase the customer satisfaction and market share by the effective use of CRM.
1.4 OBJECTIVES OF THE RESEARCH
The followings are the objectives of this research;
- To study how critically practised in Lloyds Banking Group
- Analysis the data mining process of Lloyds Banking Group
- To find out how the bank segments their customers
- To analysis how the bank retaining their customers
- To find out how does the bank measure customer Life Time Value
- To verify the relationship between the customers and the Lloyds Banking Group
1.5 SCOPE OF THE STUDY
The scope of the study and research work has limited to Lloyds Banking Group only. This chosen level of aspects has stayed at large in the study so that it can be studied well and analyzed thoroughly to get a deeper understanding. Trying to cover too much ground may lead to a very superficial and confused analysis and may involve long time duration to complete the project work or report. Therefore a specified and narrow down approach with Lloyds Banking Group and an evaluation of its success has comprised with the researc
2.0 LITERATURE REVIEW
This chapter contains a review of literature relevant to the research. This literature review deals with, about CRM, the history and goals of an integrated banking CRM, the technological factor of CRM, the process cycle in banks, data warehouse technology, data mining process, how to analysis the data, customer segmentation process, communication strategies of bank to the customers etc.
2.1 CUSTOMER RELATIONSIP MANAGEMENT
Existing research states that ‘relationships are the base to the successful development and edition of new business viewpoint, though business have taken care of relationships with their customers for many centuries’ (Gronroos, 1994). Sheth and Parvathiyar, (1995) said that relationships demand much more than mere transactions. Rather, they symbolize strategic and tactical issues based on a new philosophical move that geared in the direction of long-term organisation survival.
According to Storbacka, (1994) relationship marketing got popular in 1990s but it has a long history under different names. In its starting, one-to-one marketing appeared in the mid 1990s, which transformed into Customer Relationship Management.
Parvatiyar and Sheth gave a static definition of CRM. “Customer Relationship Management is a comprehensive strategy and process of acquiring, retaining and partnering with selective customers to create superior value for the company and the customer” (Parvatiyar and Sheth 2000, p.6)
“What criteria determine who “How can we acquire this customer will be our most profitable in the most efficient and effective customers?” way?”
“How can we increase the “How can we keep this customer loyalty and the profitability for as long as possible?”
Of this customer?”
2.2 THE HISTORY AND GOALS OF AN INTEGRATED BANKING CRM
According to Puccinelli (1999) the financial services industry as entering a new era where personal attention is decreasing because the institutions are using technology to replace human contact in many application areas.
Sherif, 2002 advocated that, now global changes brought new trends, directions and new ways of doing business, which also brought new challenges and opportunities to financial institutions. In order to complete with newly increasing competitive pressures, financial institutions must recognize the need of balancing their performance by achieving their strategic goals and meeting continues volatile customer needs requirements. Different ways must be analyzed to meet customer needs.
Foss said that banks are highly focusing on CRM for the last five years that is expected to continue.
According to Peter (1998) and Chablo (1999) the main goals of an effective integrated CRM solution in the banking sector are to enable financial institutes to;
a) Widen customer relationship through acquiring new customers, identifying and targeting new segments and expanding in new markets.
b) Lengthen the existing relationship developing longer term relationships, increasing perceived value of products and introducing new products and
c) Deepen the relationship with customers initiating the cross selling and up selling opportunities, understanding the propensity of different customer segments to purchase and increase sales.
The implementation if CRM system in a bank helps the business organisation to obtain a complete picture of their existing customers, design both customer-oriented and market-driven financial products and services, as well as implement extensive and reliable financial marketing research and efficient campaigns, to achieve and enhance customer loyalty and profitability.
The above goals can be achieved through the seamless integration of information technology solutions and business objectives at every process of the bank business that affects the customer.
2.3 THE PHASES OF CRM
The main phases of CRM are as follows;
1. Customer selection or Segmentation
According to Dave Chaffey (2009), customer selection defining the types of customers that a company will market to. It means identifying different groups of customers for which to develop offerings and to target during acquisition, retention and extension. Different ways of segmenting customers by value and by their detailed lifecycle with the customer are reviewed.
Many companies are now only proactively marketing to favoured customers. Seth Godin (1999), says “Focus on share of customer, not market share fire 70 per cent customers and watch your profits go up!”
According to Efraim Turban (2008), the most sophisticated segmentation and targeting schemes for extension of customers are often used by banks, which have full customer information and acquire history data as they search for to boost Customer Lifetime Value (CLV) through encouraging increased use of products overtime. The segmentation approach used by banks is based on five main basics which in result are covered on top of each other. The amount of options used, and therefore the complexity of approach, will depend on resources obtainable, opportunities, capabilities and technology afforded by catalog.
i. Identify customer lifecycle groups
When guests use online services then they basically pass those seven or more stages. The organisations have clear these segments and establish the CRM infrastructure to categories customers in this manner; then they deliver focused messages, whichever by modified web messaging or by e-mails that are triggered routinely because of various rules. First-time guests recognized by a cookie placed on their PC. When guests registered, they are tracked through the residual stages. The customers who have purchased one or more products are one particular important group. The key challenge is for a company to encourage a customer to shift from the first product to the second and then go on. Explicit offers can be try to push customer for further products. In the same way, when customers turn into an inactive then the customer required follow-up.
ii. Identify customer profit characteristics
This is a conventional segmentation which is based on the nature of customer. For Business 2 Business Companies it includes sex, age and geography. It includes volume of the organisation and the type of sector or application, the organisation operates in.
iii. Identify behaviour in response and purchase
As shown in 2.2 through analysis of data base when customer progress through the lifecycle, company is capable to build up a detail reaction and buy history which judges the details of frequency, recency, group of product buy and monetary value. This approach is known as ‘RFM (Recency, Frequency, Monetary value) analysis.
iv. Identify multi-channel behaviour
In spite of of the eagerness of the company for online channels, various customers are chosen for using online channels and others customers are chosen conventional channels. This is, to an extent, be indicated by RFM and response examination since customers with a preference for an online channel is more reactive and make more use online. Customer who likes online channels is focused mostly by online communications such as e-mail, but when customer like conventional channels is focused by conventional communications such as direct mail or phone. This is known as ‘right-channelling’.
v. Tone and style preference
In a same way to channel liking, customers are respond in their own way to various types of message. Some customers like rational application, in that time a detailed e-mail may work best. On the other hand some customers are preferred an emotional appeal. Companies are test for this in customers or conclude it using profit description and response performance and then expand various inventive treatments consequently.
2. Customer acquisition
Processes used to add new customer. According to Turban (2008), customer acquisition refers to marketing activities intended to form relationship with new customers while reducing acquisition cost and targeting high-value customers. Service value and selecting the right path for various customers are essential at this stage and during the lifecycle.
The conventional manner to customer acquisition include a marketing manager developing a blend of mass marketing (billboards, magazine advertisements etc.) and direct marketing (mail, telephone, etc.) campaigns based on their knowledge of the particular customer base that was being focussed. Marketing campaign trying to pressure new customers to buy a particular type of diapers, the mass marketing ads might be determined in parenting magazines. The advertisements could also be positioned in more conventional publications whose readership demographics were alike to those of new parents.
Customer acquisition is comparatively similar to mass marketing. A marketing manager selects the demographics that they are involved in and after that works with a data vendor to obtain lists of buyers who meet those features. The data vendors have large database holding millions of eventual customers that can be segment based on explicit demographic criteria.
The idea of “similar demographics” has conventionally been an art rather than a science. Usually there are not hard-and-fast systems about whether two groups of buyers share the similar features. Most of the segmentation that took place in conventional direct marketing involves hunches on the division of the marketing professional.
3. Customer retention
Dafe Chaffey 2009 said that customer retention refers to the marketing actions taken by a company to keep its current customers. Identifying applicable offerings based on their personal needs and complete position in the customer lifecycle (e.g. purchase value or number) is key.
Customer retention strategy aims to keep a high percentage of valuable customers and a customer development strategy aims to boost the value of those retained customer to the organisation. Customer retention is based on customer loyalty. And customer loyalty is the point to which a customer will continue with a specific brand or vendor.
Customer acquisition to retain and extend create long-term customer relationship. We need to calculate customer satisfaction, as satisfaction drives loyalty and loyalty drives profitability. This relationship is exposed below;
The marketers aim is to push customers up the curve towards the affection zone. But the majority are not in that zone. Marketers must understand to achieve retention,why customers defers or are indifferent.
4. Customer extension
This technique is encouraging customers to increase their involvement with a company. According to Turban 2008, customer extension is increasing the range of products that a customer buys from an organisation. Sometime it is referred ‘customer development’.
Increasing the lifetime value (CLV) of a customer is the main objective of customer extension by encouraging cross-sell. For example a customer of Egg credit card may be offered the loan or a deposit account.
There are many of customer extension technique for CRM as follows;
- Re-sell: same type of products to existing customers-particular vital in some Business 2 Business background as re-buys or modified re-buys.
- Cross-sell: sell extra products which may be closely related to the original buy.
- Up-sell: this is mean, selling more expensive products.
- Reactivation: Customers who have purchased for some time or have lapsed can be encouraged to buy again.
- Referrals: generating sells from recommendation from existing customers.
2.4 CUSTOMER LIFETIME VALUE MODELLING
Customer Lifetime Value (CLV) is also an important theory and practise of CRM. But the calculation of CLV is not straightforward. There are so many company, they do not calculate it. According to Dave Chaffey (2009) “Lifetime value is the total net benefits that a customer or group of customers will provide a company over their total relationship with the company”. CLV is based on estimating the income and costs related with each customer over a phase of time and then calculating the net present value in present monetary terms using a discount rate value applied over the stage.
Efraim Turban (2006) said there is various scale of complexity in calculating LTC. Those are exposed in 2.6. Option 1 is a realistic way or estimated proxy for future LTV, but the true LTV is the future value of the customer at individual level. CLV modelling at a segment level 4 is crucial within marketing since it answers the question;
How much can I afford to invest in acquiring a new customer?
- Lifetime value analysis helps marketers to:
- Create the true value of a company’s customer base
- Recognize and compare crucial target segment
- Calculate the effectiveness of another customer retention strategy
- Plan and calculate investment in customer acquisition programmes
- Make decisions about product and offers
2.7 gives an example of how LTV can be used to develop a CRM strategy for different customer groups. There are 4 (four) main types of customers are indicated by their present and future value as bronze, silver, gold and platinum. Separate customers’ groupings (circles) are recognized according to their current value (as indicated by current profitability) and future value as indicated by CLV calculation.
Every group will have a customer segmentation based on their demographics. Therefore this is used for customer selection. Within the four main value groupings, there are various strategies are developed for various customer groups. Few bronze customers such as group A and B practically do not have development potential and are usually unprofitable, therefore the objective is to reduce costs in communications and if they do not stay as customers this is acceptable. Some bronze customers like group C may have potential for growth; therefore for group C the strategy is to extend their purchases. Silver customers are focused with customer extension offer and gold customers are extended. Platinum customers are the best customers; therefore the communication is very important with these customers.
2.5 THE TECHNOLOGICAL FACTORS OF CRM
According to Davenport and Short, (1990); Porter, (1987) ‘information technology is an enabler to thoroughly redesign business process to achieve improvements in organisational performance’. ‘Information Technology help helps a business process by facilitating changes to job practices and establishing new techniques to link a customer with organisations, suppliers and stakeholders ‘ (Hammer and Champy, 1993).
Eckerson and Watson (2000) advocated that ‘CRM take full advantage of technology to collect and analyze data on customer patters, expand predictive models, interpret customer behaviour, proper respond with communications, and deliver product and service to individual customers. By using technology a company can create a 360 degree view of customers to find out from past interactions to optimize future ones.’
Peppard (2000) said that ‘the leading factors in CRM development is improvement in network infrastructure, client/server computing, and business intelligence applications. CRM collect, store, maintain and distribute customer knowledge all over the organisation. The effectual management of information has a vital role to play in CRM. In the case of calculating customer lifetime value, consolidated view, product tailoring and service innovation, the information is essential.’ Along with data warehouses, enterprise resource planning (ERP) system and the internet are the central infrastructures to CRM applications.
Fickel (1999) said ‘CRM applications link front office (e.g. marketing, sales and customer service) and back office (e.g. financial, logistics, operations and human resources) functions with the company’s customer touch point’.
A company’s touch point is “all of the communication, human and physical interactions your customers experience during their relationship lifecycle with your organisation. Whether an ad, Web site, sales person, store or office, touch points are important because customers from perceptions of your organisation and brand based on their cumulative experiences”
(Source; http://www.imediaconnection.com/content/4508.imc at 16/10/2009 on 15:25)
According to Eckerson and Watson (2000), ‘CRM integrated touch points is something like a common view of the customer. A separate information systems controlled these touch points. 2.8 demonstrates the relationship between customer touch point with back and front office operations’
Peppers and Rogres, (1999) said ‘In many companies, CRM is just a technology solution that extends divide databases and sales force automation tools to link sales and marketing functions in order to develop targeting efforts. On the other hand some organisations consider CRM as a tool that is exclusively designed for one-to-one relationship.’ According to Goldenberg (2000) ‘CRM is not just a technology applications for sales, marketing and service, but when CRM fully and successfully implemented, customer-driven, a cross-functional, technology-integrated business process management strategy that improves relationships and encompasses the whole organisation’.
2.6 DATA WAREHOUSE TECHNOLOGY
According to Watson (2000) ‘data warehouse is a tools of information technology management that helps business decision makers to instant access of information of customer data throughout the organisation by combining all database and operational systems like sales and transaction, human resource, inventory, purchasing, financial and marketing system. Data warehouse pull out, clean, convert and manage large volumes of data from various systems and creating a historical record of all customer’.
Data warehousing technology is the most crucial part of CRM because it makes CRM possible. Shepard et al. (1998) said ‘a better understanding of customer behaviour is possible because data warehousing technology consolidates correlates and convert customer data into customer intelligence. Understanding of customers and their purchase patterns can improve information related to customer service interactions, billing and account status, back orders, product returns, product shipment, and internal operating cost. The capacity of a data warehouse to store hundreds and thousands of gigabytes of data make an analysis feasible as well as immediate.
Organisational benefits with a data warehouse are as follows;
- exact and faster access of information
- bad and duplicate data eliminate by quality data and filtering
- customer profiling and retention modelling
- it calculate total present value and estimate future value of every customer
- it gives detail report
2.7 DATA MINING TECHNOLOGY
Peppers and Rogres, (1999) said that ‘the first analytical step of data mining is to describe the data. Data mining summarize its statistical attributes like standard deviations and means, visually review it by use of charts and graphs and distributes the value of the field in our data. But alone data description can not provide an action plan. We have to build a predictive model based on patterns determined from known results and after that we have to test the model on result outside the original sample. An ideal model should never be confused with reality, but it is useful guide to understanding our businesses’.
According to Eckerson and Watson (2000) ‘we can use data mining for both classification and regression problems. In first problem we can predict what type something will fall into. In second problems we are predicting a number like probability that a person will respond to an offer. In CRM process, data mining is often used to allocate a score to a particular customer. Data mining is also often using to recognize a set of characteristics, which is called profile. Data mining segments customers in to groups with similar behaviour like purchasing a particular product.’
2.8 THE CRM PROCESS CYCLE IN BANKS
Pound (2000) said that exploration and alteration process should be done by the banks on basis of customer information captured; this shows the full value of CRM initiatives. Banks set up a closed CRM cycle with the help of an integrated CRM solution, which composed of a set of continuous iterative process. It manages the whole customer related process for bank, analysing customer profile, customer data and life time value, which is helping to making marketing decision and optimizing the execution of marketing campaigns, customer service strategies and sales strategies across various channels during the bank.
According to Professor Constantin Zopounidis (2002) CRM process cycle is based on a generic business view. It presents a continuous improvement of value between customers and banks across touch points. The main stages are as follows;
Customer data collection
Customer data analysis
Marketing strategy and action programs
Back-office Data External Data Touch-Point Data
Pound 2000 said that ‘recent banking data sources are extremely heterogeneous. Geographic information is dispersed due to continual acquisitions, mergers and reorganizations. For example a bank might use web site, ATMs, e-mail, sales, call centres and marketing automation applications that must be integrated in a unified environment of CRM banking. An effective multi-channels customer interface will not be possible without a centrally integrated warehouse driving the entire CRM process cycle. This should be update real time. The historical data should be recorded by it, which is used to create propensity models and customer life time value models to recognize past behaviour and action in order to take future marketing strategy’.
2.9 CUSTOMER DATA COLLECTION
Kristin Anderson & Carol Kerr (2002), said that in banking transaction system data such as (e.g. Checking, Credit, Savings) are frequently organised around accounts, channels, products and other alike transactional concepts. This limits the bank ability on identifying the total relationship and unique customers. An Integrated CRM is a major goal it consolidates these “information islands” and separate solution, which forms an open cross-bank system from all executives, business area department officers and branch employees, shares the identical customer information. Integrated banking CRM structure can be obtained from this necessary basis of data supply.
Operation (contact) sources: Chou, Chou 2000, said the customer communication touch-point (ATM, Branch, Call-Centre, Internet-Banking, Mobile banking, personal contact, etc.)
Internal sources: Professor Constantion Zopounidis (2000) said internal sources that are the available information island, data bases and product oriented systems from other banks such as (Cards, Deposits, Investments, and loans etc.), Marketing campaign response, meta-data analysis and reliable data mining results.
External Sources: Professor Constanin Zopounidis 2002, said marketing researches that of external sources, infomediaries etc. Providing geo-demographic, psycho-graphic data and lifestyle, these can help to improve customer images
2.11 CUSTOMER DATA ANALYSIS
Heygate (1998), said Simple and sophisticated data analysis techniques are required for deriving the valuable customer insight from the data collected in a central customer warehouse. More advance data analytics includes OLAP (Online Analytical Processing) mining techniques and tools, these extracts applicable patterns or trends in the data.
According to Lawer (2000), key incorporated customer management insights provided by customer data analysis are customer segmentation/differentiation, concentration and distribution of customer’s value; share of purchases/profits, analysis of strategies that widen/lengthen/deepen customer relationship.
Hawkes 2000, advocated customer data analysis enables the recognition of customer’s profit and customers preferences for definite bank product and services, indicates the most suitable channels to reach the customers, and assesses the profitability and life time value of every personality.
Additionally, Delto 1998 said that the future manners of the consumers can be predicted by analysing their past behaviour. Customer statistics, profit and segmentation are the main amount produced of the analysis stage feeding the marketing strategy planning and completing process. Having easily accessible information to marketing makes the difference between a winning campaign and a failure.
2.12 MARKETING STRATEGY AND PROGRAMES
Kristin Anderson and Carol Kerr 2002 advocated captured results and data of customer analysis support marketers to route marketing messages, processes and strategies. True values of data of Lloyd TSB are discovered by tools and process for marketing decision making, marketing decision making and CRM initiatives and campaign are deployed from converted information to customer knowledge.
Goal of marketing automation within CRM are which personalise and optimizes each customer contact from planning, execution, monitoring marketing strategies and action programmes.
Bryan Foss 2003 said it is critical for bank CRM not only to extract their data source to uncover patterns and insight but also to operationalise the system through the bank performance to turn the customer knowledge into importance creating achievement.
Merlin Stone 2003 advocated the grades from advertising and CRM activities and strategies continue the process knowledge acquisition enhancing the on-going assessment of marketing data intelligence, closing the feed-back loop. Hence, the final element of CRM process cycle is the valuation of the results of campaign driven by marketing data intelligence. It is crucial to measure performance and feed result back into the centre customer data warehouse, in order to convey
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