and addresses such issues as sales, technical support and marketing. As a dynamic tool it allows a business to share any information collected from interactions with customers. By way of example, as a company you might want customer feedback that is gathered from a technical support session, which could inform your marketing staff about services of interest to customers. Overall, the primary purpose of Collaborative CRM is to improve the quality of customer service and to increase customer satisfaction. Aspects of Collaborative CRM Collaborative CRM can be broadly identified by two aspects: Interaction Management- This management process deals with designing the communication or interaction channel process within an organization which is specific to customer interaction and finally enhancing the extent of communication between both the parties. The communication channel depends on the customers’ preference on how they require the interaction to be dealt with. Some customers prefer to be contacted via phone and email because of more comfort ability or non- availability of manual interaction due to no time or unavailability of resources. Some of them prefer to have live online meeting or web meeting to reduce the travel time and lack of time or maybe they prefer more clarified real time environment by sitting at desk and transact. Some of the customers insist for agent conducted services which is often face-to-face interaction as they believe that this way is more efficient and conclusive. Depending on these channels of interaction it is very important for organization to fulfil these needs of customers and gather information from them and implementing it into the CRM before interacting to enhance the interaction power. Channel Management- After analysing and implementing the interaction medium it’s important to enhance the power of channels through which the customers are interacted. By using latest technological aspects for improving channel interaction could help to contact customers in an efficient way and gather information from them to help organization to understand the customers. Hence it is important for an organization to clearly arrange the channel responsibilities and duties. Collaborative CRM and its importance to build a collaborative strategy Collaborative Strategy is a method where a company gives a common platform to build synergy among all stakeholders for business process improvement, product innovation and pricing, customer or employee retention. Steps to build a successful collaborative strategy: Understand the business goal: An enterprise may have different collaborative strategy for different business needs. For example: Strategy for business process improvement may differ from employee retention strategy. So business must define their goal that they want to achieve using collaborative strategy. 51 CU IDOL SELF LEARNING MATERIAL (SLM)
Identify stakeholders: It is another important task for an enterprise to determine who can access business information. Data visibility rules must be set to protect data from being stolen or leaked. Choose technology based on business needs: There are lots of fancy applications available in the market but all of them may not have same capabilities to meet your requirements. Beside business requirement, you must consider other factors also like software cost and scalability, development duration, maintenance effort. This is the place where collaborative CRM comes into Collaborative Strategy. Measure the effectiveness of the strategy: Business must have some KPIs which will tell how effective the strategy was, can you continue with the same strategy, or it needs any modification. Advantages of Collaborative CRM Collaborative CRM enables valued customer interaction across the channels. Entangles web or online collaboration to cut down service cost of customers. Collaborative CRM integrates customer interaction with call centers to enable multi- channel interaction with customers and helps them make understand the overall process vales. Collaborative CRM describes a view of integrated customer’s details during interaction to server them in a better way. This CRM solution brings customers, process and strategies and data together so that organizations could serve and retain customers more efficiently. Features and Benefits of Collaborative CRM The Collaborative CRM type has the following features and benefits: Interaction management: The more you know your clients, the better you can service them, and a collaborative CRM allows you to do just that. It goes without saying that not all teams work directly with clients. It is simpler to serve customers when they have a consolidated access point to their data and interaction history. Customers will interact with your organisation or contact you through a variety of ways. As a result, it's critical to maintain track of their favourite communication channel. Collaborative CRMs keep track of how your customers contact you and allow you to respond to them using the same channels. 52 CU IDOL SELF LEARNING MATERIAL (SLM)
Document management: Collaborative CRMs also offer document management systems, so you won't have to worry if any members of your team need access to formal papers such as contracts, technical documents, proposals, and so on. Collaborative CRM is the way to go: 1. To improve departmental communication. 2. To increase client retention and loyalty by disclosing consumer information to third parties 3. must be aware of the needs and preferences of customers 4. To foster a customer-focused culture 3.4SUMMARY Analytical CRM, sometimes known as Analytic CRM is the process through which organisations transform customer-related data into actionable insight for either strategic or tactical purposes. Most of the data maintained in corporate databases are structured database. Unstructured data take the form of textual or no-textual files. External data can be used to enhance the internal data and can be imported from a number of sources including market research companies and marketing database companies. Modelled data are generated by third parties from data that they assemble from a variety of sources. Collaborative CRM, a highly effective method of communication as it covers direct interaction with customers including feedback and issue reporting. 3.5KEYWORDS Hierarchical Model as an organisation chart or family tree, in which a child can have only one parent, but a parent can have many children. Network Database: The network database allows children to have one parent, more than one parent, or no parent. Relational database: are the standard architecture for CRM applications that use structured data. Relational databases store data in two dimensional tables, comprised of rows and columns, like a spreadsheet. Compiled list data are individual level data assembled by list bureaux or list vendors. Census data are obtained from government census records. 53 CU IDOL SELF LEARNING MATERIAL (SLM)
Modelled data are generated by third parties from data that they assemble from a variety of sources. RDBMS is a software programme that allows users to create, update and administer a relational database. De-duping: Customers become aware that their details appear more than once on a database when they receive identical communications from a company. Merge and purge also known as merge-purge, this is a process that is performed when two or more databases are merged. Interaction Management- This management process deals with designing the communication or interaction channel process within an organization which is specific to customer interaction and finally enhancing the extent of communication between both the parties. Channel Management- After analysing and implementing the interaction medium it’s important to enhance the power of channels through which the customers are interacted. 3.6LEARNING ACTIVITY 1. What is Customer-related database? _________________________________________________________________________ ___________________________________________________________________________ 2. State the three types of Structured Customer-related data? ___________________________________________________________________________ ___________________________________________________________________________ 3. What is RDBMS? ___________________________________________________________________________ ___________________________________________________________________________ 3.7UNIT END QUESTIONS A. Descriptive Questions Short Questions 1. What is Analytical CRM? 2. What do you mean byHierarchical Databases? 3. What is meant by Network Database? 54 CU IDOL SELF LEARNING MATERIAL (SLM)
4. Write short note on Structured and Unstructured Data? 5. What are the features of Collaborative CRM? Long Questions 1. Explain Corporate Customer-related Data. 2. How will you develop a customer related database? 3. Explain the different aspects of Collaborative CRM? 4. State the features and benefits of Collaborative CRM? 5. Explain the desirable data attributes? B. Multiple Choice Questions 1. Programs designed for customers which is limited to any affinity group are classifieds a. Club MembershipPrograms b. RoyaltyPrograms c. LoyaltyPrograms d. Group MembershipPrograms 2. First step in analysis of customer value isto a. Identify Customers ValueAttributes b. Assessing AttributesImportance c. Assessing Company'sPerformance d. Assessing CompetitorsPerformance 3. Difference between customer’s evaluation including all costs incurred and benefits is called a. Customer PerceivedValue b. Company MarketValue c. CustomerAffordability d. CustomerReliability 4. Process of building, organizing and using databases of customers to build customerrelationship is classifiedas a. DatabaseMarketing b. CustomerDatabase c. Detailed Database d. CompanyDatabase 55 CU IDOL SELF LEARNING MATERIAL (SLM)
5. Perceived monetary value of all benefits which customers expect from a given product because of brand image iscalled a. Total CustomerBenefit b. Total CustomerCost c. Total EconomicCost d. Total FunctionalCost Answers 1 -a, 2 –a, 3-a, 4–a, 5-a 3.8REFERENCES References Books Sheth, J.N., Atul, P. and Shainesh, G. 2117. Customer Relationship Management: Emerging Concepts, Tools and Applications, 1st Edition, McGraw Hill Education. ISBN: 978-0070435049. Customer Relationship Management (CRM) by Dr K Govinda Bhat Mukerjee K, Customer Relationship Management: A Strategic Approach to Marketing Text Books References Francis Buttle and Stan Maklan, Customer Relationship Management: Concepts and Technologies, Third Edition, Special Indian Edition, 2015 Gupta, S. and Lehmann, D. 2105. Managing Customers as Investments: The Strategic Value of Customers in the Long Run, Prentice Hall. ISBN: 978-0131428959. Rai, A.K. 2112. Customer Relationship Management: Concepts and Cases, Prentice Hall India. ISBN: 978-8121346956. Gamble P Stone M and Woodcock N 1999, Customer Relationship Marketing up close and personal. London: Kogan Page: Jain S C 2005. CRM Shifts the paradigm, Journal of Strategic Marketing, 13 December, 275-91: Evans, M. O’Malley, L and Patterson M 2004, Exploring direct and Customer Relationship Marketing, London: Thomson Websites https://www.slideshare.net/jaiserabbas/customer-relationship-management-crm- 10974369?next_slideshow=1 56 CU IDOL SELF LEARNING MATERIAL (SLM)
https://www.marketing91.com/3-types-of-customer-relationship-management/ https://www.slideshare.net/itsvineeth209/chapter-3-strategic-crm https://www.sendinblue.com/blog/steps-to-creating-a-crm-strategy/ https://www.vtiger.com/operational-crm/ 57 CU IDOL SELF LEARNING MATERIAL (SLM)
UNIT 4- INTRODUCTION TO CUSTOMER RELATIONSHIP MANAGEMENT (CRM) STRUCTURE 4.0 Learning Objective 4.1 Introduction 4.2 Models of CRM 4.3 Customer Satisfaction, Loyalty and Business performance 4.4Summary 4.5Keywords 4.6Learning Activity 4.7Unit End Questions 4.8References 4.0 LEARNING OBJECTIVES After studying this unit, you will be able to: Describe models of CRM Identify strategies for CustomerSatisfaction Understand the customer loyalty Understand the Business Performance Process of customer satisfaction model 4.1INTRODUCTION In recent years, the marketing communication environment has seen conventional advertising media fragmentation and the development of new non-traditional media. As a result, contemporary marketing has had to employ a range of communication channels in order to reach the target audience. Researchers have always looked at the efficacy of these numerous communication options or media types in isolation. On the other hand, this strategy has failed to see the potential for interactions and synergy among the many communication options. The changing media landscape demands a rethinking of media strategy, with media synergy viewed as a key component moving ahead. Future marketers will have to figure out how to decipher all interactions within and amongst all media kinds as they are consumed by the client. The new approach to media planning 58 CU IDOL SELF LEARNING MATERIAL (SLM)
should start with the consumer, with horizontal rather than vertical media planning based on an understanding of how different media forms interact with the audience as they are consumed. 4.2 MODELS OF CRM Managing customers profitably is the core objective of company. How to manage customers? This is the question that ask very frequently. For this question many researchers and managers try to dig out the solution. There are number of CRM models are developed learn how to manage customers. CRM models are helpful to understand the concept of CRM and regulate the modern concept of CRM. We are discussing here: 1. IDIC Model 2. QCI Model 3. CRM Value Chain Model IDIC MODEL The IDIC model was developed by Peppers and Rogers. This model suggests that companies should take four actions in order to building, keeping and retaining the long term one-to-one relationships with customers. 1. Identify 2. Differentiate (value, need) 3. Interaction 4. Customize Identify First, a firm must determine who is the actual client and should have a thorough understanding of their needs. It is not only important to know about your consumers, but it is also necessary to learn more about them in order to better understand them and serve them profitably. Differentiate Make a distinction between your customers based on two factors: need and worth Differentiate your customers to see which ones are creating the most value today and which ones have the most potential in the future. More value should be given to consumers who generate more value for you. Differentiate your consumers based on their requirements. Different clients have different requirements and providing them in a professional manner is essential. 59 CU IDOL SELF LEARNING MATERIAL (SLM)
Figure 4.1 – CRM models Interaction The company should place a strong focus on customer engagement to ensure that it fully comprehends the consumer's expectations and connection with the brand. Customers' requirements and the value they provide must be considered in the company's interactions with them. Direct interaction with consumers gives the impression that the firm cares about them and wants to serve them individually. Customers become loyal as a result of these efforts, and the firm develops long-term connections. Customize After you've differentiated your consumers based on their beliefs and requirements, you'll need to tailor your product to meet their wants and values. Personalize the offer and messaging to guarantee that clients' expectations are satisfied. Customers can learn about your capacity to meet their needs by interacting with you. Failure of the third step indicates a problem with the second or third steps. So go back to the prior steps or return to the previous stages. Re-examine them, look for new information, and reorganise these processes. 1) QCI MODEL: The QCI model is also a consultancy firm's offering. The authors of the concept prefer to refer to it as a customer management model rather than a relationship management model. They represent a set of actions that firms must undertake in order to gain and keep consumers at the core of the model. The concept depicts humans carrying out procedures and utilising technology to aid them. 60 CU IDOL SELF LEARNING MATERIAL (SLM)
The quality competitiveness index model (QCI) is another name for the QCI model. This model encompasses a variety of operations including workers, people, and organisations, as well as technology. Relationships with the external world, according to this paradigm. Because the external environment has a direct impact on the customer experience when they wish to start the selling process or connect with the business. The external environment has an impact on how companies plan. Figure 4.2 Customer experience Now as you can see in the figure that customer experience affects three activities future: customer proposition, customer management activity and measurement. 61 CU IDOL SELF LEARNING MATERIAL (SLM)
Customer proposition means something that a company offers to customer against the price. Customer management activity is a process of capturing customers, start with targeting, conversation, selling and end with retaining or winning back the customers. Customer management activity affects customer’s experience that how a company acquires, retains a customer and also penetrates. Finally, measurement process also affects the customer experience. People and organization have relation with planning process, customer proposition, customer management activity and measurement. Because CRM start with people and end with people. Infrastructure deals with organization in a sense of technology, customer information and process management. One big thing is that each activity, people, organization, process and technology has dual effect and inter correlated with each other. 3) CRM VALUE CHAIN MODEL CRM is a three-letter acronym with an emotive connotation. For some, CRM is just a link between marketing and IT: CRM is a sales and service activity that is supported by technology. Others see it as nothing more than carefully focused one-to-one communication. Simply said, CRM is a tool that uses people, information technology, customer data, corporate processes, and customers to manage customer relationships. When it comes to designing and executing CRM strategies, the CRM value chain is a well- established paradigm that organisations can simply follow. It has been under development for five years and has been tested in a variety T, software, telecommunications, financial services, retail, media, manufacturing, and construction: business-to-business and business-to-consumer contexts, with both major firms and SMEs: IT, software, telecoms, financial services, retail, media, manufacturing, and construction. The model is built on sound theoretical concepts as well as commercial requirements. The CRM value chain process' ultimate goal is to guarantee that the firm develops long-term, mutually beneficial connections with its strategically important customers. Customers aren't all strategically important. Some clients are simply too costly to acquire and maintain. They buy rarely and in little amounts; they pay late or default; and they place high demands on customer service and sales representative. They want costly, short-run, customised output, and then defect to competitors. Customers who are strategically unimportant are referred as such 62 CU IDOL SELF LEARNING MATERIAL (SLM)
Figure 4.3 Profitability Analysis Five primary steps to profitable relationships The five steps in the CRM value chain are customer portfolio analysis, customer intimacy, network development, value proposition development and managing the relationship. 1. Customer Portfolio Analysis The first phase in the CRM value chain, CPA, recognises that not all customers are equal in terms of importance to the firm. Who are our SSCs (strategically significant clients), according to CPA? SSCs have been adequately defined above, so let's move on to CPA. CPA informs us how valuable our clients are to us. A client portfolio is the collection of groups that make up a company's customer base. Restaurants, grocery shops, amusement parks, and sports arenas, for example, are among Coca-customers. Cola's it means that before beginning the CRM process, a company should have a full understanding of its customers. 2. Customer Intimacy Knowing about your client is one thing but selecting them to serve with your product is another. The majority of businesses gather information on their customers. Scanner data, loyalty card data, complaints files, market research, and geo demographic data are all examples of sectors that are overburdened with data. The challenge now is how you will use this information to provide the best possible service to your consumers. Long-term partnerships need a greater understanding of your consumers. For a firm to manage long-term relationships with devoted and strategically irrelevant consumers, it is critical to understand what, who, why, when, and how customers behave. 3. Develop the Network 63 CU IDOL SELF LEARNING MATERIAL (SLM)
The network position of a firm, or its connectivity to other parties that collaborate to give value to the selected client, is a significant source of competitive advantage. It is critical for a firm to offer value for customers at every level of the selling process in order to serve client relationships. It indicates that in order to service consumers financially, the firm must build a comprehensive network. Suppliers, manufacturers, employees, investors, technology, distributors, and retailers are all part of a successful network. CRM is not a fast cure; it necessitates owners and investors willing to make long-term investments in people, processes, and technology in order to implement CRM initiatives. 4. Value Proposition Development You'll know who you want to serve by the fourth stage of the CRM value chain, and you'll have created, or be in the process of creating, your network. Now it's up to the network to collaborate in order to produce and provide the desired value(s) to the desired consumers. The value proposition will be created by the network that the firm develops now. Every member of a well-developed network contributes to the creation of value for customers. 5. Relationship Management The major phases come to a close with this step. All of these stages assist the firm in establishing and maintaining a connection. Now it is up to the corporation to manage these connections in such a way that both parties, the company and the consumer, get value for their money and long term. Five supporting conditions of CRM value chain model These are five supporting conditions to fulfil the CRM value chain model. 1. Culture and leadership 2. Procurement processes 3. Human resource management processes 4. IT/Data management processes 5. Organization design These are some essential requirements that a firm must take into account while operating its CRM. The culture of your company will determine whether you can manage long-term relationships or not, as some cultures do not enable you to do so. The procurement and HR processes at your company can also help you figure out how you'll go about doing this. You can't perform CRM without an IT and data management procedure since customer information and data is saved on technology. Relationship management is aided by organisational design. 4) PAYNE AND FROW’S FIVE-PROCESS MODEL 64 CU IDOL SELF LEARNING MATERIAL (SLM)
a. Strategy development process b. Value creation process c. Multichannel integration process d. Performance assessment process e. Information management process Figure 4.4 Information Management Process 5) GARTNER COMPETENCY MODEL According to this model, organisations must have capabilities in eight areas in order to be successful with CRM. Building a CRM vision, developing CRM strategies, designing a valuable customer experience, intra- and extra-organizational collaboration, managing customer lifecycle processes, information management, technology implementation, and developing indicators of CRM success or failure are just a few of them. 65 CU IDOL SELF LEARNING MATERIAL (SLM)
Figure 4.5 GARTNER COMPETENCY MODEL 4.3CUSTOMER SATISFACTION, LOYALITY AND BUSINESS PERFORMANCE An important rationale for CRM is that it improves business performance by enhancing customer satisfaction and driving up customer loyalty, as shown in below figure. Figure 4.6the Satisfaction-Profit Chain There is a compelling logic to the model, which has been dubbed the ‘satisfaction-profit chain’. Satisfaction increases because customer insight allows companies to understand their customers better and create improved customer value propositions and better customer experiences. As customer satisfaction rises, so does customer intention to repurchase. This is in turn influence actual purchasing behaviour that has an impact on business performance. 66 CU IDOL SELF LEARNING MATERIAL (SLM)
We will examine the variables and linkages between them. Fist we will define the major variables customer satisfaction, Customer loyalty and business performance. Customer Satisfaction Customer satisfaction has been the subject of considerable research, and has been defined and measured in many ways. We define customer satisfaction as follows: Customer Satisfaction is the customer’s fulfilment response to a customer experience, or some part thereof. Customer Satisfaction is a pleasurable fulfilment response. Dissatisfaction is apleasurable fulfilment response. The experience, or some part of it component of the definition suggests that the satisfaction evaluation can be directed at any or all elements of the customer’s experience. This can include product, service, process and any other components of the customer experience. Themost common way of operationalising satisfaction is to compare the customer’s perception of an experience, or some part of it, with their expectations. This is known as the expectations-disconfirmation model of customer satisfaction. This model suggests that if customers believe their expectations have been met, they are satisfied. If their expectations are underperformed, this is negative disconfirmation, and they will be dissatisfied. Positive disconfirmation occurs when perception exceeds expectation. The customer might be pleasantly surprised or even delighted. This model assumes that customers have expectations, and that they are able to judge performance. The expectations-disconfirmation model adopts a cognitive perspective on customer satisfaction. A customer satisfaction paradox has been identified by expectations-disconfirmation researchers. At times customers’ expectations are met but the customer is still not satisfied. This happens when the customer’s expectations are low. ‘I expected the plane to be late. It was. I’m unhappy!’ Many companies research customer requirements and expectations to find out what is important for customers, and then measure customers’ perceptions of their performance compared to the performance of competitors. The expectations-disconfirmation model is not without its detractors despite its widespread use. Some experts do not accept that customers make satisfaction judgements by comparing each experience to prior expectations, rather, they form judgements over multiple episodes and across numerous channels – in other words, satisfaction judgements are associated with overall customer experience. Satisfaction, from this perspective, is an overall assessment or attitude rather than a gap. Equally, customer satisfaction judgements may have a strong emotional or affective content that is not picked up when the expectations-disconfirmation approach is used. Customers may simply like or not like their experience and may be unable or unwilling to articulate why in terms of having specific expectations being met or not. Some researchers suggest that 67 CU IDOL SELF LEARNING MATERIAL (SLM)
emotion and cognition interact, and that the interaction effects on customer satisfaction are both complex and dynamic: that is, they change over time. Affect has a strong influence on satisfaction in the early stages of judgement formation but its role declines as the customer have further experiences. Hence, we should be cautious about viewing customer satisfaction as a simple episodic assessment of performance versus expectations. Customer Loyalty Customer Loyalty has also been the subject of considerable research. There are two major approaches to defining and measuring loyalty, one based on behaviour, the other on attitude. Behavioural loyalty is measured by reference to customer purchasing behaviour. Loyalty is expressed in continued patronage and buying. There are two behavioural aspects to loyalty. First, is the customer still active? Second, have we maintained our share of customer spending? In portfolio purchasing environments, where customers buy products and services from a number of more-or-less equal suppliers, the share of customer spending question is more important. Many direct marketing companies use RFM measures of behavioural loyalty. The most loyal are those who have high scores on the three behavioural variables. Recency of purchases ®, Frequency of purchases (F) and Monetary value of purchases (M). The variables are generally measured as follows: R = Time Elapsed since last purchase F = Number of purchases in a given time period M = Monetary value of purchases in a given time period. Attitudinal loyalty is measured by reference to components of attitude such as beliefs, feelings and purchasing intention. Those customers who have a stronger preference for, involvement in or commitment to a supplier are the more loyal in attitudinal terms. These perspectives on loyalty have been combined by Dick and Basu, as shown in below Figure. 68 CU IDOL SELF LEARNING MATERIAL (SLM)
Figure 4.7 Two-dimensional model of customer loyalty. These authors identify four forms of loyalty according to relative attitudinal strength and repeat purchase behaviour. 'Loyals' are those who have high levels of repeat buying and a strong relative attitude. 'Spurious loyals' have high levels of repeat purchase but weak relative attitude. Their repeat purchasing can be explained by inertia, high switching peat purchase but costs or indifference. 'Latent loyalty' exists when a strong relative attitude is not accompanied by repeat buying. This might be evidence of weakness in the company's distribution strategy, the product or service not being available when and where customers want. From a practical point-of-view, the behavioural definition of loyalty is attractive because sales and profits derive from actions and not attitude. However, taking the trouble to understand the causes of weak or negative attitudes in customers can help companies identify barriers to purchase. It is equally true that knowledge of strong or positive attitudes can help companies understand the causes of competitor-resistant commitment. However, it is not clear from the Dick and Basu model whether attitude precedes behaviour or behaviour precedes attitude. Researchers generally accept that causation is circular rather unidirectional. In other words, attitudes influence behaviour, and behaviour influences attitude. Business Performance Business performance can be measured in many ways. The recent trend has been away from simple short-term financial measures such as quarterly profit or earnings per share. Leading companies have moved towards a more rounded set of performance indicators, such as represented by the triple bottom line\" and balanced scorecard.\" The balanced scorecard employs four sets of linked key performance indicators (KPI); financial, customer, process, and learning and growth. The implied connection between these indicators is that people (learning and growth) do things (process) for customers (customer) that have effects on business performance (financial). 69 CU IDOL SELF LEARNING MATERIAL (SLM)
Customer-related KPIs that can be used to evaluate business performance following the adoption of CRM include customer satisfaction levels, customer retention rates, customer acquisition costs, number of new customers acquired, average customer tenure, customer loyalty (behavioural or attitudinal), sales per customer, revenue growth, market share and share of customer spending (wallet). The balanced scorecard is highly adaptable to CRM contexts. Companies need to ask the following questions: What customer outcomes drive our financial performance? What process outcomes drive our customer performance? What learning and growth outcomes drive our process performance? The satisfaction-profit chain suggests that the customer outcomes of satisfaction and loyalty are important drivers of business performance. Share of customer spend (share-of-wallet or SOW) is a popular measure of CRM performance. If your company makes a strategic CRM decision to serve a particular market or customer segment, it will be keen to measure and grow its share of the chosen customers spending. As indicated in below Figure, share of customer spend focuses on winning a greater share of targeted customers' or segments' spending, rather than market share. Figure 4.8 Market Share versus share of customer 4.4 SUMMARY CRM models are helpful to understand the concept of CRM and regulate the modern concept of CRM. The CRM value chain process' ultimate goal is to guarantee that the firm develops long-term, mutually beneficial connections with its strategically important customers. Affect has a strong influence on satisfaction in the early stages of judgement formation but its role declines as the customer has further experiences. 70 CU IDOL SELF LEARNING MATERIAL (SLM)
Behavioural loyalty is measured by reference to customer purchasing behaviour. Attitudinal loyalty is measured by reference to components of attitude such as beliefs, feelings and purchasing intention. The balanced scorecard employs four sets of linked key performance indicators (KPI); financial, customer, process, and learning and growth. 4.5 KEYWORDS A Client Portfolio is the collection of groups that make up a company's customer base. Customer Satisfaction is the customer’s fulfilment response to a customer experience, or some part thereof. Expectations-Disconfirmation Model: The most common way of operationalising satisfaction is to compare the customer’s perception of an experience, or some part of it, with their expectations. This is known as the Expectations-Disconfirmation Model of customer satisfaction. 4.6LEARNING ACTIVITY 1. What is IDIC Model? ___________________________________________________________________________ ___________________________________________________________________________ 2. What is meant by the CRM Value Chain? ___________________________________________________________________________ ___________________________________________________________________________ 4.7UNIT END QUESTIONS 71 A. Descriptive Questions Short Questions 1. What is the CRM Model developed by Peppers and Rogers? 2. What is the CRM Model of Francis Buttle? 3. What is Payne’s model of CRM? 4. How to make customer loyalty? 5. What are the features of Collaborative CRM? Long Questions 1. What are the strategies to influence customers’ satisfaction? CU IDOL SELF LEARNING MATERIAL (SLM)
2. What are uses of customer loyalty? 3. Write a note on to measure customer satisfaction tools? 4. What are the models of CRM? 5. Write a note onBusiness Performance? B. Multiple Choice Questions 1. Any occasion on which brand or product is encountered by end customersis called a. Customer touchpoint b. Company touchpoint c. Retailers touchpoint d. Relationship touchpoint 2. Customer satisfaction with the purchase of a product is dependent upon what? a. The product's performance relative to the buyer's expectations b. The product's performance relative to the price c. The product's performance relative to the service d. The product's performance relative to the quality 3. A loyal customer has which kind of the relationship with the organization? a. No relationship b. Indifferent relationship c. Emotional relationship d Transactional relationship 4. In property development, customer relationship is based on which of the following factors? a. Attitudes b. Money c. Trust d. Convenience 72 CU IDOL SELF LEARNING MATERIAL (SLM)
5. This is the processing of data about customers and their relationship with the enterprise in order to improve the enterprise’s future sales and service and lower cost. a. click streamanalysis b. databasemarketing c. customer relationship management d. CRManalytics Answers 1 -a, 2 –a, 3 -c, 4 –c, 5 -d 4.8REFERENCES References Books Sheth, J.N., Atul, P. and Shainesh, G. 2117. Customer Relationship Management: Emerging Concepts, Tools and Applications, 1st Edition, McGraw Hill Education. ISBN: 978-0070435049. Customer Relationship Management (CRM) by Dr K Govinda Bhat Mukerjee K, Customer Relationship Management: A Strategic Approach to Marketing Text Books References Francis Buttle and Stan Maklan, Customer Relationship Management: Concepts and Technologies, Third Edition, Special Indian Edition, 2015 Gupta, S. and Lehmann, D. 2105. Managing Customers as Investments: The Strategic Value of Customers in the Long Run, Prentice Hall. ISBN: 978-0131428959. Rai, A.K. 2112. Customer Relationship Management: Concepts and Cases, Prentice Hall India. ISBN: 978-8121346956. Gamble P Stone M and Woodcock N 1999, Customer Relationship Marketing up close and personal. London: Kogan Page: Jain S C 2005. CRM Shifts the paradigm, Journal of Strategic Marketing, 13 December, 275-91: Evans, M. O’Malley, L and Patterson M 2004, Exploring direct and Customer Relationship Marketing, London: Thomson Websites https://www.slideshare.net/jaiserabbas/customer-relationship-management-crm- 10974369?next_slideshow=1 73 CU IDOL SELF LEARNING MATERIAL (SLM)
https://www.marketing91.com/3-types-of-customer-relationship-management/ https://www.slideshare.net/itsvineeth209/chapter-3-strategic-crm https://www.sendinblue.com/blog/steps-to-creating-a-crm-strategy/ 74 CU IDOL SELF LEARNING MATERIAL (SLM)
UNIT 5 -PLANNING AND IMPLEMENTING CRM STRATEGY STRUCTURE 5.0 Learning Objectives 5.1 Introduction 5.2 Database 5.3 Data warehouse 5.4 Customer database and data mart 5.5 Uses of Customer database 5.6Summary 5.7 Keywords 5.8Learning Activity 5.9 Unit End Questions 5.10References 5.0 LEARNING OBJECTIVES After studying this unit, you will be able to: Describe the information included in database Identify and Developing the Information Database Understand customer Information Database and Data warehousing Explain The stages of Data warehouse Describe the Data mart. 5.1INTRODUCTION The transmission or transit of information or a message from the sender through a specified route to the receiver while overcoming hurdles that slow it down is referred to as the communication process. The communication process is circular in nature, since it starts with the sender and ends with the sender in the form of feedback. It occurs at all levels of the organisation, including the top, bottom, and sides. As such, communication must be a constant and dynamic exchange in which various elements impact and are affected. The communication process is made up of several phases, each of which is necessary for efficient communication. 75 CU IDOL SELF LEARNING MATERIAL (SLM)
Data warehousing is the collection and management of data from many sources into a centralised repository in order to provide meaningful business insights. With all of your data in one location, performing analysis and reporting at various aggregate levels becomes much easier. A data warehouse's design is divided into three levels. The database server is the one at the bottom, where data is loaded and stored. The analytics engine, which analyses the data, is in the middle. The front-end client, which represents the outcome through analysis, reporting, and data mining tools, is the most important. These layers form the foundation of a data warehouse's overall operation. The data warehouse collects and organises information into a large database. After the data has been gathered, it is sorted into different tables based on the data type and structure. It's the brains behind the BI system, and it aids in making better business decisions. Simply said, it's an electronic storage area for all of your company's data, which is gathered from many marketing and other sources. 5.2 DATABASE Customer-related data can be seen from the perspective of the present, the past, or the future, concentrating on current opportunities, previous sales, or projected prospects. Individual customers, customer cohorts, customer segments, market segments, or whole markets may be the subject of customer-related data. They might also include information on products, competitors, regulations, or anything else related to the establishment and maintenance of client relationships. Companies may evaluate their consumers and predict future trends in the competitive market using data from a data warehouse. It is simpler to service consumers correctly and achieve greater levels of customer satisfaction when businesses have exact knowledge about what they want and expect from them. You can always think ahead of your rivals when it comes to historical analysis, product creation, pricing strategy, anticipating market changes, and customer happiness if you use the proper data warehousing software. Investing in a well-functioning data warehouse will he further process? Data Warehousing and Data Analytics: The terms \"data warehousing\" and \"data analytics\" are frequently interchanged. These two names may appear to be similar, but they are not the same, which encapsulates the distinction between them. The practise of combining all organisational data into a single database is known as data warehousing. 76 CU IDOL SELF LEARNING MATERIAL (SLM)
Data analytics, on the other hand, is all about evaluating raw data and drawing inferences from the results. Although the ideas are connected, they are distinct. After the data warehousing process is done, the data analytics phase begins. The prospect and customer database is, without a doubt, the most effective marketing and research tool available to help a company develop. Here's a checklist to make sure you're collecting the proper information. Contact names. It includes a primary contact (name of the individual), but one is also required to watch for any key names or titles at the business and record them. This assures you have multiple points of contact of those that might be part of the decision-making process to use your services. It also serves as a back-up should your primary contact ever leave the company. Job title and job definitions. Get the official titles of any of your contacts (double check to make sure they are correct). Also, if possible, make notes on what their job descriptions are (that is, what are they responsible for). This information can be helpful to refer to later if you need to make contact with multiple people in the company. Demographic or psychographic information. Having a sense of the age, background, likes/dislikes of your prospects or customers can be important in improving communication with them. As you have discussions with your contacts, if they express elements of their background, experience -- or if you are able to gauge some information on this buy observation, make some notes in your database. Many times, especially with prospects, it's helpful to have these notes on hand to refresh your mind of these details before making the next follow-up contact. Name of company. Be sure to get the right spelling and format of the company, so that it will appear correctly on all of your letters, faxes, etc. For example, is it \"XYZ Technology\" or XYZ Technology, Inc.?\" Pay close attention to these details, as making a mistake can make for bad presentations later in your communication to a prospect or customer. Address. It includes the information Get both the physical and the mailing address if they are different. Make note of which address they prefer you to send them anything to. Methods to contact them. This should include any alternative ways to contact the customer such as phone numbers (including cellular phones, if applicable) email addresses, website address, fax numbers, etc. As your relationship evolves with the prospect or customer, be sure to keep updating your database if you receive new ways to potentially contact them down the road. 77 CU IDOL SELF LEARNING MATERIAL (SLM)
Buying history. Make sure to make notes of the date of the first purchase, subsequent services, amount of sale, and any other transactional information. Source of lead. If the contact is a prospect, be sure to keep track of how customer initially made contact with you. What is from another customer's referral? From a direct mailing you did? Or a booth at a conference or trade show? Code this into your database for later reference. Source of sale. When the prospect makes his/her first purchase, record (if applicable) any effort that they may have responded to. Did they respond to an email or follow- sales letter you sent? Or telephone call. Tracking this information over time will help you identify what methods of follow-up are most effective in generating first-time revenue from a prospect. Special needs of customers. Capture and record any special needs that the prospect or customer indicates to you as part of your ongoing communication with them. This is important information that can be used later to expand or alter your service offerings. Customer comments. Be sure to keep track of any comments from customers, whether they be complaints, testimonials, and special requests. 5.3DATA WAREHOUSE A set of analytical tools mines databases for patterns and insights to aid managers and staff in making better decisions that increase organisational performance. Marketing the following is a list of message points in the data warehouse: A data warehouse is a repository of business data obtained directly from operational systems and external data sources. \"Data warehousing\" is defined as \"a subject-oriented, non-volatile, time-varying collection of data in support of a decision-making process.\" A data warehouse is supposed to be a place where data gets stored so that applications can access and share it easily. A data warehouse is of course a base but it contains summarized information. According to Bill Inmon, \"A collection of non-volatile data of different business subjects and objects, which is time variant and integrated down various sources and applications and stored in a manner to make a quick analysis of business situation.\" A data warehouse is a relational database that is designed for query and analysis rather than for transaction processing. It usually contains historical data derived from transaction data, but it can include data from other sources. It separates analysis workload from transaction workload and enables an organization to consolidate data from several sources. In addition to 78 CU IDOL SELF LEARNING MATERIAL (SLM)
a relational database, a data warehouse environment includes an Extraction, Transportation, Transformation, and Loading (ETL) solution, an On-Line Analytical Processing (OLAP) engine, client analysis tools, and other applications that manage the process of gathering data and delivering it to business users. A Data Warehouse (DW) is a database used for reporting. The data is uploaded from the operational systems for reporting. The data may pass through an operational data store for additional operations before it is used in the DW for reporting. A data warehouse maintains its functions in three layers: 1) Staging: It is used to store raw data for use by developers (analysis and support). 2) Integration: This layer is used to integrate data and to have a level of abstraction from users. 3) Access: This layer is for getting data out for users. This definition of the data warehouse focuses on data storage. The main source of the data is cleaned, transformed, catalogued, and made available for use by managers and other business professionals for data mining, online analytical processing, market research, and decision support. However, the means to retrieve and analyse data, to extract, transform and load data, and to manage the data dictionary are also considered essential components of a data warehousing system. Many references to data warehousing use this broader 'context. Thus, an expanded definition for data warehousing includes business intelligence tools, tools to extract, transform, and load data into the repository, and tools to manage and retrieve metadata With the passage of time, the necessity for a data warehouse has risen. Every company, regardless of size, wants a data warehouse that gives them a single view of all their data. This was the first time a data warehouse was used in a sophisticated way. The following is a list of common steps in the utilisation of a data warehouse: Offline Operational Database: In this step, data from an operating system is transferred to a server so that loading, processing, and reporting the data does not affect the operational system's performance. Offline Data Warehouse: To generate relevant business insights, the data in the warehouse is continuously updated from the operational database. Real-time Data Warehouse: The data warehouse is updated whenever a transaction occurs in the operational database. Integrated Data Warehouse: Every transaction in the operational database is updated in the data warehouse at the same time. The warehouse then creates transactions, which are sent to the operational database. 79 CU IDOL SELF LEARNING MATERIAL (SLM)
When these appliances are used in conjunction with data warehouses, they may help companies fulfil their modern-day data integration needs. The following advantages may be obtained by integrating all consumer data in a data warehouse: Indexing across accounts Customers' past data is easily accessible. Interactive voice response technology has been improved. Digital communications that are tailored Data warehouse appliances serve as the foundation for constructing effective data warehouse systems for businesses. Basic Data Warehouse: A basic data warehouse allows you to reduce the quantity of data saved in your system. This may be accomplished by eliminating duplication from the data and making it appear simple and straightforward. Because the idea incorporates data from numerous sources, different departments may access data straight from the warehouse, saving time by not having to open multiple files to get what they need. Staging Area and Data Warehouse: Before transferring the data to storage, some data warehouses undertake the cleaning procedure. There are \"staging zones\" in these systems where information is initially examined and assessed before being transmitted to the warehouse. As a business, you may utilise data warehouses with staging areas to handle massive amounts of consumer data, ensuring that unnecessary data is filtered out and your team is left with just accurate data to work with. Data Marts and Data Warehouses: You may increase the amount of customisation in your data warehouse by using data marts. After the data has been processed, data marts provide it to the teams and employees who require it the most. This will assist various departments within an organisation increase their production by eliminating the need for them to wait for information from other departments. The decision support database (Data Warehouse) is kept distinct from the operational database of the company. The data warehouse, on the other hand, is an environment rather than a product. It's an information system's architectural design that gives users access to current and historical decision-support data that's difficult to find or find in a typical operational data store. You may be aware that a database created by 3NF for an inventory system may have tables that are connected to one another. A report on current inventory information, for example, may have more than 12 linked conditions. 80 CU IDOL SELF LEARNING MATERIAL (SLM)
This can cause the query and report to take a long time to respond. A data warehouse introduces a novel architecture that can assist to improve query performance and minimise response time for reporting and analytics. The following is another name for a data warehouse system: System to Assist Decision Making (DSS) Information System for Executives Information Management System (MIS) Analytical Application for Business Intelligence Warehouse of Data A Data Warehouse is a central repository where data from one or more data sources is stored. The transactional system and other relational databases feed data into a data warehouse. The following are examples of data sources: Structured Semi-structured Data that is unstructured Users may access the processed data in the Data Warehouse using Business Intelligence tools, SQL clients, and spreadsheets after the data has been processed, converted, and ingested. A data warehouse combines data from several sources into a single, comprehensive database. A business may assess its consumers more holistically by combining all of this information in one location,EDW (Enterprise Data Warehouse) 1. EDW (Enterprise Data Warehouse) is a centralised data warehouse. It offers decision- making assistance to the entire company. It provides a uniform approach to data organisation and representation. It also has the capability of classifying data by subject and granting access based on such divisions. 2. Operational Data Store: An operational data store, also known as an ODS, is a data store that is required when neither a data warehouse nor an OLTP system can meet an organization's reporting requirements. The data warehouse in ODS is updated in real time. As a result, it is commonly used for regular tasks such as maintaining employee data. 3. Data Mart: This is a data warehouse. The data warehouse is subdivided into data marts. It is tailored to a certain business line, such as sales, finance, sales, or finance. Data may be collected directly from sources in an independent data mart. 81 CU IDOL SELF LEARNING MATERIAL (SLM)
Data Warehouse phases in general Previously, data warehousing was used in a pretty basic way by companies. With time, though, more complex data warehousing applications emerged. The following are the stages of data warehouse (DWH) utilisation in general: 1. Operational Database Offline: Data is simply transferred from an operating system to another server at this step. The performance of the operating system is not impacted by the loading, processing, and reporting of the duplicated data in this fashion. 2. Data Warehouse on the Cloud: The Operational Database feeds data into the Data warehouse on a regular basis. To fulfil the Data warehouse objectives, the data in Data warehouse is mapped and transformed. 3. Data Warehouse in Real Time: Data warehouses are updated at this step whenever a transaction occurs in the operational database. For example, a booking system for an airline or a train. 4. Data Warehouse (Integrated): When the operational system executes a transaction, Data Warehouses are continually updated at this point. After that, the Data warehouse creates transactions, which are subsequently sent back to the operational system. Figure 5.1 Data warehouse 82 CU IDOL SELF LEARNING MATERIAL (SLM)
Data Warehouse is the extension of database Data warehouse is the main repository of customer ‘s data Data in the data warehouse are processed (i.e., EFL) therefore is more integrated and consistent. While the information in the database tends to be real-time, the information in the data warehouse can be updated regularly. While database focuses on automating the process of collecting and customers information, data warehouse looks more at assisting managers in performing more advanced analysis and thus making better decisions. 5.4 CUSTOMER DATABASE AND DATA MART Databases support the four forms of CRM: 83 CU IDOL SELF LEARNING MATERIAL (SLM)
Define the Database Functions Define the information Requirements Identify the information sources Select the database technology and Hardware Platform Populate the database Maintain the Database Table 5.1 Four forms of CRM: 1. Define Database Functions: It supports the four forms of CRM i) Strategic CRM: It needs data about markets, market offerings, customers, channels, competitors, performance, and potential to be able to identify which customers to target for customer acquisition, retention and development, and what to offer them. Collaborative CRM implementations generally use the operational and analytical data, so that partners in distribution channels can align their efforts to serve end-customers. Customer-related data is necessary for both operational and analytical CRM purposes. ii) Operational CRM: it uses customer related data to help in every running of the business. iii) Analytical CRM: it uses customer related data to support the marketing,sales, and service decisions that aim to enhance the value created for and from customers. iv) Collaborative CRM: in this form of CRM customer related data are typical organized into two subsets, reflecting these operational and analytical purpose. 2. Define the information requirements: The people best placed to answer the question “what information is needed? Are those who interact or communicate with customers for sales, marketing and services purposes and those who have to make strategic CRM decisions? 84 CU IDOL SELF LEARNING MATERIAL (SLM)
With the advent of packaged CRM applications, much of the database design won has been done by the software vendors. The availability of industry-specific CRN applications, with their corresponding industry-specific data models, allows for I much closer fit with a company's data needs. Where there is a good fit-out of that box, the database design process for both operational and analytical CRN applications becomes one of implementing exceptions that have been overlooked by the generic industry model. Some CRM vendors have also built in the extract, transform and load processes to move information from OLTP to OLAP databases although it is highly likely that a client will need to modify and customize the standard processes. The various forms of information required are about: I) Customer Information Fields: Most CRM software’s have predefined fields in different modules, whether for sales, marketing or service applications. For example, in a sales application, a number of fields (columns) of information about customers are common, e.g., contact data, contact history, transactional history, current pipeline, future opportunities, products and communication preferences. ii) Contact Data: Who is the main contact (name) and who else (other names) is involved in buying decisions? What are their roles? Who is the decision- makers, buyers, influencers, initiators and gatekeepers? What are the customer's invoice addresses, delivery addresses, phone number, fax numbers, e-mail addresses, street addresses and postal addresses? Iii) Contact History: Who has communicated with the customer, when, about what, in which medium and with what outcome? IV) Transactional History: What has the customer bought and when? What has been offered to the customer, but not been purchased? v) Current Pipeline: What opportunities are currently in the sales pipeline? What is the value of each opportunity? What is the probability of closing? Is there a 10 DATA MART Companies often build enterprise-wide data warehouses, where a central data warehouse serves the entire organization, or they create smaller, decentralized warehouses called data marts. A data mart is a subset of a data warehouse in which a summarized or highly focused portion of the customer’s data is placed in a separate database for a specific population of users. For example, a company might develop marketing and sales data marts to deal with customer info. A data mart typically focuses on a single subject area or line of business, so it usually can be constructed more rapidly and at lower cost than an enterprise-wide data warehouse. 85 CU IDOL SELF LEARNING MATERIAL (SLM)
However, complexity, costs, and management problems will rise if an organization creates too many data marts. Sourcing, Acquisition, Clean-up and Transformation Tools The functionality includes: – Removing unwanted data from operational databases – Converting to common data names and definitions – Calculating summaries and derived data – Establishing defaults for missing data – Accommodating source data definition changes The data sourcing, clean-up, extract, transformation and migration tools have to deal with some significant issues, as follows: – Database heterogeneity. – Data heterogeneity – Data warehouse operational information such as data history (snapshots, versions), ownership, extract audit trail, usage data The non-trivial extraction of novel, implicit, and actionable knowledge from large datasets. – Extremely large datasets – Discovery of the non-obvious – Useful knowledge that can improve processes – Cannot be done manually Technology to enable data exploration, data analysis, and data visualization of very large databases at a high level of abstraction, without a specific hypothesis in mind. Sophisticated data search capability that uses statistical algorithms to discover patterns and correlations in data. Data Mining is a step of Knowledge Discovery in Databases (KDD) Process – Data Warehousing – Data Selection – DataPre-processing – Data Transformation – Interpretation/Evaluation Data warehousing 86 CU IDOL SELF LEARNING MATERIAL (SLM)
SQL / Ad Hoc Queries / Reporting Software Agents Online Analytical Processing (OLAP) Data Visualization Data Mining Applications 5.5 USES OF CUSTOMER DATABASE Customer-related data might also be maintained by different channel managers, e.g., company-owned retail stores, third-party retail outlets and online retail. Similarly, different product managers might maintain the own customer-related data. These life events tend to set one generation apart from the next. A person's views about authority and organizations, what they want from work, and how they aim to fulfil those objectives are all influenced by their cohort. Organizations will be better equipped to recognize and eliminate sources of conflict and expectation mismatches if they have a better knowledge of generational cohort differences. They will also be able to develop solutions that will satisfy the requirements of both employees and employers. Understanding the importance of generational cohort diversity can assist companies in developing a productive and engaged workforce. Simply adhering to the present discrimination laws and claiming a desire to be \"fair\" will not enough. Anoption organization unless they wish to jeopardize their viability, profitability competitiveness. In marketing generational cohorts is a segment of demographics which helps marketers determine how to target an advertisement and just who will be most likely to buy a product within an advertisement. Generational cohorts refer not only to age of a particular consumer but also to what generation they are in. Certain generations can determine what types of products a consumer of a given generation will buy. Generation cohorts include seniors, baby boomers, generation X & Y, and tweens: i) Seniors (before 1946): In America this generational group is considered the fastest growing group of them all. People in this cohort also want thing that are familiar, have a great value, and are a quality item. While seniors will generally have money to spend because they have been investing throughout their lives, they won't spend just to spend and are looking for specific high-quality items. They are also more likely to buy something in real estate, the travel industry, the automobile industry, or investments. They have time for the leisure of vacations, a second car, or a beach house because they are retired. Key Characteristics: conformity, conservatism, traditional family values, the nobility of sacrifice for the common good, patriotism, team player. 87 CU IDOL SELF LEARNING MATERIAL (SLM)
ii) Baby Boomers (1946 to 1964): This is the generation that is often crossing the senior gap as the years pass. Baby boomers are the children born after the influx in pregnancy rates after World War II. This generation spans about 18 years. Baby boomers have a few shared characteristics such as feelings of economic security, a willingness to spend money, and a need for retaining youth. Personal fitness places, salons, and products designed to stop mental aging will appeal most to this group. No longer having to support their children, baby boomers have significant disposable income - however, much of it is being and will be spent on services and experiences rather than products. Wellness is one of the major interests for people in this age cohort. Marketers targeting this age cohort are focusing on improving the convenience and quality of the shopping experience and emphasizing wellness offerings. iii) Generation X (1965 to 1976): This is the 11-year generation between 1965 and 1976. They tend to be more money conscious than their parents in the baby boomer generation and their investment savings tends to match up more with the seniors. They have an aversion to risk and want products that aren't considered status items. They are more likely to indulge in places like TJ Maxx or Walmart before stepping foot into a Bergdorf’s. They want quality, cheap, and convenient products. iv) Generation Y (1977 to 1994): This is the largest generational cohort since the Baby Boomers. They want to have an even balance between work and lifestyle. They are also more likely to move back in with their parents. This generation isn't learning technology; it is expecting technology and will be more impressed by Apple than by the same old PC. Generation Y consumers are more knowledgeable and independent in the' choice of products to buy. Marketers targeting this segment are attempting to build honest, authentic, personal relationships with consumers in this segment since they are not as responsive to conventional mass media advertising an branding as their parents. v) Tweens (1995 to present): If Generation Y expects technology, tweens technology. While technology became a thing Generation Y helped to reach staggering proportions, tweens have been around technology all of their liv They are the best target market for cell-phone companies as they use them more than in- person conversation. They like innovation and the best way to react them is by texts and Facebook. 2) Age Profile: The age profile of the consumer market can be extremely relevant to business. Although out of a marketer's control, the death rate and birth rate influence 'bulges' in generation cohorts, which may have positive or negative effects on the potential customer base. Marketers of young fashion may struggle due to a falling population teenager, at the 88 CU IDOL SELF LEARNING MATERIAL (SLM)
same time as children's wear marketers are thriving due to an upturn' the birth rate. Clearly, some marketers are more directly influenced by changing patterns than others, when their product range is directly linked to the age of the consumer, 3) Income and Expenditure: Although the feeling of being better-off is influenced one's level of wealth relative to those one comes into contact with, rather than actual income level, the majority of consumers in developed societies such Europe, U.S.A. and India have enjoyed an increasing level of personal disposal income since the Second World War. 4) Ethnic Diversity: It refers to the group within a larger society which considers itself to be different or is considered by the majority group to be different because of its distinctive ancestry, culture, and customs. 5) Working Patterns: The trend for more women to enter the workplace is continuing in Europe and occupations have moved from the traditional manufacturing industries to the service sector. This type of employment, characters by part-time and flexible working hours and 'lighter' work (such as keyboard and telephone operators, catering, and shop work) generally suits female employees and with the growth of communication and information technology, many job roles can actuallybe carried-out from the 'home-office'. At, the same time, the proportion of time spent by individuals in the workplace is increasing. B.CHANGES IN SHOPPER VALUES AND LIFESTYLE Values can be defined as broad preferences concerning appropriate courses of action outcomes. As such, values reflect a person's sense of right and wrong or what \"ought to\" be. \"Equal rights for all\" and \"People should be treated with respect and dignity\" i representative of values. Values tend to influence attitudes and behavior. India is a diverse country, a fact that is visibly prominent in its people, culture and climate from the eternal snows of the Himalayas to the cultivated peninsula of far South, from t deserts of the West to the humid deltas of the East, from the dry heat and cold of the Central Plateau to the cool forest foothills, Indian lifestyles clearly glorify the geography. The food, clothing and habits of an Indian differ in accordance to the place of origin. Some of the lifestyle changes that have occurred in the recent past and have had significant effect on market are the following: Time poverty and therefore a resulting convenience orientation, particularly ft working women. Car dependency, resulting in a growth of edge-of-town and out-of-town shopping centers. Cellular families, resulting in a growth of spending on personal appliances households with teenage children are likely to have multiple television sets telephones, music players, and personal computers. 89 CU IDOL SELF LEARNING MATERIAL (SLM)
Informality, as a possible result of the weakening influence of traditional bodies o authority such as the church, the police, the state, and the family. Home style changes resulting in the growth of spending on the home and garden. Increased focus on leisure time. Longer working hours puts a brighter spotlight on the quality of leisure time and consumers are prepared to purchase items and services that will enhance their precious free time. 1) Changing Shopping Perspective: Today's busy consumers have less free time. It is becoming harder for people to find time to shop in a leisurely manner. Customers are becoming more demanding and less forgiving as their shopping options increase in number, size, and variety. Consumers get bored quickly and expect marketers to blend shopping, eating, and playing into the one equation. Marketer must learn how to sell diversely to multiple generations and genders. This investment in customers will yield more sales and greater loyalty. The key to success in market is two pronged: i) Knowing what the customer wants, ii) Providing what the customer wants just as it is required in the most cost-efficient manner. The first requires customer intimacy, that is, the combination of soft market research (focus groups, laddering, psychographics), with hard data analysis - trends, patterns, statistical clustering, and demographics. The second requires a supply chain that is efficient and just-in-time. It requires the information to flow quickly and purposefully from the point of sale to the supplier, while integrating the logistics provider. 2) ConsumerPatronage for Different Retail Format: Consumer patronage differ sharply by the product category purchased. It is vital for marketers to know where consumers are buying various goods and services, and plan accordingly. Many consumers do cross-shopping where they: Shop for a product category through more than one retail format, or Visit multiple retailers on one shopping-trip. Some cross-shopping examples are given below: Some supermarket customers also regularly buy items carried by the supermarket at convenience stores, full-line department stores, drugstores, and specialty food stores. Some department store customers also regularly buy items carried by the department store at factory outlets and full-line discount stores. 90 CU IDOL SELF LEARNING MATERIAL (SLM)
c) In shopping centers, one-sixth of the people who visit music/electronic stores also shop at shoe-stores, one-sixth at family apparel stores, and 11 p cent at book-stores. Of those who visit hobby stores, 18 per cent also shop at sporting goods-stores. 3) Attitudes toward Shopping: Over the years, considerable research has been done o people's attitudes toward shopping. Let us highlight some of the recent research findings. Shopping Experience: People prefer the retailer whose layout they knew best, the retailer with no stuff in the aisles, the retailer with the best employee attitudes, tkcleanest retailer, and the retailer that appeared neatest and nicest inside. Attitudes toward Shopping Time: Retail shopping is viewed as a chore many people. Half of them “feel hassled to shop\". Changing Feelings about Retailing: There has been a major change in people attitudes toward spending, value, and shopping at established retail outlets over the past decade. People no longer believe high prices accurately reflect value. Today’s savvy, more pragmatic shoppers have discovered they can reasonable quality at everyday low prices. Reasons for Buying or not buying on a Shopping Trip: When makingpurchase with a particular retailer, both apparel and consumer electronic customers say they were most influenced by an item's being on sale - or have a good price even if not on sale - and the retailer's carrying the style/look/brand sought. Attitudes by Market Segment: Grocery shoppers can be divided several categories, such as: shopping avoiders - those who dislike grocery shopping; time-starved shoppers - those who will pay more for convenience responsible shoppers - those who feel grocery shopping is one of their household tasks; and traditional shoppers - those who plan store carefully. Attitudes toward Private Brands: About two-thirds of consumers belieretailer brands are as good as or better than manufacturer brands. Consumerbought branded items because they saw them as having particular image, qualitiesand consistency not found in other items. Impulse Purchases and Customer Loyalty: Two other aspects of consumer behavior merit special attention: Impulse Purchases: Impulse Purchases occur when consumers buy product and/or brands they had not planned on buying before entering a store, reading mail-order catalog, seeing a TV shopping show, turning to the web, and so forth. There are three kinds of impulse shopping: Completely Before coming into touch with a merchant, a consumer has no intention of making a purchase in a products or service category. When a customer comes into touch with a retailer, he or she plans to make a purchase in the products service category but has not yet decided on a brand. 91 CU IDOL SELF LEARNING MATERIAL (SLM)
Unintentional Substitution: A consumer plans to purchase a certain brand of product or service but changes his or her mind after speaking with a store. Customer Loyalty: The phrase \"customer loyalty\" refers to the behavior of repeat consumers as well as those who provide positive feedback, reviews, or testimonials. Customer loyalty refers to a customer's preference for one firm or product over another for a certain need. Customers in the packaged goods sector are said to as \"brand loyal\" because they choose to buy a certain brand of soap over others. However, note the term \"choose\"; customer loyalty is demonstrated when consumers make decisions and perform acts. In a poll, customers may report high levels of satisfaction with a firm, but contentment does not imply loyalty. Loyalty is demonstrated by the actions of the customer; customers can be very satisfied and still not be loyal. Those who make decisions based on a large amount of data Users who get information from numerous data sources using customized, complicated methods. It's also utilized by those who wish to access info with basic technologies. It's also necessary for individuals who wish to take a methodical approach to making judgments. Data warehouse is beneficial if the user needs quick performance on a large quantity of data, which is required for reports, grids, or charts. The first step is to create a data warehouse. If you're looking for 'hidden patterns' in data flows and groups, you've come to the right place. Components of data warehouses The front component is also known as the load manager. It handles all of the processes related to data extraction and loading into the warehouse. These activities involve data transformations to get the data ready for the data warehouse. Warehouse Manager: The warehouse manager is responsible for overseeing the warehouse's data administration. It conducts tasks such as data analysis to guarantee consistency, index and view construction, demoralization and aggregate generation, source data transformation and merging, and data archiving and baking-up. Query Manager: A backend component is sometimes known as a query manager. End user access tools. What Is a Data Warehouse Used For? Airline: It is used in the airline system for operational purposes such as crew assignment, route profitability studies, frequent flyer programme promotions, and so on. 92 CU IDOL SELF LEARNING MATERIAL (SLM)
Banking: It is frequently utilised in the banking industry to efficiently manage the resources available on the desk. A few banks also utilised it for market research, product performance analysis, and operations. Data warehouse was also utilised in the healthcare industry to strategize and anticipate outcomes, produce patient treatment reports, and exchange data with tie-in insurance firms, medical assistance organisations, and so on. Public sector: Data warehouses are utilised in the public sector to acquire intelligence. It assists government entities in keeping and analysing tax records and health-care information for each individual. Warehouses are largely utilised in the investment and insurance sectors to evaluate data patterns, client habits, and follow market movements. Data warehouses are frequently utilised in retail chains for distribution and marketing. It also aids in the tracking of goods, consumer purchasing patterns, and promotions, as well as setting price strategy. Telecommunications: In this industry, a data warehouse is utilised for product marketing, sales choices, and distribution decisions. Industry of Hospitality: Warehouse services are used by this industry to plan and estimate their advertising and marketing efforts, which they employ to target clients based on their feedback and travel habits. How to Set Up a Data Warehouse A three-prong strategy, as shown below, is the best method to handle the business risk associated with a Datawarehouse deployment. Business strategy: We identify technical issues, such as existing architecture and tools, in this section. Facts, dimensions, and characteristics are also identified. Data transformation and mapping are also passed. Data warehouse deployment should be done in phases based on topic areas. Booking and billing are two related business entities that should be developed first and then merged. Iterative Prototyping: Rather of implementing the Datawarehouse all at once, it should be done in stages. Implementing a Data Warehouse: Best Practices Make a plan to check the data's consistency, correctness, and integrity. The data warehouse should be well-integrated, well-defined, and well-timed. 93 CU IDOL SELF LEARNING MATERIAL (SLM)
When creating a Data warehouse, make sure you choose the correct tool, follow the life cycle, avoid data conflicts, and be willing to learn from your mistakes. Spend as little time as possible extracting, cleaning, and loading data. Ensure that all stakeholders, including businesspeople, are involved in the Data warehouse implementation. Ascertain that data warehousing is a collaborative/team effort. You don't want to build a data warehouse that is useless to the organisation. 5.6 SUMMARY The term consumer, end user, individual buyer and individual user refer to the same, a buyer who buys product and services for end use. 1. Point of sale. The most common time to gather data on your customers is at the point of sale. 2. Web forms. Using a form for gated content is fundamental. 3. Content marketing 4. Email marketing 5. Social media 6. In person 7. Webinars. 8. Surveys. 9. Create Brand Affinity. 10. Develop Customer Loyalty. 11. Provide Better Customer Service. 12. Direct Channel to Customers. 13. Launching New Products. 14. Take Your Brand to the Next Level with Strategic Marketing. So specifically, the end user or end consumer market refers to that group of consumers who buy/purchase goods, services and ideas for their final and ultimate consumption, not for the reproduction by any means. Consumer market is likely to be composed of end consumers whose need differs in 360-degree pattern. Understanding their need, want, value expectation and service expectations are the way to win this market by product and services which a firm is offering 94 CU IDOL SELF LEARNING MATERIAL (SLM)
5.7KEYWORDS Customer Channel: the imparting or interchange of thoughts, opinions, or information by speech, writing, or signs. Customer database: is the collection of information that is gathered from each person. Data Warehouse: A Data Warehouse is a place where data can be stored for more convenient mining. Data Mart:Data Mart is an index and extraction system. Customer Service: including the inspiration to write an awesome resume can be tough 5.8LEARNING ACTIVITY 1. What is meant by Datawarehouse? ___________________________________________________________________________ ___________________________________________________________________________ 2. Whatis a data mart? ___________________________________________________________________________ ___________________________________________________________________________ 5.9UNIT END QUESTIONS A. Descriptive Questions Short Questions 1. What is Customer information database? 2. What are the major uses of data warehouse? 3. Describe how the Database helps in company to generate more revenue. 4. What is the use of customer Database in Customer Relationship Management? 5. What is meant by Data Mart? Long Questions 1. How to develop a customer information database? 2. What are the factors influencing customer warehouse? 3. Narrate the steps involved in customer database of individual customers. 4. Discuss the uses of customer database. 5. Discuss about the changes in Shoppers values and lifestyles. B.Multiple Choice Questions 95 CU IDOL SELF LEARNING MATERIAL (SLM)
1. Record which is based on business customers past purchases, sales price and volumes is classifiedas a. Business database b. Customerdatabase c. Database’smarketing d. Companymarketing 2. Whole cluster of benefits when company promises to deliver through its market offering iscalled a. Valueproposition b. Customerproposition c. Productproposition d. Brandproposition 3. Third step in customer's valueanalysis a. Assessing attributesimportance b. Assessing company'sperformance c. Monitoring competitors’performance d. Both b andc 4. All costs customer expects to incur to buy any market offering is called a. Total economiccost b. Total functionalcost c. Total customercost d. Total functionalcost 5. Percentage or number of customers who move from one level to next level in buying decision process iscalled a. ConversionRates b. MarketingRates c. ShoppingRates d. LoyaltyRates Answers 1 –a, 2 –a, 3 - d, 4 – c, 5 –a 96 CU IDOL SELF LEARNING MATERIAL (SLM)
5.10REFERENCES References Books Sheth, J.N., Atul, P. and Shainesh, G. 2117. Customer Relationship Management: Emerging Concepts, Tools and Applications, 1st Edition, McGraw Hill Education. ISBN: 978-0070435049. Customer Relationship Management (CRM) by Dr K Govinda Bhat Mukherjee K, Customer Relationship Management: A Strategic Approach to Marketing Text Books References Francis Buttle and Stan Maklan, Customer Relationship Management: Concepts and Technologies, Third Edition, Special Indian Edition, 2015 Gupta, S. and Lehmann, D. 2105. Managing Customers as Investments: The Strategic Value of Customers in the Long Run, Prentice Hall. ISBN: 978-0131428959. Rai, A.K. 2112. Customer Relationship Management: Concepts and Cases, Prentice Hall India. ISBN: 978-8121346956. Gamble P Stone M and Woodcock N 1999, Customer Relationship Marketing up close and personal. London: Kogan Page: Jain S C 2005. CRM Shifts the paradigm, Journal of Strategic Marketing, 13 December, 275-91: Evans, M. O’Malley, L and Patterson M 2004, Exploring direct and Customer Relationship Marketing, London: Thomson Website http://whatis.techtarget.com/definition//0.289893,sid9_gci213567,00.html http://onlinebusiness.about.com/cs/marketing/g/CRM.htm http://www.siebel.com/what-is-crm/software-solutions.shtm http://computing-dictionary.thefreedictionary.com/CRM http://www.destinationcrm.com/articles/default.asp?ArticleID=5460 97 CU IDOL SELF LEARNING MATERIAL (SLM)
UNIT 6 -PLANNING AND IMPLEMENTATION OF CRM STRATEGY STRUCTURE 6.0 Learning Objectives 6.1 Introduction 6.2 Data Mining 6.3 Components of data mining 6.4 Scope and Importance of data mining 6.5 Data mining Application 6.6 Problems and issues in Data Mining 6.7 Summary 6.8Keywords 6.9Learning Activity 6.10 Unit End Questions 6.11 References 6.0 LEARNING OBJECTIVES After studying this unit, you will be able to: Describe framework of data mining Understand data mining Application Describe Problems and issues in data mining Discuss Scope of Data mining Explain Privacy Issues in Data Mining 6.1INTRODUCTION Data mining is the process of finding anomalies, patterns and correlations within large data sets to predict outcomes. Using a broad range of techniques, you can use this information to increase revenues, cut costs, improve customer relationships, and reduce risks and more. The Data Mining Specialization teaches data mining techniques for both structured data which conform to a clearly defined schema, and unstructured data which exist in the form of 98 CU IDOL SELF LEARNING MATERIAL (SLM)
natural language text. Specific course topics include pattern discovery, clustering, text retrieval, text mining and analytics, and data visualization. 6.2 DATA MINING Data Mining in Customer Relationship Management 1. Analysis of Baskets: Determine which goods people frequently buy together. Stocking, shop layout tactics, and promotions can all benefit from this knowledge. 2. Forecasting sales: Businesses can make stocking decisions by looking at time-based trends. It also assists you with supply chain management, financial planning, and total control over internal operations. 3. Marketing with a database: Customers' profiles may be created based on their demographics, tastes, preferences, and purchasing habits, among other factors. It will also help the marketing department create tailored marketing campaigns and promotions. This will result in increased production, the most efficient use of the company's resources, and the desired return on investment. 4. Life-cycle management that is predictive: Data mining allows a company to forecast the lifetime value of each client and provide suitable service to each group. 5. Segmentation of customers: Learn which clients are likely to buy your items and tailor your marketing campaigns and promotions to their likes and preferences. Because you won't be targeting people that exhibit little to no interest in your offering, this will enhance efficiency and yield the required ROI. 6. Customization of Products: Manufacturers have the ability to modify items to meet the specific demands of customers. They must be able to forecast which features should be packaged to fulfil consumer demand in order to do so. 7. Detection of fraud: A firm can take remedial action and prevent future fraud by reviewing previous transactions that were subsequently proven to be fraudulent. This functionality will be extremely beneficial to banks and other financial organisations. 8. Guarantees: Manufacturers must forecast the number of consumers who will file warranty claims, as well as the average cost of each claim. This will guarantee that business money is managed efficiently and effectively. 99 CU IDOL SELF LEARNING MATERIAL (SLM)
Figure 6.1 DATA MINING IN CRM According to William JFrawley, Gregory “Data mining or knowledge discovery in database is the nontrivial extraction of implicit, previously unknown and potentially useful information from data. This encompasses a number of different technical approaches such as clustering data summarization. Learning classification, finding dependency networks, analysingchanges and detecting anomalies 6.3 COMPONENTS OF DATAMINING The architecture of a typical data mining system may have the following major components 1) Database, data warehouse or other information repository: This is one or set of database, data warehouse spread sheets, or other kinds of information repositories. Data cleaning and data integration techniques may be performed on the data. 2) Data house or data warehouse server: the database or data warehouse server is responsible for fetching the relevant data based on the user data mining request. 3) Knowledgebase: This is the domain knowledge that is used to guide the search or evaluate the interestingness of resulting patterns. Such knowledge can include concept hierarchies used to organize attributes or attributes values into different levels of abstraction. 4) Data mining engine: this is essential to the data mining system and ideally consists of a set of functional modules for tasks such as characterization,association,classification, cluster analysis and evolution and deviation analysis. 5) Pattern Evaluation Module: This component typically employs interestingness measures and interacts with the data mining modules so as to focus the search toward interesting patterns. It may use interestingness threshold to filter out discovers patterns. 100 CU IDOL SELF LEARNING MATERIAL (SLM)
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