Customer Relationship Management (CRM) Not a concept or a project Business strategy

2. Value of Customer Relationship Management Understand the essential elements that comprise a customer relationship management program • Customer Relationship Management (CRM) • Not a concept or a project • Business strategy • To understand, anticipate and manage the needs of an organization’s current and potential customers • CRM • A combination of strategic, process, organizational, and technological change McGraw-Hill/Irwin

3. Value of Customer Relationship Management Understand the essential elements that comprise a customer relationship management program • Allied Medical Corp • Strong correlation between customer satisfaction • 50% of unhappy customers will “bail out” • Knowing your customer and adding value to their transactions—add profits McGraw-Hill/Irwin

4. Describe the relationship that exist between marketing research and customer relationship management The Essentials of CRM • Customer Relationship Management (CRM) • Integration of customer information throughout the business • Business enterprise • Must respond to rapidly changing environments • Disrupters • Internet • Electronic commerce • New types of businesses • Retaining your current customers cheaper than getting new ones • ratio 1 to 5 for sales and marketing expenditures • http://www.mannesmann.comhttp://www.lendingtree.com McGraw-Hill/Irwin

5. Describe the relationship that exist between marketing research and customer relationship management Exhibit 4.1 McGraw-Hill/Irwin

6. Describe the relationship that exist between marketing research and customer relationship management The Essentials of CRM • Customer Interaction • Organizations • Centerpiece of CRM Program • Customer Knowledge McGraw-Hill/Irwin

7. Describe the relationship that exist between marketing research and customer relationship management The Essentials of CRM • CRM begins with the determining of • Types of relationships with customers • Types of interaction required to acquire and capture customer information • How to store and integrate the customer data • How and when to analyze the information to determine the best customer segments based on profitability • How this information is to be disseminated throughout the enterprise McGraw-Hill/Irwin

8. Marketing Research and Customer Relationship Management Describe the relationship that exist between marketing research and customer relationship management • Primary Functions of CRM • To Collect • To Store • To Analyze Customer Interaction Information • Customer knowledge McGraw-Hill/Irwin

9. Marketing Research and Customer Relationship Management Describe the relationship that exist between marketing research and customer relationship management • Marketing Research’s Role • Market Intelligence • Real-time customer information • CRM Starts with Customer Knowledge • Understanding the wants and needs of customers • Major Use of Customer Knowledge • Assess profitability and provide increased value to targeted customer segments McGraw-Hill/Irwin

10. Marketing Research and Customer Relationship Management Describe the relationship that exist between marketing research and customer relationship management • Marketing Research • What kind of relationship will add value to the enterprise’s customers? • What is the value perception of the customer segment and how can the value be enhanced? • What products, services, and mode of delivery have value to the customer segment? • What are customers’ responses to marketing and sales campaigns? McGraw-Hill/Irwin

11. Marketing Research and Customer Relationship Management Describe the relationship that exist between marketing research and customer relationship management • MR Captures and Integrates Information • Demographic, psychographic, behavioral and preference data • Data Used for Two Purposes • To create customer profiles • To segment customers • Create a Market Intelligence Culture • silos McGraw-Hill/Irwin

12. Transforming Marketing Research into Market Intelligence Understand the meaning of marketing intelligence • Customer Information Falls into the 20/80 ratio • MIE Business Model—Granular Data • Detailed, highly personalized and specifically structured around the individual customer • Overall goal—capturing and retaining customers • Customer-centric Approach McGraw-Hill/Irwin

13. Transforming Marketing Research into Market Intelligence Understand the meaning of marketing intelligence • Strategic Use of Customer Information • Two Key Questions • What does my customer value? • What is the value of my customer? • Primary Information Collected • MR – Analyzes customer values, likes and dislikes, lifetime value, and profitability • Information used – To refine product and service offerings McGraw-Hill/Irwin

14. Transforming Marketing Research into Market Intelligence Understand the meaning of marketing intelligence • Information Based on Transactional Focus • Exchanges with customers—Window of Opportunity • Build loyalty • Enterprise Wide Approach to the Use of Information • Information at every touchpoint • Technology Support of the CRM Structure • Link-pin—turning customer data into customer knowledge McGraw-Hill/Irwin

15. Data Collection in a CRM Environment Illustrate the process of data collection for a CRM program • Technology • Driving force behind the integration and sharing of data and the collection of customer data • Goal • To collect all relevant customer interaction data • to store the data in the warehouse • To analyze the data McGraw-Hill/Irwin

16. Data Collection in a CRM Environment Illustrate the process of data collection for a CRM program • Accessing Customer Data over the Internet • Passive Data • Such as geographic and specific user information • Active Data • User interacts with website • Cookies • Directed Data • Comprehensive data collected about customers McGraw-Hill/Irwin

17. MR and CM: The Database Process Illustrate the development and purpose of the data warehouse • What is a Database • Collection of information indicating what customers are purchasing, how often they purchase, and the amount they purchase • Database Generated By • Sales invoices • Warranty cards • Telephone calls • Market research projects McGraw-Hill/Irwin

18. Data Collection in a CRM Environment Illustrate the development and purpose of the data warehouse • Purpose of a Customer Database • To develop meaningful, personal communication with its customers • Customer Database • Specific Purpose of Databases • To improve the efficiency of market segmentation • To increase the probability of repeat purchases • To enhance sales and media effectiveness • To enable users to measure, track and analyze customer behaviors McGraw-Hill/Irwin

19. Data Collection in a CRM Environment Illustrate the development and purpose of the data warehouse • Benefits of Databases • Exchanging information with customers • Determining heavy users • Determining lifetime customer value • Building segment profiles McGraw-Hill/Irwin

20. Data Collection in a CRM Environment Illustrate the development and purpose of the data warehouse • Marketing databases answer crucial questions • Why do some consumers buy our products or services regularly, while others do not? • How do our products compare with the competition? • What is the relationship between perceived value and price of the product? • How satisfied are customers with the service level and support for the product? • What are the comparisons among lifestyles, demographics, attitudes, and media habits? McGraw-Hill/Irwin

21. Marketing Research and Data Enhancement Illustrate the development and purpose of the data warehouse • Data Enhancement • The overlay of information about customers to better determine their responsiveness to marketing programs • Three Advantages • Move knowledge of customers • Increased effectiveness • Predicting responses to changing marketing programs McGraw-Hill/Irwin

22. Exhibit 4.2 Illustrate the development and purpose of the data warehouse McGraw-Hill/Irwin

23. Marketing Research and Data Enhancement Illustrate the development and purpose of the data warehouse • Effective Development of Enhanced Databases • Geodemographic factors • Attribute data • Attitudinal data • Motivational data • Target market characteristics • Heavy product users versus light users • Based on demographic, purchase volume and frequency • Other data points—shopping patterns, advertising effectiveness and price sensitivity McGraw-Hill/Irwin

24. Comprehensive Collection of Interrelated Data Databases Affinity Frequency Recency Amount Rule of Thumb in Database Development Long-term commitment Width Total number of records Depth Overall number of key data fields Resources Dynamics of Database Development Illustrate the development and purpose of the data warehouse McGraw-Hill/Irwin

25. Illustrate the development and purpose of the data warehouse Database Technology • What is Data • Data Item or Field • Database Technology • Tools used to transform data into information • Processes data and stores it in a single databank • Database management system • Data dictionary McGraw-Hill/Irwin

26. Illustrate the development and purpose of the data warehouse Database Technology • Two Types of Database Processing Systems • Sequential Database System • Organizes data in a simple path, linkage or network • Only two single data fields can be paired • See Exhibit 4.4 McGraw-Hill/Irwin

27. Exhibit 4.4 Illustrate the development and purpose of the data warehouse McGraw-Hill/Irwin

28. Illustrate the development and purpose of the data warehouse Database Technology • Two Types of Database Processing Systems • Relational Databases System • Requires no direct relationship between data fields • Uses tables with rows and columns • Tables not the data fields are linked together • See Exhibit 4.5 McGraw-Hill/Irwin

29. Exhibit 4.5 Illustrate the development and purpose of the data warehouse McGraw-Hill/Irwin

30. What is Data Warehousing? Illustrate the development and purpose of the data warehouse • Data Warehouse • Central Repository • Two Purposes • Collect and store data • Operational Data • Online Transactional Processing (PLTP) • Collect, organize and make data available • Informational Data • Online Analytical Processing (OLAP) • Comparable to a Library McGraw-Hill/Irwin

31. Database Technology and Data Warehousing Illustrate the development and purpose of the data warehouse • Marketing-Related Data and Data Warehousing • Two Unique Forms of Customer Data • Real-time transactional data • Collected at the point of sale • Customer-volunteered information • Customer comment cards or complaints • Customer registration information • Customer communications via chat rooms • Data obtained through advisory groups McGraw-Hill/Irwin

32. Data Mining: Transforming Data Into Information Explain the process of data mining as it relates to the data warehouse • Data Mining • Process of finding hidden relationships among variables contained in data stored in the data warehouse • Analysis Procedure • Known primarily for the recognition of significant patterns of data for particular customers or customer groups McGraw-Hill/Irwin

33. Exhibit 4.6 Explain the process of data mining as it relates to the data warehouse McGraw-Hill/Irwin

34. Database Technology and Data Warehousing Explain the process of data mining as it relates to the data warehouse • Marketing Research Question • Description • Prediction • Data Mining Approaches • Profile groups • Predict customer satisfaction levels McGraw-Hill/Irwin

35. Database Technology and Data Warehousing Explain the process of data mining as it relates to the data warehouse • Data Mining Implementation • Identifies • Method for storage and categorization of data • Data Mining Approach • Visual Data Mining • Presentation of the results • Access and comprehension of the results of analysis McGraw-Hill/Irwin

36. Understand the role of modeling in database analysis Database Modeling • Database Modeling and Analysis • Statistical Analysis • Designed to Summarize • Customer Modeling • Question that should be asked • Scoring Models • Used to predict • Initial object McGraw-Hill/Irwin

37. Understand the role of modeling in database analysis Exhibit 4.8 McGraw-Hill/Irwin

38. Understand the role of modeling in database analysis Database Modeling • Key Variables in Scoring Models • Enable researcher to determine which factors can be used to separate customer into purchase groups • Use weights to multiply assigned values • Use actual purchase behavior data • Key variables • Assign weights or scores depending on ability to predict purchase behavior McGraw-Hill/Irwin

39. Understand the role of modeling in database analysis Database Modeling • Lifetime Value Models • Premise • Lifetime Value Models • Price variables • Sales promotional variables • Advertising expenditures • Product costs • Relationship-building efforts • Database Information • Used to identify most profitable customers McGraw-Hill/Irwin

40. Understand the role of modeling in database analysis Exhibit 4.9 McGraw-Hill/Irwin

41. Summary • Value of Customer Relationship Management • Essentials of Customer Relationship Management • Marketing Research and Customer Relationship Management • Transforming Marketing Research Into Market Intelligence • Data Collection in a CRM Environment • Marketing Research and Customer Management: The Database Process McGraw-Hill/Irwin

42. Summary • Marketing Research and Data Enhancement • The Dynamics of Database Development • Database Technology • What Is Data Warehousing? • Data Mining: Transforming Data Into Information • Database Modeling McGraw-Hill/Irwin