Business Driven Information Systems 2e

1. Business Driven Information Systems 2e CHAPTER 9 CUSTOMER RELATIONSHIP MANAGEMENT AND BUSINESS INTELLIGENCE

2. Chapter Nine Overview SECTION 9.1 – CUSTOMER RELATIONSHIP MANAGEMENT • Customer Relationship Management Fundamentals • Using IT to Drive Operational CRM • Using IT to Drive Analytical CRM • CRM Trends: SRM, PRM, ERM • The Ugly Side of CRM SECTION 9.2 – BUSINESS INTELLIGENCE • Business Intelligence • Operational, Tactical, and Strategic BI • Data Mining • Business Benefits of BI

3. SECTION 9.1 CUSTOMER RELATIONSHIP MANAGEMENT

4. LEARNING OUTCOMES • Compare operational and analytical customer relationship management • Explain the formula an organization can use to find its most valuable customers • Describe and differentiate the CRM technologies used by sales departments and customer service departments

5. LEARNING OUTCOMES • Describe and differentiate the CRM technologies used by marketing departments and sales departments • Compare customer relationship management, supplier relationship management, partner relationship management, and employee relationship management

6. CRM FUNDAMENTALS • Customer relationship management (CRM) – involves managing all aspects of a customer’s relationship with an organization to increase customer loyalty and retention and an organization's profitability • Many organizations, such as Charles Schwab and Kaiser Permanente, have obtained great success through the implementation of CRM systems

7. CRM FUNDAMENTALS • CRM overview

8. CRM as a Business Strategy • CRM is not just technology, but a strategy, process, and business goal that an organization must embrace on an enterprisewide level • CRM can enable an organization to: • Identify types of customers • Design individual customer marketing campaigns • Treat each customer as an individual • Understand customer buying behaviors

9. Business Benefits of CRM • Organizations can find their most valuable customers through “RFM” - Recency, Frequency, and Monetary value • How recently a customer purchased items (Recency) • How frequently a customer purchased items (Frequency) • How much a customer spends on each purchase (Monetary Value)

10. Evolution of CRM • CRM enables an organization to: • Provide better customer service • Make call centers more efficient • Cross sell products more effectively • Help sales staff close deals faster • Simplify marketing and sales processes • Discover new customers • Increase customer revenues

11. Evolution of CRM • CRM reporting technology – help organizations identify their customers across other applications • CRM analysis technologies – help organization segment their customers into categories such as best and worst customers • CRM predicting technologies – help organizations make predictions regarding customer behavior such as which customers are at risk of leaving

12. Evolution of CRM • Three phases in the evolution of CRM include reporting, analyzing, and predicting

13. Evolution of CRM

14. Operational and Analytical CRM • Operational CRM – supports traditional transactional processing for day-to-day front-office operations or systems that deal directly with the customers • Analytical CRM – supports back-office operations and strategic analysis and includes all systems that do not deal directly with the customers

15. Operational and Analytical CRM

16. USING IT TO DRIVE OPERATIONAL CRM

17. Marketing and Operational CRM • Three marketing operational CRM technologies: • List generator – compiles customer information from a variety of sources and segment the information for different marketing campaigns • Campaign management system – guides users through marketing campaigns • Cross-selling and up-selling • Cross-selling – selling additional products or services • Up-selling – increasing the value of the sale

18. Sales and Operational CRM • The sales department was the first to begin developing CRM systems with sales force automation – a system that automatically tracks all of the steps in the sales process

19. Sales and Operational CRM • Sales and operational CRM technologies • Sales management CRM system – automates each phase of the sales process, helping individual sales representatives coordinate and organize all of their accounts • Contact management CRM system – maintains customer contact information and identifies prospective customers for future sales • Opportunity management CRM system – targets sales opportunities by finding new customers or companies for future sales

20. Sales and Operational CRM • CRM Pointers for Gaining Prospective Customer • Get their attention • Value their time • Overdeliver • Contact frequently • Generate a trustworthy mailing list • Follow up

21. Customer Service and Operational CRM • Three customer service operational CRM technologies: • Contact center (call center) • Web-based self-service system • Click-to-talk • Call scripting system

22. Customer Service and Operational CRM • Common features included in contact centers • Automatic call distribution • Interactive voice response • Predictive dialing

23. CRM Metrics • Sales Metrics • Number of prospective customers • Number of new customers • Number of retained customers • Number of open leads • Number of sales calls • Amount of new revenue • Amount of recurring revenue • Number of proposals given

24. CRM Metrics • Service Metrics • Cases closed same day • Number of cases handled by agent • Number of service calls • Average number of service requests by type • Average time to resolution • Average number of service calls per day

25. CRM Metrics • Marketing Metrics • Number of marketing campaigns • New customer retention rates • Number responses by marketing campaign • Number of purchases by marketing campaign • Revenue generated by marketing campaign • Customer retention rate

26. USING IT TO DRIVE ANALYTICAL CRM • Personalization – when a Web site knows enough about a persons likes and dislikes that it can fashion offers that are more likely to appeal to that person • Analytical CRM relies heavily on data warehousing technologies and business intelligence to glean insights into customer behavior • These systems quickly aggregate, analyze, and disseminate customer information throughout an organization

27. USING IT TO DRIVE ANALYTICAL CRM • Analytical CRM information examples • Give customers more of what they want • Value their time • Overdeliver • Contact frequently • Generate a trustworthy mailing list • Follow up

28. CRM TRENDS: SRM, PRM, AND ERM • Current trends include: • Supplier relationship management (SRM) • Partner relationship management (PRM) • Employee relationship management (ERM)

29. THE UGLY SIDE OF CRM • Business 2.0 ranked “You” the customer as the number one person who mattered most

30. OPENING CASE QUESTIONSCustomer First Awards • Summarize the evolution of CRM and provide an example of a reporting, analyzing, and predicting question Progressive might ask its customers • How could Progressive’s marketing department use CRM technology to improve its operations? • How could Mini’s sales department use CRM technology to improve its operations?

31. OPENING CASE QUESTIONSCustomer First Awards • How could Progressive and Mini’s customer service departments use CRM technology to improve their operations? • Define analytical CRM and its importance to companies like Progressive and Mini

32. SECTION 9.2 BUSINESS INTELLIGENCE

33. LEARNING OUTCOMES • Explain the problem associated with business intelligence. Describe the solution to this business problem • Describe the three common forms of data-mining analysis? • Compare tactical, operational, and strategic BI

34. LEARNING OUTCOMES • Explain the organization-wide benefits of BI • Describe the four categories of BI business benefits

35. BUSINESS INTELLIGENCE • Business intelligence (BI) – applications and technologies used to gather, provide access to, and analyze data and information to support decision-making efforts • Parallels between the challenges in business and challenges of war • Collecting information • Discerning patterns and meaning in the information • Responding to the resultant information

36. The Problem: Data Rich, Information Poor • Businesses face a data explosion as digital images, email in-boxes, and broadband connections doubles by 2010 • The amount of data generated is doubling every year • Some believe it will soon double monthly

37. The Solution: Business Intelligence • Improving the quality of business decisions has a direct impact on costs and revenue • BI systems and tools results in creating an agile intelligent enterprise

38. The Solution: Business Intelligence • BI enables business users to receive data for analysis that is: • Reliable • Consistent • Understandable • Easily manipulated

39. The Solution: Business Intelligence • BI can answer tough customer questions

40. OPERATIONAL, TACTICAL, AND STRATEGIC BI • Claudia Imhoff, president of Intelligent Solutions, divides the Spectrum of data mining analysis and business intelligence into three categories: • Operational • Tactical • Strategic

41. OPERATIONAL, TACTICAL, AND STRATEGIC BI

42. OPERATIONAL, TACTICAL, AND STRATEGIC BI

43. BI’s Operational Value • Richard Hackathorn’s graph demonstrating the value of operational BI

44. BI’s Operational Value • The key is to shorten the latencies so that the time frame for opportunistic influences on customers, suppliers, and others is faster, more interactive, and better positioned

45. DATA MINING • Data mining – process of analyzing data to extract information • Data-mining tools – use a variety of techniques to find patterns and relationships in large volumes of information • Classification • Estimation • Affinity grouping • Clustering

46. DATA MINING • Common forms of data-mining analysis capabilities include: • Cluster analysis • Association detection • Statistical analysis

47. Cluster Analysis • Cluster analysis – a technique used to divide an information set into mutually exclusive groups such that the members of each group are as close together as possible to one another and the different groups are as far apart as possible • CRM systems depend on cluster analysis to segment customer information and identify behavioral traits

48. Association Detection • Association detection – reveals the degree to which variables are related and the nature and frequency of these relationships in the information • Market basket analysis • INSERT FIGURE 9.17

49. Statistical Analysis • Statistical analysis – performs such functions as information correlations, distributions, calculations, and variance analysis • Forecast – predictions made on the basis of time-series information • Time-series information – time-stamped information collected at a particular frequency

50. BUSINESS BENEFITS OF BI • Benefits of BI include: • Single Point of Access to Information for All Users • BI across Organizational Departments • Up-to-the-Minute Information for Everyone