Creating Customer and Company Value through CRM. Richard Staelin Edward & Rose Donnell Professor of Business Administration Duke University

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1 Creating Customer and Company Value through CRM Richard Staelin Edward & Rose Donnell Professor of Business Administration Duke University

2 What is CRM? Strategic CRM Operational CRM Analytical CRM 2

3 Core CRM Processes Collaborative Communication Information Capture Information Integration Information Access Information Use Develop customer profile Segmentation Retention behavior Channel analysis Customize offers Best customers CLV Knowledge of costs 3

4 What has gone wrong with CRM? Core Capabilities Firm Performance Technology 4

5 Why CRM works The more relationships the customer has with the firm, the higher the real and psychological switching costs Number of years with the bank or less or more Number of Services Used 5

6 Why CRM works The more relationships the customer has with the firm, the greater the expected profits Contribution Margin (Index) or less or more Number of services used 6

7 Why CRM works The more relationships the firm has with the customer, the more the firm knows about the customer s behavior Use CRM as a tool for learning about customers needs Avoid black-box tools for database marketing when doing CRM Good predictions are even better with behavioral insights 7

8 Why CRM works Cost of acquiring new customers is higher than cost of retaining them New customer you can acquire at the margin is likely to be a switcher who will eventually switch to a better offer. Retention probability Marginal acquisition cost 8

9 The Problem In many businesses, the customers most likely to sign on are precisely the worst customers you could possibly find» Reichheld, The Loyalty Effect.» The customers you want to attract don't respond, and the ones you don't want to attract do» Richard E. Mirman, Chief Marketing Officer, Harrah s Entertainment, Inc. (M)ost of the people applying for a card with say, a 12 percent APR, were the last people issuers would approve» Lucy Lazarony, bankrate.com 9

10 The Culprit: Adverse Selection There are good and bad customers Often, you do not know which is which before it is too late Major problem in marketing risk products Insurance, loans, credit cards Potential for conflict between functions acquiring and approving customers Solutions: Self-selection through multiple products Need as many products as types of customers Screening 10

11 Problems with Screening Costly Must screen all customers to determine type When cross-selling to current customers Best customers will not respond Wider range of options Rejection can lead to termination of relationship 11

12 Results for Top 3 Deciles N = 1157 Select based on Response Select based on Approval Simultaneous Approach Responses Approvals Rejections

13 Analytic CRM for Customer Retention How bad is customer churn? Some Industry Statistics: Cellular 25-35% Paging 30-48% Computer on-line service 33% Long Distance Phone 25% 13

14 The Value of Customer Retention Typical Wireless Carrier 500,000 users 25% churn rate $300/customer acquisition cost $500/year average customer value 5% reduction in churn equals: $1.9 million acquisition savings ($1.9 m = 125,000 churners x 5% x $300/customer) $3.1 million in retained customer value ($3.1 m = 125,000 churners x 5% x $500/customer) TOTAL SAVINGS: $5.0 million => $15,000 per day Source: Oracle website 14

15 How to reduce churn? Don t be too aggressive in customer acquisition (marginal acquisitions are more likely to attrite) Your current customer is your best prospect Cross-selling Up-selling Exit surveys & early attrition-detection 15

16 Customer Retention Modeling Exit surveys Why do you want to leave? Where are you going? What could we have done to keep you? (too late) Attrition modeling (looking at the past) Detecting early signals of attrition Identifying customers at risk for preventive measures 16

17 Early defection detection Exit Interview Past behavior 17

18 Analytic CRM for Customer Development Customer transactions are becoming increasingly impersonal, reducing the opportunities for personal selling Cross-selling increases the number of ties between the firm and the customer (higher switching costs) Opportunity to learn about customer s needs, improving the firm s competitiveness is done by value rather than persuasion More effective on incoming than outgoing calls Must avoid over-touching the customer The right product for the right customer at the right time 18

19 The Royal Bank of Canada experienced a direct response rate of 40% when it increased the timeliness and relevancy of its campaigns. - Peppers & Rogers Group 19

20 Observed High Technology Industry Predicted Product Purchased? Q1 Q2 Q3 Q4 Q5 Q6 Time Managerial Questions: Which customers would provide revenue in the next planning cycle? What product (s) would a customer purchase given past purchases? When would the customers make their purchase(s)? How much to spend on a given customer? 20

21 Results from the field experiment (B-to-B High Tech Firm) Difference between test and control group Parameter Hardware Software Revenue ($) a Cost of Communication ($) Number of Contacts Before Purchase Profits ($) Return on Investment -952*** -6*** 970*** 1.4*** -1,182** - 4*** 1,1116*** 1.5*** Hardware & Software *** -5*** 749** 1.9*** a The reported values are unit values per customer during the experiment year and are cell medians; *** Significant at α =.01 21

22 Cross-selling of financial services If there is a natural sequence of acquisition of financial services, it can be inferred from observed buyer behavior Services are ordered according to their difficulty The financial needs or financial maturity of a household can be inferred from the financial services currently in use. 22

23 The pyramid of financial independence Risk & Tax Protection Growth stocks, municipal bonds, tax shelters & real estate Growth to offset inflation Risk management Stocks, mutual funds, bonds, cash management accounts Emergency cash reserve Foundation Products Insurance, Pension/IRA plans Money market, time deposits Checking, savings, credit card, loans 23

24 Empirical Evidence Panel of 3000 investors in the US Portfolio of financial services utilized during a year Application of Latent Trait Theory to estimate: difficulty of each financial service Financial Maturity of each investor Item Characteristic Curve relating a service difficulty to the investors Financial Maturity 24

25 Item characteristic curve 1 Likelihood of Buying Score 25

26 Foundation Products 100.0% 90.0% 80.0% Usage Probablity 70.0% 60.0% 50.0% 40.0% 30.0% Average Difficulty of Foundation Products 20.0% 10.0% Difficulty of a service 0.0% Financial Maturity Checking/Savings/NOW Bank Credit Card Home Mortgage Other Loans 26

27 Risk Management & Cash Reserves 100.0% 90.0% 80.0% Usage Probablity 70.0% 60.0% 50.0% 40.0% 30.0% 20.0% 10.0% 0.0% Financial Maturity Life Insurance Pension Plan IRA Money Market 27

28 Growth to offset inflation 100.0% 90.0% 80.0% Usage Probablity 70.0% 60.0% 50.0% 40.0% 30.0% 20.0% 10.0% 0.0% Financial Maturity Corporate Stocks Cash Management Account Mutual Funds 28

29 Risk and Tax Protection 100.0% 90.0% 80.0% 70.0% Usage Probablity 60.0% 50.0% 40.0% 30.0% 20.0% 10.0% 0.0% Financial Maturity Tax Shelters Corp.Govmt Bonds Real Estate 29

30 Current Income -Post Retirement 100.0% 90.0% 80.0% 70.0% Usage Probablity 60.0% 50.0% 40.0% 30.0% 20.0% 10.0% 0.0% Financial Maturity CD/T-Bill Time Deposit Annuity 30

31 How to utilize the model Financial Maturity 31 Probability of Ownership

32 How to utilize the model Financial Maturity 32 Probability of Ownership

33 The iceberg effect The customer database provides only a glimpse of the customers behavior Relationship with your firm Relationships with your competitors 33

34 Cross-selling of financial services Sample of customers from a commercial bank in Brazil Data Internal (customer database) Number of transactions/month Volume of Deposits in the bank Demographic data Use of 22 services within the bank External (survey) Use of 22 services outside the bank 34

35 Model Calibration DATA Customer Database Survey MODEL Sequence of acquisition for services within and outside the bank 35

36 Implementation Test Customer Database Model of service usage within and outside the bank Survey Test Likelihood of usage outside the bank 36

37 % of all users outside the bank Top users outside the bank, as predicted by the model 37

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40 Product Centric Cross-selling Prod.A Prod.B Etc. Prod.Z Cust.1 Cust.2 Etc. Cust.N 40

41 Customer-Centric Cross-Selling Analyze customer behavior Measure customer value What should be the strategy with this customer? Cost reduction Revenue enhancement Development Retention 41

42 Customer Centric Cross-selling Prod.A Prod.B Etc. Prod.Z Cust.1 Cust.2 Etc. Cust.N 42

43 How analytics can enhance CRM Acquisition: Look back at past acquisition efforts to identify the profile of profitable acquired customers. Development: Look at patterns of past service usage across customers to identify the next service to cross-sell to each customer Retention: Relate exit surveys to past customer behavior to identify early signals of attrition 43

44 Acquiring, developing and retaining profitable customers What s CRM Why CRM works Analytical CRM Customer acquisition Developing customer relationships Churn management 44

45 What s CRM: A Historical Perspective Mass Marketing Segmented Marketing One-to-One Marketing 45

46 One-to-One Marketing Small businesses Limited number of customers Regional monopolies 46

47 Mass Marketing 47

48 Segmented Marketing 48

49 What s CRM: Back to One-to-One Marketing Market saturation Brand proliferation Brand switching Customization Consumer demand for personalized services CRM Information Technology 49

50 Customer Relationship Management? 50 The Customer s Value to Us Low High Low High Our Value to the Customer

51 The customer life cycle acquisition Development and retention Universe of Customers Prospect Target Market Responder Responder New Customer Retained or repeat customer Low Value High Potential High Value Former Customer Forced Churn Voluntary Churn Winback 51

52 Analytic CRM for Customer Acquisition Typical Customer Acquisition Program 1-4% RESPONSE SAMPLE OF LEADS GEO-DEMOGRAPHICS (AND THE KITCHEN SINK) NON-RESPONSE 96-99% RESPONSE MODEL: RESPONSE = f(β, PREDICTORS) 52

53 Problems with Response Modeling for Customer Acquisition Most response models pay more attention to non-responses (majority) than to responses, leading to false negatives False positives produce small direct costs False negatives produce larger opportunity costs Leads with high response probability might not be the most attractive customers on the long run Learn from the past, by looking at subsequent Customer Lifetime Value from previous acquisition programs 53