CADMEF IMC Academic Roundtable: May 10-11, 2012 DePaul University, Chicago, A Framework to Understand Customer Data Quality in CRM Systems for Financial Services Firms

1. A Framework to Understand Customer Data Quality in CRM Systems for
Financial Services Firms
CADMEF IMC Academic Roundtable: May 10-11, 2012
DePaul University, Chicago
Debra Zahay
Associate Professor of Interactive Marketing
Northern Illinois University
James Peltier
Professor of Marketing
University of Wisconsin, Whitewater
Marketing Department
College of Business and Economics
Anjala S. Krishen
Assistant Professor
Department of Marketing, Lee Business School
University of Nevada, Las Vegas

2. Agenda
• Background/Motivation
• Prior Work
• Method
• Results
• Managerial Implications

3. Primary Research Streams 1999-2012
Customer Customer
Information Information
Management Use in New
for Competitive Product
Advantage Development
Data Quality,
Personalization
and CRM
With co-authors: Domagalski, Fredericks, Griffin, Handfield, Krishen,
Lehmann, Mason, Payton, Peterson, Peltier, Schibrowsky, Shavitt, Schultz,
Scovotti, Thorbjornsen, White

4. Managerial View of the Learning Organization
Competitive Advantage
Learning Activities
Use
4. Interpret
Move 3. Disseminate
2. Remember
Store
1. Generate
Get

5. Practitioners Perceive the Value of
Information as Hierarchical
• Successful marketing databases Predictive model scores
contain many “views” of RFM Scores
customers and prospects... Models/
Model segmentation scores
Scores Lifetime Value Scores
Consumer or business demographics
Self-Reported or overlaid
Descriptive Lifestyle, hobbies, interests
Data Personal Dates -- birthday, anniversary, etc.
Times mailed/solicited
Promotional History Response to promotions
Detailed purchase or donor history
Transactional History Customer service interactions
Name, address, phone
E-mail
Base Contact Data Preferred communication. Channel
Join/First Purchase Date
Source
5 Source: The Allant Group

6. Learning Organization Theory Suggests
Similar Hierarchy for Interactive Strategy
Development
Source: Roberts and Zahay 2012

7. Research Method & Analysis
• Qualitative Study
• Pre-Test
• Final Survey
• Factor analysis to refine variables
• Regression analysis to determine
relationship between use of customer data
types and CRM Data Quality

8. Survey Background
• Data Collection:
– 525 mailed
– Three waves, one mail wave, one including $2 bill and
one telephone follow up wave
– 32 % response rate
• 170 Executives in Financial Services
– 50% primarily b2b and 40% b2c, rest other trade
relationships
– 50% had retail relationships, 27% relied on outside sales
– 10% online sales
– Executives had typically twenty years of experience
• 166 useable surveys
• Response: Percent of Time Data Collected

9. Proposed CRM Data Type Hierarchy:
Hypotheses are that use of these data types are
positively related to CRM Data Quality, in this order
Personalizati
on
Customer
Touchpoint
Psycho-Demographic
Transactional/RFM Data
Customer Contact Information

10. What is CRM Data Quality?
Overall, Data is of high quality when it reflects perceived
reality
In a customer context, we measured managers’
perception of:
• Overall quality of the customer contact system
• Overall Quality of Data
• Overall quality of the CRM system
• 5-Point Scale
• 5=Strongly Agree
• 1=Strongly Disagree

11. Hypotheses Supported in General, Transactional,
Contact Data More Important in Relation to
Customer Data Quality, Touchpoint Data Less So
Personalization
=.39
Transactional/RFM =.32 Offers and
Communications
Psycho-Demographic =.30
Customer Info and
Customer Contact Information = .24 Collection Points
Customer Touchpoint =.13

12. Hypothesized vs. Actual Relationships
Suggest Shift in Management Focus
Personaliz
ation
Personalization
Customer =.39
Touchpoint
Transactional/RFM
Psycho- =.32
Demographic Psycho-
Demographic =.30
Transactional/RFM Data
Customer Contact Information
= .24
Customer Contact Information Customer Touchpoint =.13

13. Contacts and Questions
Debra Zahay
Northern Illinois University
815-753-6215
zahay@niu.edu
James Peltier
University of Wisconsin, Whitewater
262-472-5474
peltierj@uww.edu
Anjala S. Krishen
University of Nevada, Las Vegas
540-588-3961
anjala.krishen@unlv.edu
“Building the foundation for customer data quality
in CRM Systems for financial services firms,”
Journal of Database Marketing and
Strategy Management, Volume 19, Number 1,
pages 5-16
Peltier, J.W., Zahay, D.L. and Lehmann, D.L. (2012
Forthcoming), "Organizational Learning and CRM
Success: A Model for Linking Organizational
Practices, Customer Data Quality, and
Performance," Journal of Interactive Marketing.