Customer Data Quality for CRM Systems


Published on

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

Published in: Business, Technology
1 Like
  • Be the first to comment

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide

Customer Data Quality for CRM Systems

  1. 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. 2. Agenda• Background/Motivation• Prior Work• Method• Results• Managerial Implications
  3. 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. 4. Managerial View of the Learning Organization Competitive Advantage Learning Activities Use 4. Interpret Move 3. Disseminate 2. Remember Store 1. Generate Get
  5. 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. 6. Learning Organization Theory SuggestsSimilar Hierarchy for Interactive Strategy Development Source: Roberts and Zahay 2012
  7. 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. 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. 9. Proposed CRM Data Type Hierarchy:Hypotheses are that use of these data types arepositively related to CRM Data Quality, in this order Personalizati on Customer Touchpoint Psycho-Demographic Transactional/RFM Data Customer Contact Information
  10. 10. What is CRM Data Quality?Overall, Data is of high quality when it reflects perceivedrealityIn 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. 11. Hypotheses Supported in General, Transactional,Contact Data More Important in Relation toCustomer 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. 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. 13. Contacts and Questions Debra Zahay Northern Illinois University 815-753-6215 James Peltier University of Wisconsin, Whitewater 262-472-5474 Anjala S. Krishen University of Nevada, Las Vegas 540-588-3961“Building the foundation for customer data qualityin CRM Systems for financial services firms,”Journal of Database Marketing andStrategy Management, Volume 19, Number 1,pages 5-16Peltier, J.W., Zahay, D.L. and Lehmann, D.L. (2012Forthcoming), "Organizational Learning and CRMSuccess: A Model for Linking OrganizationalPractices, Customer Data Quality, andPerformance," Journal of Interactive Marketing.