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
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
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A Framework to Understand Customer Data Quality in CRM Systems for Financial Services Firms
CADMEF IMC Academic Roundtable: May 10-11, 2012DePaul University, Chicago
Debra ZahayAssociate Professor of Interactive Marketing
Northern Illinois University
James Peltier Professor of Marketing
University of Wisconsin, WhitewaterMarketing Department
College of Business and Economics
Anjala S. KrishenAssistant Professor
Department of Marketing, Lee Business SchoolUniversity of Nevada, Las Vegas
Detailed purchase or donor historyCustomer service interactions
Times mailed/solicitedResponse to promotions
Consumer or business demographicsSelf-Reported or overlaidLifestyle, hobbies, interestsPersonal Dates -- birthday, anniversary, etc.
Predictive model scoresRFM ScoresModel segmentation scoresLifetime Value Scores
Practitioners Perceive the Value of Information as Hierarchical
Source: The Allant Group
Learning Organization Theory Suggests Similar Hierarchy for Interactive Strategy
Development
Source: Roberts and Zahay 2012
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
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
PersonalizationCustomer
Touchpoint
Psycho-Demographic
Transactional/RFM Data
Customer Contact Information
Proposed CRM Data Type Hierarchy: Hypotheses are that use of these data types are positively related to CRM Data Quality, in this order
CRM Data Quality
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
Personalization=.39
Transactional/RFM =.32Psycho-Demographic =.30
Customer Contact Information = .24Customer Touchpoint =.13
Offers and Communications
Customer Info and Collection Points
Hypotheses Supported in General, Transactional, Contact Data More Important in Relation to Customer Data Quality, Touchpoint Data Less So
CRM Data Quality
Hypothesized vs. Actual Relationships Suggest Shift in Management Focus
“Building the foundation for customer data quality in CRM Systems for financial services firms,” Journal of Database Marketing andStrategy 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.