an integrated imc data framework dmef direct/interactive marketing research summit: october 13-14,...
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An Integrated IMC Data FrameworkDMEF Direct/Interactive Marketing Research Summit: October 13-14,
2012Las Vegas, NV
James Peltier
Professor of MarketingUniversity of Wisconsin, Whitewater
Marketing DepartmentCollege of Business and Economics
Debra Zahay
Associate Professor of Interactive MarketingMarketing Department
Northern Illinois University
Anjala S. KrishenAssistant Professor
Department of Marketing, Lee Business SchoolUniversity of Nevada, Las Vegas
Agenda
• Background/Motivation• Prior Work• Hypotheses• Method• Results• Implications
Managerial View of the Learning Organization
1. Generate
2. Remember
3. Disseminate
4. Interpret
Learning Activities
Competitive Advantage
Use
Move
Store
Get
PersonalizationCustomer
Touchpoint
Psycho-Demographic
Transactional/RFM Data
Customer Contact Information
Zahay, Peltier and Krishen (2012) Examined a Hierarchical Framework for IMC Data
CRM Data Quality
Personalization=.39
Transactional/RFM =.32Psycho-Demographic =.30
Customer Contact Information = .24Customer Touchpoint =.13
Offers and Communications
Customer Info and Collection Points
Relationships Supported in General, Transactional, Contact Data More Important in Relation to Customer
Data Quality, Touchpoint Data Less So
CRM Data Quality
The Strategic CRM Context (Payne and Frow 2005)
Improves Shareholder Value by:
Developing relationships with key customers and
segments
Uses data and information to co-create value with
customers
Requires Data-Driven Cross Functional Integration of:
Processes
People
Operations
Marketing Capabilities
Enabled by:
Information Technology Applications
Multi-Stage Research Method & Analysis
• Qualitative Study• Pre-Test• Final Survey• Exploratory Factor analysis, correlation
analysis, Coefficient Alphas, CFA• SEM to determine relationship between use
of customer data types and CRM Data Quality
Method: Survey Data Collection• 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
What is CRM System Quality (α = .76)?Overall, Data is of high quality when it reflects perceived reality. In our context, we measured managers’ perception of:
1. Overall Quality of Internet and Email data2. Overall Quality of Loyalty/Retention Data3. Overall Quality of Contact Management Data and 4. Overall Quality of CRM data capabilities
• 5-Point Scale• 5=Strongly Agree• 1=Strongly Disagree
Customer Performance Measured by Long-Term Customer Profitability
Customer Performance (α = .76): 1. Customer Retention on an annual basis, 2. Cross-Selling, and 3. ROI on a customer basis.
“To the best of your knowledge, please rate your business unit’s performance in the past 2-3 years relative to the competition” on a 1 = lower to 5 = higher scale.
• 5-Point Scale• 5=Higher• 1=Lower
Independent Variables Measured Percent of Time Data Types Collected
• Personalization/Tracking Data (α = .89): 1. Tracking marketing offers/messages
made to customers, 2. Tracking marketing offers/messages
responded to by customers3. Tracking method of contact for
marketing offer• Pyscho-Demographic Data (α = .75):
1. Lifestyle data2. Psychographics3. Demographics
• Customer Touchpoint Data (α = .76) : 1. Email2. Service 3. Internet4. Telephone
• RFM/Transactional Data (α = .83): 1. Last purchase date,2. Revenue by product,3. Total Revenue from Customers4. Length of time as customer
• Message/Offer Personalization Data (α = .82):1. Tailor marketing offers to
customers2. Tailor communications to
customers3. Tailors communications to
prospects
StdCoef
t-Value
H1 RFM/Transactional → CRM System Quality .110 1.60H2 Psycho-Demographic → CRM System Quality .248*** 3.50H3 Offer/Message
Personalization→ CRM System Quality .144* 1.87
H4 Personalization Tracking → CRM System Quality .303*** 4.22H5 Customer Touchpoints → CRM System Quality .139* 2.20H6 Customer Touchpoints → Customer Performance .293*** 3.96H7 RFM/Transactional → Psycho-Demographic .419*** 5.93H8a RFM/Transactional → Offer/Message
Personalization.140* 2.06
H8b RFM/Transactional → Personalization Tracking n.s. n.s.H9 RFM/Transactional → Customer Touchpoints .201** 2.60H10a Psycho-Demographic → Offer/Message
Personalization.275*** 3.67
H10b Psycho-Demographic → Personalization Tracking .230*** 3.29H11 Psycho-Demographic → Customer Touchpoints n.s. n.s.H12 Offer/Message
Personalization→ Personalization Tracking .452*** 7.06
H13 Personalization Tracking → Customer Touchpoints .165* 2.12H14 CRM System Quality → Customer Performance .211*** 3.96
SEM RESULTS, all paths except RFM/ Transactional to CRM System Quality (p < .055) significant at p <.05, one tailed
Model Fit: RMSEA=.01, GFI =.995
Implications
• Performance link from Data Quality • Firms need to be more vigilant than ever in
tracking transactional and psych-demographic data
• Personalization and Content data leads to increased customer touchpoint data
• Touchpoint data eventually leads to CRM system Quality, CRM Performance, completing the loop, validating the cycle
Contacts and Questions James PeltierUniversity of Wisconsin, [email protected]
Debra ZahayNorthern Illinois [email protected]
Anjala S. KrishenUniversity of Nevada, Las [email protected]
“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.