1. BGS Customer Relationship Management
Chapter 5
CRM and Data Management
Thomson Publishing 2007 All Rights Reserved

2. Introduction Data management is a key CRM enabler
Data integration is a series of steps
Critical path to create a single accurate view of the customer
Manage the customer interaction

3. Managing Customer Interactions
Customer perceptions driven by interaction experiences
Digital age has enabled the customer to expect more
Improper management undermines relationship between the organization and the customer
Proper management requires a centric view of the customer

4. Managing Customer Interactions
Successful management allows organizations to
Create and sustain loyalty
Differentiate itself from competition
Grow relationships
Increase favorable customer word-of-mouth
Attaining a centric view of the customer requires data integration across the enterprise

5. Customer Data Integration (CDI) Problem
Data capture and storage process variances
Disparate databases
Real-time customer interaction
Data latency
Lack of standards
Data inaccuracy

6. CDI Definition and Requirements
CDI: A data management process where all customer and prospect data is consolidated to create a single accurate view of the customer
All organization points of customer interaction must have access to an accurate and current customer centric view
Data to be distributed accurately to points of interaction in a timely manner

7. CDI Definition and Requirements
CDI requires:
Enabling technology to manage initial and ongoing data integration efforts
Customer linkage capability
Organization-wide adoption of technology and customer linkage

8. House-Holding Concepts
Individuals living at the same address and having the same last name are considered to be in the same household
House-holding allows an organization to view a customer at several levels
Individual level
Household level
Mechanics for creating households are similar for consumers and businesses

9. House-Holding Concepts
Consumer house-holding considerations
Children have temporary address while attending college
People have secondary residences (e.g., snowbirds)
Changing norms (e.g., home office, nontraditional family)
Ethnic names

10. House-Holding Concepts
Business house-holding is more complex
Different addresses and different names but same organization
People within organization are new, promoted, transferred, and leave the organization
Virtual offices

11. CDI Steps Identify Touch Points
Any area that an interaction can occur between an organization and a customer or prospect
Interaction medium may vary
Human to human (e.g., POS)
Human to human with technology as enabler (e.g., customer communicating via Web chat session)
Human to technology (e.g., customer interfacing with computer telephony)
Technology to technology (e.g., Web transaction)

12. CDI Steps Identify Touch Points
Position in value chain can present challenges
Mfg. not having access to retail transaction
Retailer not having access to mfg. warranty transaction
Outsourced Web hosting and data capture quality issues
Retailer not having access to subcontractors for delivery and customer service
Organizations not capturing informal data from outsourced telemarketing firm
B2C business interface examples – POS, order processing, customer service, distribution, repair/maintenance, PR, survey, promotion response, unsolicited communication from consumer, noncountry of origin

13. CDI Steps Identify Touch Points
B2B business interface examples – procurement, accounts payable and receivable, sales, technical support, order processing, customer service, distribution, repair/maintenance, PR, survey, promotion response, investing community, value chain partners, unsolicited communication

14. CDI Steps Define How Data is Collected
Technology
Web forms, Web free form text, computer telephony, kiosks, self-service POS, fax
Human
Verbal, written, observation

15. CDI Steps Establish Data Collection Rules
Identify data variables to be collected (e.g., demographic, psychographic, geographic, behavioral, transaction)
Define priority scheme for data variable capture based on source

16. Consumer Data Rule Construction
Element
Touch Point A
Touch Point B
Touch Point C
Touch Point D
Data Used
Income
Age
Occupation
Homeowner
Children
$65K-$70K
35-40
Professional
N/A
$120K 37
Other
2(4-8 yrs)
Unskilled
Yes
4 yrs,
3yrs X
$65K
2 (4-8 yrs) 13

17. Business Data Rule Construction
Element
Industry Research
Web Sites
Sales Personnel
Trade Publications
Data Used
Annual Revenue
Plant Square Footage
$10 MM
4,000
$11-13 MM
5,500
3,500 –4,000
N/A
3, ,200 13

18. CDI Steps Manage Input Process after Collection
Timing
Process step dependency
Data flow and scheduling
Security
Corrupted or lost
Unauthorized use or access
Inconsistency worse than inaccuracy

19. CDI Steps Place Data in Common Formats
Provides for:
Efficient data hygiene processing
Enhances matching logic for postal, linkage, and enhancement processing
Is required by some software processing
May not always be necessary depending on software capability in handling dynamic processing

20. CDI Steps Split Linkage Data
Split data into two categories: nonlinkage and linkage
Nonlinkage data can contain many variables and is not needed for data hygiene, postal, matching, and secondary data enhancement processing
Linkage data is required for the data hygiene, postal, matching, and enhancement steps
Splitting the data increases processing efficiency and reduces data management efforts

21. CDI Steps Standardize and Correct Linkage Data
Ensure address variables from all touch points are in a standard format for an optimal address correction process
Utilize commercial software to correct address components
Outsource or acquire software and process internally
Process in real-time or batch mode

22. CDI Steps Postal Processing
Varies by country
Mandatory for certain types of mailing in United States.
Usually an outsourced function
Required to ensure most current addresses are on file for customers and prospects, which supports the relationship build and sustain strategy

23. CDI Steps Postal Processing
18-20 percent of the population change addresses annually
LACS – Locatable Address Conversion System
NDI – National Deliverability Index
DSF2 – Delivery Sequence File Second Generation

24. CDI Steps Customer Linkage Identification
Sometimes referred to as deduplication or merge/purge
Objective – identify each appearance of an individual or business and assign an identifier to each linkage record

25. CDI Steps Customer Linkage Identification
Record linkage categories include Manual, Deterministic, or Probabilistic
Manual is not feasible for large files
With deterministic, individuals or companies are said to be the same if there is a match on certain variables
Probabilistic uses weights and probability algorithms to determine if two or more records are the same person or company

26. CDI Steps Customer Linkage Identification
Phonemic name compression
Customer linkage approaches
Tight versus loose matching
Industry nuances
Some industries prone to less accuracy
Organizational structure influences business rule definitions
Changing linkage rules require extensive rework to database contents

27. CDI Steps Data Enhancement
Nonprimary sources of data
Highly dependent upon linkage capability
Can be costly
Source credibility must be determined
Determine if the process will be outsourced

28. CDI Steps Data Suppression
Purpose
Avoid contact with nonprofitable customer
Adhere to customer request for no interaction
Legal and ethical conformance (e.g., deceased, young children, prisons, military, fraud detection)
Optimize marketing investments
Perform using internal information as basis for suppression (e.g., opt-out, fraud detection, avoid nonprofitable customers)
Use external suppression files (Table 5.10)

29. CDI Steps Consolidate Linkage and Non-Linkage Data
Match linkage to non-linkage data on sequence numbers
Consolidate and aggregate appropriate variables
Prepare data for update process to respective Database entities
Data is not actionable knowledge

30. CDI Ancillary Benefits
Fraud detection
Data anomalies
Identify data collection areas that need improvement or that present new opportunities
Identify business process areas that may need improvement, are unnecessary, or that are missing

31. Summary CDI is a CRM key success factor
CDI is dynamic due to technology changes, business objective changes, new best
CDI can vary by industry or country
CDI has ancillary benefits