bgs customer relationship management chapter 5 crm and data management chapter 5 crm and data...
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BGSCustomer Relationship
Management
BGSCustomer Relationship
ManagementChapter 5
CRM and Data Management
Chapter 5CRM and Data Management
Thomson Publishing 2007 All Rights Reserved
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
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
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
Customer Data Integration (CDI) Problem
• Data capture and storage process variances
• Disparate databases• Real-time customer interaction• Data latency• Lack of standards• Data inaccuracy
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
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
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
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
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
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)
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
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
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
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
Consumer Data Rule Construction Consumer Data Rule Construction
DataElement
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
N/A
$120K
37
Other
N/A
2(4-8 yrs)
N/A
37
Unskilled
Yes
1 @ 4 yrs,1 @ 3yrs
X
X
X
X
1 @ 4 yrs,1 @ 3yrs
$65K
37
Professional
Yes
2 (4-8 yrs)
DataElement
Industry Researc
h
Web Sites
Sales Personnel
Trade Publicatio
ns
Data Used
Annual Revenue
Plant Square Footage
$10 MM
4,000
$11-13 MM
5,500
$10 MM
3,500 –4,000
N/A
3,800 - 4,200
$10 MM
4,000
Business Data Rule Construction Business Data Rule Construction
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
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
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
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
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
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
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
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
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
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
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)
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
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
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