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BGS Customer Relationship Management
Chapter 5 CRM and Data Management Thomson Publishing 2007 All Rights Reserved
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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
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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
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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
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Customer Data Integration (CDI) Problem
Data capture and storage process variances Disparate databases Real-time customer interaction Data latency Lack of standards Data inaccuracy
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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
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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
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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
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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
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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
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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)
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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)
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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
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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
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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
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