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data warehouse— a large reservoir of detailed and summary data that describes the firm and its activities, organized by the various business units in a way to facilitate easy retrieval of information describing the firm’s activitiesdata— facts and figures that are difficult to use because of their volume. information— meaningful compilations and summaries of data that tell the user something that he or she did not already knowCRM architecture— facilitates the gathering of data, storing it, transforming it into information, and presenting the information to users.
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CHAPTER 3
INFORMATION TECHNOLOGY AND COLLECTING CUSTOMER DATA
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INFORMATION TECHNOLOGY AND CRM
data warehouse— a large reservoir of detailed and summary data that describes the firm and its activities, organized by the various business units in a way to facilitate easy retrieval of information describing the firm’s activities
data— facts and figures that are difficult to use because of their volume.
information— meaningful compilations and summaries of data that tell the user something that he or she did not already know
CRM architecture— facilitates the gathering of data, storing it, transforming it into information, and presenting the information to users.
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EXHIBIT 3.1 A BASIC CRM MODEL
Data sources
Data warehouse
system
Information users
Data gathering system
Information delivery
system
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A Basic CRM Model Data Sources
internal—business units, such as a manufacturing, finance , or sales
external—organizations and individuals outside the firm. Data Acquisition
computer-readable formats acquired from internal sources, data entry operators, or compatibility with touch points for external sources
Data Storage record file database data mart—a subset of the data warehouse that contains
data relating to a portion of the firm’s transactions.
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A Basic CRM Model Data Management
database management system (DBMS)— software that maintains the data and makes it available for use
data dictionary—a detailed description of each data element
Exhibit 3.2: A Database Management System Model Management and Control
data security—achieved by use of passwords, supplemented with directories that specify the operations
Exhibit 3.3: A Data Dictionary Entry Information Delivery
query responses—answers to user questions that are displayed on the users’ workstations
Information Users CRM user interface—designed to facilitate navigation
through the data and to enable the users to easily make queries
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EXHIBIT 3.2 A DATABASE MANAGEMENT SYSTEM MODEL
Information
requests
Data description language processor
Database description (schema)
Database manager
Displayed informatio
n
Printed information
Database
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EXHIBIT 3.3 A DATA DICTIONARY ENTRY
C : Documents and Settings \ CRMDW. Mdb Thrusday, May15, 2002
Table : tblCustomer Page1
PROPERTIES
Data Created: 5/15/02 10:10:10 AM GUID: Long binary data
Last Updated: 5/15/02 2:25:30PM NameMap: Long binary data
OrderByOn: False Orientation: 0
RecordCount: 0 Updatable: True
Columns
Name Type Size
Customer ID Text 8
AllowZeroLength: False
Attributes: Variable Length
Collating Order: General
ColumnHidden: False
ColumnOrder: Default
ColumnWidth: Default
Data Updatable: False
Description: Unique indentification number for each
customer
DisplayControl: Text Box
GUID: Long binary data
Ordinal Position: 1
Required: True
Source Field: Customer ID
Source Table: tblCustomer
UnicodeCompression: True
GROUP PERMISSIONS
Admins Delete, Read Permissions, Set Permissions, Change Owner, Read Definition,
Write Definition, Read Data, Insert Data, Update Data, Delete Data
Users Delete, Read Permissions, Set Permissions, Change Owner, Read Definition,
Write Definition, Read Data, Insert Data, Update Data, Delete Data
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COMPUTER ARTHITECTURES
client/server— the stored data and functions that are performed on the data are allocated to the central server and to the user, called the client Exhibit 3.4: Tiered Client/Server Configurations Three commodities—(1) control over the user
interface, (2) the location of the software that performs the user’s functions, and (3) the location of the data—reside at the client level
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EXHIBIT 3.4 CLIENT/SERVER ARCHITECTURES
Client
Client
Client
Server
Client
Client
Client
Server Server Server
A. Two-tiered architecture B. Multi-tiered architecture
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DATA INPUT
Contact Points touch point—any transaction or customer interaction
with the organization Point of Sale Input
POS terminals—scan product data from bar codes and obtain customer data from credit cards, checks, or store identification cards
Keyed and Scanned Data Input keyed input—when POS terminals and EDI cannot be
used, the data most likely will have to be keyed into workstations by data entry operators
scanned input—when data can be optically scanned, i.e. credit card invoices and airline tickets
Internet Input Web-based systems—allow tracking of customer
information for search and purchasing behavior
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DATA STORAGE
main memory secondary storage direct access storage storage area network (SAN)— allows
business units throughout the organization to store data on different servers.
storage resource management (SRM) software— allocates storage in the most efficient way by locating unused storage and allocating it where it can best be used
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DATABASE STRUCTURES
database design— arrange the data so that it can easily be retrieved
hierarchical and network— the first structures, required that special physical links be built into the records to integrate data from multiple files
relational— structure that makes use of data elements already in the data tables to integrate the contents of multiple tables
Exhibit 3.5: Data Attributes Enable Relations
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EX 3.5 DATA ATTRIBUTES ENABLE RELATIONS
Salesperson Number
Sales Region Number
Salesperson Name
123 1 Carolyn Wright
150 1 Ronald Hudson
188 1 Wally Collins
198 1 Sandy Lee
205 2 Richard Glenn
220 2 Vincent Garza
235 2 Ray Cox
A. Salesperson table
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EX 3.5 DATA ATTRIBUTES ENABLE RELATIONS (Cont.)
Customer Number Customer NameSalesperson
NumberYear-to-Date Sales
30788 Austin Auto 123 2,500
30381 Jitney Jungle 235 16,283
30885 Central Repair 123 432,850
31246 Ace Body Shop 198 325
31980 Armadillo Imports 123 37,098
32659 Southern Motors 123 2,375
32776 Bonham Bearings 150 16,201
32829 Wrecking Bar 188 88,567
35294 Continental Cars 150 14,219
36291 Cowboy Trailers 220 59,263
41283 Nomad Motors 205 12,504
B. Customer table
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Multidimensional Databases
data dimension— an array of data in a particular order one-dimension analysis two-dimension analysis—for example, customer sales by
month (customer and time) multidimensional databases (MDDBs)— software develope
d to overcome the decreased effectiveness of relational database structures as the number of dimensions increases
hypercube— data arrayed by three or more dimensions Exhibit 3.6: Data Stored in Hypercubes Exhibit 3.7: More than Three Data Dimensions
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EXHIBIT 3.6 DATA STORED IN HYPERCUBES
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EXHIBIT 3.7 VISUALIZING MORE THAN THREE DATA DIMENSIONS
Salesperson
Sales branch
Sales region
All regions
Salesperson
Customer
Customer territory
Customer category
All customers
Customer
Product
Product line
All products
Product Time
Time
Quarter
Hour
Day
Month
Year
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DATA ANALYSIS AND INFORMATION DELIVERY
analysis tools—include reports, database queries, and mathematical modeling, or on-line analytical processing (OLAP)
Reports and Database Queries repetitive report (or periodic report)—prepared
automatically according to a schedule, such as monthly, without requiring requests by users
special report—prepared when a special information need arises, such as a response to a database or data warehouse query
Exhibit 3.8: A Report or Query Response Showing Two Dimensions of Data
drill down—successively increasing the degree of detail, or granularity, of the data
Exhibit 3.9: Drilling Down to Finer Granularity
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EXHIBIT 3.8 A REPORT OR QUERY RESPONSE SHOWING TWO DIMENSIONS OF DATA
Sales RegionNumber
SalespersonNumber
SalespersonName
Y-T-D Sales
1 123 Carolyn Wright 474,8231 150 Ronald Hudson 30,4201 188 Wally Collins 88,5671 198 Sandy Lee 325
Region 1 Total 594,135
2 205 Richard Glenn 12,5042 220 Vincent Garza 59,2632 235 Ray Cox 16,283
Region 2 Total 88,050
Company Total 682,185
Customer Sales by Salesperson Report
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EXHIBIT 3.9 DRILLING DOWN TO FINER GRANULARITYProduct Sales in Dollars May 2003
Product Line Quota Actual Variance%
CD/tape/radio 200,000 182,305 -8.8
TV 750,000 831,200 +10.8
Computer 375,000 402,117 +7.2
Total 1,325,000 1,415,622 +6.8
A. Product Sales by product line
CD/Tape/Radio Sales in Dollars May 2003
Product Quota Actual Variance%
Patriot 150,000 104,900 -30.1
Series30 30,000 31,200 +4.0
Series50 20,000 46,205 +231.0
Total 200,000 182,305 -8.8
B. CD/Tape/Radio sales
Patriot Model CD/Tape/Radio Sales by Retail Store
May2003
Retail Store Quota Actual Variance%
Phoenix 45,000 20,010 -55.5
Santa Fe 50,000 25,877 -48.2
Rapid City 32,500 33,338 +2.6
Boise 22,500 25,675 +14.1
Total 150,000 104,900 -30.1
C.Patriot model CD/Tape/Radio sales by retail store
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DATA ANALYSIS AND INFORMATION DELIVERY
Mathematical Modeling constructed in a software form and uses data and
users’ instructions to project what might happen in the future
On-line Analytical Processing (OLAP) an approach to quickly conduct analysis of data in
a data warehouse where the user is on-line with the system
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DATA ANALYSIS AND INFORMATION DELIVERY
Data Mining how the user extracts previously unknown informatio
n from the large reservoir of the data warehouse, similar to the way that miners extract gold, coal, diamonds, and so on from the earth.
verification mode— to believe that the warehouse contains data in certain forms or patterns and conducts repetitive queries to support this hypothesis.
knowledge discovery— the user lets the system determine the path to follow in conducting the analysis
Exhibit 3.10: Hypothesis Verification and Knowledge Discovery by Successive Queries
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EXHIBIT 3.10 HYPOTHESIS VERIFICATION AND KNOWLEDGE DISCOVERY BY SUCCESSIVE QUERIES
Sale Date Customer Product
02/12/03 Ed Flynn TV
02/15/03 Adele Rice Computer
02/18/03 Ric Knowles TV
03/01/03 Ed Flynn Computer
03/19/03 Angela Forest TV
03/30/03 Robin Lin Computer
04/05/03 Robin Lin CD/Tape/Radio
04/11/03 Ed Flynn CD/Tape/Radio
04/21/03 Adele Rice TV
05/16/03 Richard Rodriguez TV
05/17/03 Robin Lin TV
05/26/03 Joe Wardlaw Computer
05/29/03 Angela Forest CD/Tape/Radio
05/29/03 Richard Rodriguez CD/Tape/Radio
05/30/03 Cynthia Garfield Computer
A. Query 1 for transaction data for the Rapid
City store February through May
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EXHIBIT 3.10 HYPOTHESIS VERIFICATION AND KNOWLEDGE DISCOVERY BY SUCCESSIVE QUERIES (Cont.)
Product Sales Sequence Customers
TV,Computer,CD/Tape/Radio Ed Flynn
Computer,CD/Tape/Radio,TV Robin Lin
Computer,TV Adele Rice
TV,CD/Tape/Radio Angela Forest
TV,CD/Tape/Radio Richard Rodriguez
Computer Joe Wardlaw, Cynthia Garfield
TV Ric Knowles
B. Query2 for product sales sequences
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EXHIBIT 3.10 HYPOTHESIS VERIFICATION AND KNOWLEDGE DISCOVERY BY SUCCESSIVE QUERIES (Cont.)
Product Sales Sequence Customers Support
Factor
TV,Computer Flynn 0.125
TV,CD/Tape/Radio Flynn,Forest,Rodriguez 0.375
Computer,CD/Tape/Radio Flynn,Lin 0.250
Computer,TV Lin,Rice, 0.250
TV,Computer,CD/Tape/Radio Flynn 0.125
Computer,CD/Tape/Radio,TV Lin 0.125
C. Query 3 for support factors for product sales sequences
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CLOSED-LOOP MARKETING
CRM system loop (1) data
Data gathering Data storage
(2) information (CRM system) Information delivery
(3) strategy (managers) Exhibit 3.11: CRM-Based Marketing
Strategies Close the Loop
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EXHIBIT 3.11 CRM-BASED MARKETING STRAGEGIES CLOSE THE LOOP
Customers Data CRM system Information Managers
Marketing strategy
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COLLECTING CUSTOMER DATA
Internal Data Sources transaction processing systems—the multiple syste
ms used by organizations to process their various transactions with customers, suppliers, employees, etc.
Exhibit 3.12: Gathering Data From Order-Processing Systems
External Data Sources external sources—government, suppliers within th
e supply chain as well as those that provide syndicated data, and marketing intelligence about competitive actions are examples
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EX 3.12 GATHERING DATA FROM ORDER-PROCESSING SYSTEMS
Customers
1
Orderentry
system2
Inventorysystem
3
Billing system
4
Accountsreceivable
system
Accounts receivablemaster file
Customer master file
Inventorymaster file
Sales orders
Rejected sales order noticesCustomer
statements
Accounts receivabledata
Customerinvoices
Billed salesorder file
Approved sales order file
Filled sales orders file
Product dataCustomer
data
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What is the difference between a data warehouse and a database?
A data warehouse is a large reservoir of detailed and summary data that describes the firm and its activities, organized by the various business units in a way to facilitate easy retrieval of information describing the firm’s activities. A database is an accumulation of computer-based data that is arranged in a format to facilitate retrieval. A data mart is a subset of the data warehouse that contains data relating to a portion of the firm’s transactions.
