This document provides an overview of database marketing and direct response marketing. It discusses how companies build customer databases and data warehouses, analyze customer data through techniques like data mining, RFM analysis and lifetime value analysis. It also explains how companies can use database insights to drive targeted, personalized communications and marketing programs like permission marketing and loyalty programs. Finally, it discusses customer relationship management and how direct response marketing utilizes techniques like direct mail, catalogs, and email to prospect and retain customers.

1. Prof. (Dr.) Kao Kveng Hong, PhD, D.Litt
11-1
18 Chapter-18
Database
and
Direct Response Marketing

2. Levi Strauss
• 1853, Bavarian immigrant
• Four principles
• Empathy
• Originality
• Integrity
• Courage
• Primary brands
• Levi’s, Dockers, Levi Strauss Signature
• Dominant brand  brand erosion
• Database marketing program
• 100,000 consumers - questionnaire
• Five target groups – promotions offered
• Online shoppers – fashion messages
18
11-2

3. Database and
Direct Response Marketing
Chapter Overview
• Database marketing
• Building a data warehouse
• Database coding and analysis
• Data mining
• Database-driven marketing
• Communications
• Programs
• Customer relationship management
• Direct response marketing
18
11-3

4. Developing Loyal Customers
The 3 R’s
• Recognition
• Relationship
• Rewards
11-4

5. Database Marketing
Database
Analytics
Direct Response
Marketing
Database
Identifying customersBuilding relationships
Data-Driven
Communications
Data-Driven
Programs
11-5

6. Tasks in Database Marketing
11-6
F I G U R E 1 1 . 2
• Building a data warehouse
• Database coding and analysis
• Data mining
• Data-driven marketing
communications
• Data-driven marketing programs

7. Building the Data
Warehouse
• Operational database
• Customer transactions
• Follows accounting rules
• Marketing database
• Current customer information
• Former customer information
• Prospect information
11-7

8. Marketing Data Warehouse
• Customer names and addresses
• E-mail addresses
• Record of visits to the firm’s Web site
• History of every purchase transaction
• History of customer interactions
• Inquiries
• Complaints
• Returns
11-8

9. Marketing Data Warehouse
(continued)
• Customer survey results
• Preferences and profiles supplied by the customer
• Response history from marketing campaigns
• Appended data
• Demographic and psychographic data
(Knowledge Base Marketing or Claritas)
• Geocoding
(CACI Coder Plus)
• Database coding through customer analyses
• Lifetime value
• Customer segment cluster
• RFM (recency, frequency, monetary) analysis
11-9

10. Trade Area Draw Analysis
Sample CACI Report for a Proposed Store Site
Based on a customer profile presented to CACI, 50% of the firm’s target
customers live within 2.32 miles of the proposed retail site. Of the 14,803
customers who live within 2.32 miles, only 985 (or 6.7%) are currently
customers of this firm.
11-10
Percentile
25%
# of Customers
492
Distance
0.99
# of Households
1,992
Penetration Rate
24.7%
50% 985 2.32 14,803 6.7%
75% 1,477 4.28 45,390 3.3%
90% 1,772 8.48 97,382 1.8%
99% 1,949 27.92 3,064,490 0.1%

11. • Personalized communications
• Marketing campaigns
• Common forms of coding
• Lifetime value analysis
• RFM analysis
Database Coding and Analysis
11-11

12. Represents the profit revenue of a customer
throughout the lifetime of the relationship
• Individual lifetime value
• Customer segment lifetime value
• Key figures
• Revenue and costs
• Retention rate
• Visits or purchases per time period
11-12
Lifetime Value Analysis

13. Lifetime Value for Lilly Fashions
F I G U R E 1 1 . 3
11-13
Year 1 Year 2 Year 3
Customers 3,200 1,600 960
Retention rate 50% 60% 70%
Visits/Year 4 5 6
Sales/Visit $78.00 $94.00 $110.00
Total Revenue $998,400 $752,000 $633,600
Variable costs % 60% 60% 60%
Variable costs $ $599,040 $451,200 $380,160
Acquisition costs ($72) $230,400
Database costs ($3) $9,600 $4,800 $2,880
Total costs $839,040 $456,000 $383,040
Gross Profit $159,360 $296,000 $250,560
Cumulative Gross Profit $159,360 $455,360 $705,920
Lifetime Value/customer $49.80 $142.30 $220.60

14. •Recency
•Frequency
•Monetary
RFM Analysis
Used to predict future customer behaviors.
11-14

15. • Recency
• Divide database into 5 equal parts based on date of last
purchase.
• Code 5 to 1 with 5 the last 20% to purchase.
• Frequency
• Divide into 5 equal parts.
• Code 5 to 1 with 5 being the most frequent
• Monetary
• Divide into 5 equal parts
• Code 5 to 1 with 5 being the highest expenditures
• Codes range from 555 to 111.
RFM Analysis Procedure
11-15

16. • Code of 235
• 2 indicates has not made a recent purchase
• 3 indicates has made an average number of purchases
• 5 indicates the total monetary value of the purchases
were among the top 20% of the firm’s customers
• Recency has most impact on future purchases
• Frequency has second most impact
• Monetary has least impact
RFM Analysis Results
11-16

17. Data Mining
• Building profiles of customer groups
• Preparing models that predict future
purchase behavior
• Examples
• First Horizon – profiles best prospects
• American Eagle – price markdowns
• Goody’s – shopper baskets
• Staples – profiles of best customers
11-17

18. Executives from
Unica, a maker of
marketing automation
software, discuss the
importance and use of
data mining and
management.
Click picture to view video.
11-18

19. Data Mining and Data Coding
• Marketing communications
• Marketing programs
Drives 
11-19

20. Why the Internet is Important in Customer Communications
• Low cost
• Available 24/7.
• Metric analysis
• If the message was read
• Time it was read
• How much time was spent
• Customers access to additional information
• Build a bond with customers.
11-20
F I G U R E 1 1 . 4

21. Why build a data warehouse?
Why code data?
Why mine the data?
11-21

22. Database-Driven Communications
• Identification codes
• Customer IDs/passwords
• Personalized greetings
• After-sale communications
• Customer profile information
• In-bound telemarketing
• Trawling
11-22

23. F I G U R E 1 1 . 5
Segmenting Customers by Lifetime Value
Gold
Silver
Bronze
Mass Customers
Losers
11-23
LifetimeValue

24. Database-Driven
Marketing Programs
• Permission marketing
• Frequency/loyalty programs
• Customer relationship
management
11-24

25. • Obtain permission
• Offer a curriculum over time
• Reinforce incentives to continue the relationship
• Increase level of permission
• Leverage the permission to benefit both parties
Source: Based on Seth Godin, “Permission Marketing: The Way to Make Advertising WorkAgain, Direct
Marketing, (May 1999), Vol. 62, No. 1, pp. 41-43.
Steps in Building a Permission Marketing Program
11-25
F I G U R E 1 1 . 6

26. Successful Permission Marketing
• Ensure recipients have granted permission
• Make e-mails relevant
• Customize program by tracking member activity
Empowerment
Reciprocity
11-26

27. Reasons Consumers Opt into an E-mail Permission Program
F I G U R E 1 1 . 7
24%
Source: Based on Joseph Gatt, “Most Consumers Have Reached Permission E-mail Threshold,” Direct
Marketing (December 2003), pp. 1-2.
11-27
40%
38%
37%
41%
0% 5% 10% 15% 20% 25% 30%
Percent of Respondents
35% 40% 45%
Friend recommended
Already customer
E-mail required to
access content
Found site randomly
Sweepstakes or
chance to win

28. Reasons Customers Remain Loyal to a Permissions Relationship
F I G U R E 1 1 . 8
27%
Source: Based on Joseph Gatt, “Most Consumers Have Reached Permission E-mail Threshold,” Direct
Marketing (December 2003), pp. 1-2.
11-28
34%
34%
35%
36%
0% 5% 10% 15% 20% 25%
Percent of Respondents
30% 35% 40%
Entertaining
Price bargains
Contests and
sweepstakes
Account status updates
Interesting content

29. Frequency Program Objectives
• Maintain sales, margins, or profits
• Increase loyalty of existing customers
• Induce cross-selling to existing customers
• Differentiate a parity brand
• Preempt the entry of a new brand
• Preempt or match a competitor’s program
11-29
Source: Grahame R. Dowling and Mark Uncles, “Do Customer Loyalty Programs Really Work?” Sloan
Management Review, (Summer 1997), Vol. 38, No. 4, pp. 71-82.
F I G U R E 1 1 . 9

30. Goals of Frequency Programs
•
•
•
Develop customer loyalty
Matching or preempting the competition
Target higher income households
• Incomes of $125,000 plus - 92% enrolled
• Incomes below $125,000 – 51% enrolled
11-30

31. Principles
Frequency Programs
• Design the program to enhance the value of the product.
• Calculate the full cost of the program.
• Design a program that maximizes the customer’s motivation
to make the next purchase.
Sent letter to 4,000 offering $5 discount on dinner.
• Average visits increased
• From 25 to 42 during promotion
• From 25 to 29 after promotion
• Card holders visits increased
• Incremental sales increased
•$17,100 during promotion
•$4,700 after promotion
11-31

32. Customer Relationship
Management
• Database technology
• Customize products
• Customize communications
• Many CRM programs failed
• Built on two primary metrics
• Lifetime value
• Share of customer
11-32

33. Customer Relationship Management
Steps to Develop
• Identify the company’s customers
• Differentiate customers in terms of
needs and value
• Lifetime value
• Share of customer
• Interact with customers
• Improve cost efficiency
• Enhance effectiveness of interaction
• Customize goods or services
11-33

34. Share of a Customer
• Company A - $ 27,000
• Company B - $ 18,000
• Company C - $ 15,000
• Total expenditures -$60,000.
• Share of customer
• Company A  45%
• Company B  30%
• Company C  25%
11-34

35. Customer Relationship Management
Reasons for Failure
• Implemented before a solid customer strategy is created
• Rolling out a CRM program before changing the organization to
match the CRM program
• Becoming technology driven rather than customer driven
• Customers feel like they are being stalked instead of being wooed
11-35

36. Direct Response Marketing
• Direct Marketing Association
• Prospecting 60%
• Customer retention  40%
• Dell Computers
• Catalog
• TV and radio ads
• FSI ads
• Web site
11-36

37. Methods of Direct Marketing
F I G U R E 1 1 . 1 0
11-37
77%
73%
0% 10% 20% 30% 40% 50% 60%
% of Companies Using Particular DMMethodology
70% 80% 90%
Source: Based on Richard H. Levy, “Prospects Look Good,” Direct, Vol. 16 (December 1, 2004), pp. 1-5.
Direct mail to customers
Direct mail to prospects
Statement stuffers
16%
Catalogs 24%
Direct response-promotions 21%
Direct response-radio 10%
Direct response-TV
Direct response-Internet
8% 29%
Search engine marketing 22%
Search engine optimization
E-mail to customers
17% 55%
E-mail to prospects 46%
Inbound telemarketing 16%
Outbound telemarketing 24%

38. Direct Mail
• Most common form of direct marketing
• Types of lists
• Response list
• Compiled list
• Advantages
• Target mailings (consumer, b-to-b)
• Measurable
• Driver of online sales
• Disadvantages
• Clutter
• Costs
• Digital direct-to-press
Copyright © 2010 Pearson Education, Inc. publishing as Prentice Hall 11-38

39. Catalogs
• Long-term impact
• Low-pressure sales tactics
• First stage in buying cycle
• Database
• Specialty catalogs
• Business-to-business
11-39

40. Direct Response Media
• Television
• Radio
• Magazines
• Newspapers
11-40

41. Internet
• Direct response to ads
• Cost-effective
• Builds relationships
• Personalization of communication
• Customization of offer
• Search engine ads
11-41

42. Alternative Media
•
•
•
• Package insert programs (PIPs)
Ride-a-longs
Statement stuffers
Card packs
11-42

43. Telemarketing
• Inbound telemarketing
• Cross-selling
• Outbound telemarketing
• Cold calling
• Database
• Prospects
11-43

44. International Implications
• Differences in technology
• Laws and regulations
• Local customs
• Infrastructure
11-44