m

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