UCEA Mini-Workshop on
Database Marketing
Arthur Middleton Hughes
Vice President / Solutions Architect
KnowledgeBase Marketing
Hyatt Fisherman’s Wharf
San Francisco
Feb 14, 2002
What KnowledgeBase Marketing
Does
Compared with newcomers,
Long term customers:

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Buy more per year
Buy higher priced options
Buy more often
Are less price sensitive
Are less costly to serve
Are more loyal
Have a higher lifetime value
Retention is the way to
measure loyalty
90%
80%
70%
Percentage
Retained
from
Previous
Year
60%
50%
40%
30%
20%
10%
0%
1
2
3
4
Years as a customer
5
Retention pays better than
acquisition
Annual Profit
$48
$60
$40
$20
$0
($20)
($40)
($60)
($80)
($62)
New Customer
3rd Year
Customer
What proves that relationship
building works?


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

Manufacturer of building products
Catalog sent to 45,000 contractors
Previous policy: wait for the orders
Test: pick 1,200 customers, split into test of
600 and control of 600
Two person pilot program build relationship
with test customers to see the results
Credit: Hunter Business Direct
What did they offer?

Follow up on bids and quotes
Schedule product training
Make aware of pricing specials
Ask about customer needs
Product comparison information
New Product information

They did not offer discounts

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Improvement in Response rate
76%
76%
76%
75%
Percent 75%
who
74%
purchased 74%
in 6 months 73%
73%
72%
72%
73%
1
2
Control vs Test Group
Change in the number of
orders
112%
120%
82%
100%
Change in
number of
orders
80%
60%
40%
20%
0%
1
2
Control vs Test Groups
Change in the Average Order
Size
114%
120%
86%
100%
80%
Change in
average 60%
order size
40%
20%
0%
1
2
Control vs Test Group
Total revenue gain: $2.6
million dollars
127%
140%
120%
100%
Change in
total
revenue
70%
80%
60%
40%
20%
0%
1
2
Control vs Test Group
This stuff works!

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Building a relationship with
customers can be highly profitable
Using a database to recreate the
old family grocer is a winning
strategy
Relationship marketing is the way
to go
Why we need Lifetime Value
Analysis


We need to know the value of our
customers, so as to properly target our
sales and retention efforts
We need to discriminate among our
customers to acquire and retain the
best
Lifetime Value Analysis
Goal: Determine...

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where to put your retention dollars
the value of each retention strategy
where to put your acquisition
dollars
how much to spend on acquisition
What is lifetime value?

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Net present value of the profit to be
realized on the average new customer
during a given number of years.
Lifetime value is “Good Will.”
To compute it, you must be able to
track customers from year to year.
Main use: To evaluate strategy.
Retention Rate
Students
Courses/Year
Cost per course
Revenue
Year 1
Year 2
Year 3
40%
45%
50%
10,000
4,000
1,800
2.8
3.0
3.2
$605
$605
$605
$16,940,000 $7,260,000 $3,484,800
Costs Percent
Costs
Retention Costs $12
Total Costs
80%
77%
75%
$13,552,000 $5,590,200 $2,613,600
$120,000
$48,000
$21,600
$13,672,000 $5,638,200 $2,635,200
Profit
Discount Rate
NPV Profit
Cumulative NPV
Lifetime Value
$3,268,000 $1,621,800
$849,600
1.00
1.17
1.36
$3,268,000 $1,386,154
$624,706
$3,268,000 $4,654,154 $5,278,860
$326.80
$465.42
$527.89
Discount Rate Basic Formula
Market Rate of Interest...6%
Assume Risk 1.2 first year, 1.1 afterwards
Years = n Interest = i
Formula: D = (1 + I * risk)n
Calculation of rate after 2 years:
 D = (1.06 * 1.1)2 = 1.36
Convert to Annual
Annual Rate = (Repurchase rate) (1/years)
77% repurchase after 11 years

Annual Rate = (.77)(1/11) = 98%
45% repurchase after 4 years = 82%
99% per week = 59.2% per year
Annual = (.99) (1/(1/52))

Annual Rate = 59.2%
New Retention Strategies
Build a database linked to the website
Web registration
Frequent personal communications
Web site cost $30 per student per year
Communications extra cost $18 per
student per year
Retention Rate
Students
Courses/Year
Revenue per Course
Revenue
Year 1
Year 2
Year 3
45%
50%
55%
10,000
4,500
2,250
3.0
3.5
4.0
$605
$605
$605
$18,150,000 $9,528,750 $5,445,000
Costs Percent
Costs
Web Costs $30
Retention Costs $30
Total Costs
75%
72%
70%
$13,612,500 $6,860,700 $3,811,500
$300,000
$135,000
$67,500
$300,000
$135,000
$67,500
$14,212,500 $7,130,700 $3,946,500
Profit
Discount Rate
NPV Profit
Cumulative NPV
Lifetime Value
$3,937,500 $2,398,050 $1,498,500
1.00
1.17
1.36
$3,937,500 $2,049,615 $1,101,838
$3,937,500 $5,987,115 $7,088,954
$393.75
$598.71
$708.90
Effect of adoption of new
strategies
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$1.8 million in the third year
Profit, after all expenses paid
New LTV
Old LTV
Change
Times 10,000
Year 1
$393.75
$326.80
$66.95
$669,500
Year 2
$598.71
$465.42
$133.30
$1,332,962
Year 3
$708.90
$527.89
$181.01
$1,810,094
What is the proper
computation period?
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Which is the correct lifetime value? 1,
2, 3, 4, 5 or more years?
They are all correct. Which you use
depends on your product or service.
Long lifetimes: banks, insurance,
utilities.
Short lifetimes: continuing education.
Five Ways to Boost LTV with
DB Strategies
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Increase the retention rate
Increase the referral rate
Increase the spending rate
Decrease the direct costs
Decrease the marketing costs
How to use lifetime value
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Compute a base lifetime value
Dream up a new strategy
Estimate the benefits and costs
Determine whether your new lifetime
value goes up or goes down
Don’t undertake any new strategy until
you can prove it will be successful
Find LTV of Customer
Segments
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Many UCEA customers are quite
different in their purchase patterns
Create actionable segments and
determine the value of each
Use the results to focus your retention
programs and acquisition programs on
the most profitable segments
Dividing Customers into Three
Segments

Develop a different strategy for each
segment
Quantity
Degree Candidates
4,000
Retirees
2,000
Job Training
4,000
Total
10,000
LTV
$1,126
$329
$482
Total
$4,504,000
$658,000
$1,928,000
$7,090,000
Different marketing strategies
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Job training: market to companies
Degree Candidates: market both to
companies and individuals
Senior Citizens: market to individuals
Using lifetime value to get
budget approval
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Database marketing budgets are usually
carved from somewhere else
You have to prove that you will make better
use of the funds than the others
Lifetime value can supply testable numbers
that CFO’s can understand
Base your budget on solid numbers backed up
by valid tests
What your new budget will
buy
New LTV
Old LTV
Change
Times 10,000
Year 1
Year 2
Year 3
$393.75
$598.71
$708.90
$326.80
$465.42
$527.89
$66.95
$133.30
$181.01
$669,500 $1,332,962 $1,810,094
Retention Rate
Students
Courses/Year
Revenue per Course
Revenue
Year 1
Year 2
Year 3
45%
50%
55%
10,000
4,500
2,250
3.0
3.5
4.0
$605
$605
$605
$18,150,000 $9,528,750 $5,445,000
Costs Percent
Costs
Web Costs $30
Retention Costs $30
Total Costs
75%
72%
70%
$13,612,500 $6,860,700 $3,811,500
$300,000
$135,000
$67,500
$300,000
$135,000
$67,500
$14,212,500 $7,130,700 $3,946,500
Profit
Discount Rate
NPV Profit
Cumulative NPV
Lifetime Value
$3,937,500 $2,398,050 $1,498,500
1.00
1.17
1.36
$3,937,500 $2,049,615 $1,101,838
$3,937,500 $5,987,115 $7,088,954
$393.75
$598.71
$708.90
Using lifetime value to get
budget approval
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Database marketing budgets are usually
carved from somewhere else
You have to prove that you will make better
use of the funds than the others
Lifetime value can supply testable numbers
that CFO’s can understand
Base your budget on solid numbers backed
up by valid tests
Recency, Frequency, Monetary
Analysis
How to attract and hold
relationship buyers
Forget price. Think and talk about
quality and service.
Build a relationship with the buyer
Add value to product and relationship
Find way for buyer to build equity
Make it expensive to switch
How to identify
responsive customers
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Some customers respond, some don’t
How can you predict behavior?
Best method: look at past behavior
Behavioral indicators:
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Recent purchasers
Frequent purchasers
Large spenders
Responsive customers may not be the
most profitable
Profitable
Customers
Responsive
Customers
RFM
LTV
Not all responsive customers are profitable
Not all profitable customers will respond when you write them.
RFM Can Predict Responders
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Use RFM to select most likely
responders
Use combination of mail, phone,
and emails to responsive
relationship buyers.
How to Apply Recency Codes
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Put most recent purchase date into every
customer record
Sort database by that date - newest to oldest
Divide into five equal parts - Quintiles
Assign “5” to top group, “4” to next, etc.
Put quintile number in each customer record
Response Rate
Response by Recency Quintile
4.00%
3.50%
3.00%
2.50%
2.00%
1.50%
1.00%
0.50%
0.00%
3.49%
1.25%
1.08%
0.63%
0.26%
5
4
3
Recency Quintile
2
1
How to compute a Frequency
Index
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Keep number of transactions in
customer record
Sort Recency Groups from highest to
lowest
Divide into five equal groups
Number groups from 5 to 1
Put Quintile number in each customer
record
Response by Frequency
Quintile
2.50%
1.99%
2.00%
Response Rate
1.56%
1.31%
1.50%
1.00%
0.92%
0.93%
2
1
0.50%
0.00%
5
4
3
Frequency Quintile
How to compute a Monetary
Index
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Store total dollars purchased in each
customer record
Sort Frequency Groups from highest to
lowest
Divide into 5 equal groups (Quintiles)
Number Quintiles 5, 4, 3, 2, 1
Put Quintile number in each record
1.80%
Response by Monetary
Quintile
1.61%
1.60%
1.45%
1.46%
1.40%
1.22%
1.23%
2
1
1.20%
1.00%
0.80%
0.60%
0.40%
0.20%
0.00%
5
4
3
Monetary Response to $5,000
Product
Percentage of households promoted who purchased
2
1.68
1.5
1.17
0.88
1
0.66
0.5
0.32
0
5
4
3
Monetary Quintile
2
1
RFM Code Construction
R
5
F
35
4
34
3
33
2
32
31
1
Database
One Sort
Five
Sorts
M
335
334
333
332
331
Twentyfive sorts
Appended RFM Codes
Creating an Nth
300,000 Records
Customer Database
For Nth by 10, select every
tenth record.
Nth
30,000 Records
Result will be
statistical replica of
database
Result of Test Mailing to 30,000
#
1
2
3
4
5
RFM
555
554
553
552
551
Mailed
240
240
240
240
240
Response
20
16
13
10
11
Rate
8.15%
6.56%
5.62%
4.33%
4.51%
6
7
8
9
10
545
544
543
542
541
240
240
240
240
240
9
12
6
10
7
3.78%
4.98%
2.88%
4.26%
3.10%
11
12
13
14
535
534
533
532
240
240
240
240
10
9
8
6
4.13%
3.83%
3.35%
2.70%
Test Response Rate by RFM
Index
of Response 0 = Break Even
Cell
500
400
300
200
100
0
-100
-200
555
455
355
255
111
Profit from Test Mailing
Quantity Rate
Goods Sold
Mailing Costs
Profits (Loss)
Amount
402
$40.00 $16,080
30,000
$0.55 $16,500
($420)
Determine Break Even and Test Sizes
How to Compute the
Response Rate

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Divide number of responses by
number mailed. Multiply by 100
Example: Responses = 1034
Mailed = 40,000
Rate = 1034 / 40,000
Rate = 2.59%
Test, Full File & RFM Selects
Compared
Response Rate
Responses
Net Revenue
No. Mailed
Mailing Cost
Profits
Test
Full File RFM Select
1.34%
1.17%
2.76%
402
23,412
15,295
$16,080 $936,480 $611,800
30,000 2,001,056
554,182
$16,500 $1,100,581 $304,800
($420) ($164,101)
$307,000
8.00%
Test Vs Rollout Response
Rates
7.00%
7.00%
6.00%
6.00%
5.00%
5.00%
4.00%
4.00%
3.00%
3.00%
2.00%
2.00%
1.00%
1.00%
0.00%
0.00%
554 553 552 551 545 544 543 542 541 535 534 533 532 531 525 524 523 522 521 515 514 513 512 511 455 451 445 444 443 355 354 351 344
Retroactive RFM Test
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Many times there is not enough time or
funding to run an Nth test in advance
Solution: apply RFM codes to your last
completed outgoing promotion.
Since you know who responded, you
can determine response rates by cell
Use previous rates to govern this
rollout.
How Many RFM Cells Needed?
Test File = (Test Budget) /
(per piece cost)
 Example = $15,000 / $0.76
= 19,737
 Cells Needed = 19,737 / 274
= 72

Cell Division Determination

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To create 72 cells, some must be
less than 5
Recency most powerful. Do not
scrimp.
Example R-F-M = 6 X 4 X 3 = 72
Is this best? Test and see.
RFM For Business Databases
Business databases are small
 For small databases, use
quartiles or thirds
 Quartile = 4 X 4 X 4 = 64 Cells
 Thirds
= 3 X 3 X 3 = 27 Cells
 Custom = 5 X 2 X 2 = 20 Cells

Recent Case History
User sells personalized product
by mail
 45,000 selected for a test

Second Recency Quintile Had
More Responses. Why?
Even so, First Recency Quintile Had
Higher Sales
Recent buyers spend more per
order
Lowest two recency quintiles
did not break even
Frequency was very predictive
of response
Monetary did not predict
response rate very well
But Monetary does predict average
sales by quintile
RFM Cells clearly show who to mail
to, and who to drop
When NOT to use RFM


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
If you use it all the time, half your
customers will never hear from you
They will be lost
The others will suffer from File
Fatigue
Use it sparingly
Product launch is ideal use
THE COMPLETE DATABASE MARKETER
by Arthur Middleton Hughes
Chicago: McGraw Hill 600 pp Glossary
Revised Edition 1996
This is the bible of database marketing. Over 16,000 copies sold. John
Stevenson Exec. VP of Krupp Taylor: "Not only does this book succeed in
being clear and accessible, it is also the first complete treatise...The full
power and practice of database marketing are here, to be sure. This is the
long awaited survival manual for every marketer on the cutting edge. I can't
think of a book that is more rewarding."
This comprehensive book covers such subjects as how to build customer
loyalty, lifetime value calculation, RFM analysis, customer service,
telemarketing, fulfillment, hardware and software, clustering and profiling,
prospecting, media selection. Order from www.DBMarketing.com
STRATEGIC DATABASE MARKETING 2nd Ed.
by Arthur Middleton Hughes
Chicago: McGraw Hill 2000 400 pp
Millions have been spent on database marketing programs that did not work. In
this book Arthur Hughes shows how to evaluate strategies in advance using lifetime value analysis. He explains how to use RFM analysis to boost profits. Russ
Richmond, President of Grey Direct said: "Well, Arthur has done it again. He has
not only integrated the complicated world of databases with the traditional
concepts of direct marketing, but he accurately points out the pitfalls and the
how-tos. I know of a few careers that would have been saved had this book been
available sooner. Without a doubt this will be the cheapest investment you'll
make in your database, and perhaps the most important one." Thousands of
customer marketing databases are being built. Unfortunately, many mistakes
have been made. The reasons for these failures center on one central fault: the
inability of marketers to develop logical, practical and winning strategies for
their database marketing programs. We must study past mistakes to develop
sound principles for marketing strategy. Order from www. DBMarketing.com
Thank You