Use RFM
to Boost Your Response Rate
DMA Monday, October 17, 2005
1:00 – 2:00 PM
Georgia World Congress Center
Atlanta, Georgia
Arthur Middleton Hughes
Vice President / Solutions Architect
KnowledgeBase Marketing, Inc.
How a modern database
system works
Customer
Transactions
Marketing
Database
Inputs from Retail,
Phone, Web
Data Access
& Analysis
Software
Appended
Data &
Modeling
Web Site
Marketing
Staff
Customer
Service
Two Kinds of Database People
Constructors
People who build databases
Merge/Purge, Hardware, Software
Creators
People who understand strategy
Build loyalty and repeat sales
You need both kinds!
Responsiveness & Profitability
are not the same
Recency Frequency Monetary
(RFM) Analysis
• Used for marketing to customers
• Always improves response and profits
• Better than any demographic model
• The most powerful segmentation method
How to Apply Recency Codes
• 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
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
• For product launch, select SICs with
highest penetration ratios
• Use RFM to select most likely
responders
• Use combination of mail, phone,
and sales visits to responsive
relationship buyers.
How to Apply Recency Codes
• 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
• 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
• 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
Response by Monetary Quintile
1.80%
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
Cell
Index of Response
0 = Break Even
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
• 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
Test Vs Rollout Response Rates
8.00%
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
• 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
• 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
• 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
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
• Keep number of purchases in customer
record
• Sort records in each recency quintile
from highest to lowest
• Divide into five equal groups (Quintiles)
• Number quintiles from 5 to 1
• Put Quintile number in each customer
record
Response by Frequency Quintile
2.50%
2.00%
1.99%
Response Rate
1.56%
1.50%
1.31%
1.00%
0.92%
0.93%
2
1
0.50%
0.00%
5
4
3
Frequency Quintile
How to compute a Monetary
Index
• Store total dollars purchased in each
customer record
• Sort the records in each frequency
quintile from highest to lowest
• Divide into 5 equal groups (Quintiles)
• Number Quintiles 5, 4, 3, 2, 1
• Put Quintile number in each customer
record
Response by Monetary Quintile
1.80%
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
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
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
Cell
Index of Response 0 = Break Even
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)
What is the break even rate?
• Each test segment must be measured
• A segment breaks even if the profit from
sales exactly equals the cost of the
promotion
• BE = (Per Piece Cost) / (Net revenue
from one sale)
• BE = ($0.48) / ($28) = 1.71%
How large must test segments
be?
• Large enough for predictive accuracy
• Small enough to keep test costs down
• Size = 4.00 / (Break Even Rate)
• Size = 4.00 / 1.71% = 234 pieces
mailed
• You should adjust the “4.00” based on
your experience -- up or down.
How to Compute the Response
Rate
• Divide number of responses by number
mailed. Multiply by 100
• Example:
Responses = 1034
Mailed = 40,000
Rate = 1034 / 40,000
Rate = 2.59%
Test Response Rate by RFM
Cell
Index of Response 0 = Break Even
500
400
300
200
100
0
-100
-200
555
455
355
255
111
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
Test Vs Rollout Response Rates
8.00%
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
RFM Deals With Very Small Numbers
• Only a small percentage (such as 5%) of
customers respond to the typical offer
• 95% or more will not respond at all
• RFM tells you which customers are most
likely to be in the responsive 5%
• Those who respond may not be your
most profitable customers
Retroactive RFM Test
• Many times there is not enough time or
funding to run an nth test in advance.
• Solution: apply RFM codes to last year’s
completed outgoing promotion.
• Since you know who responded, you can
determine response rates by cell.
• Use last year’s rates to govern this year’s
rollout.
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
• 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; when you need a boost
• Use it to identify your best customers
• Don’t go hog wild!
Half Life Data
Graphing Half Life
Half Life by Revenue
What should you do?
• Maintain a customer database
• Maintain the most recent date,
frequency of orders and total dollar
amount
• Put RFM cell codes into your records
• With each mailing, see which cells
respond.
• Increase response and profits by
NOT MAILING non responsive cells
Books by Arthur Hughes
From McGraw Hill. Order at
www.dbmarketing.com
Contact Arthur: arthur.hughes@kbm1.com