Business Intelligence/
Decision Models
RFM Analysis
Outline

Explain how RFM works, and how you
can use it to improve response rates
and reduce costs

SPSS RFM



With transaction files
With customer files
Use of RFM with Target Variable
2
Recency, Frequency, and
Monetary (RFM) Analysis
According to Hughes!

Always improves response and profits

Better than any demographic model

The most powerful segmentation method
for predicting response
Old-fashioned RFM?

Never assume a CHAID program or
even a regression model will
outperform an old-fashioned RFM…
(David Shepard)
Respon se 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
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
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
Big Ticket: Response to $5,000 CD Offer by Monetary
Percentage of households promoted who purchased
2
1.68
1.5
1.17
1
0.88
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
1
M
335
334
333
332
331
Twentyfive sorts
RFM Code Construction
R
DB
F
2
M
5
5
5
4
4
4
3
3
3
2
2
2
1
1
1
1st Sort
DB
2nd Sort
DB
3rd Sort
RFM Code Construction

3
Predefined subjective breaks:



R = < 2 wks, 2-6 wks, 7-8 wks, and > 12 wks
F = 10, 8, 6, 3, 1
M = > $500, $300-500, $200-300, $100-200, < $200,
11
RFM Code Construction
R = 5, 4, 3, 2, 1 @ weight = 10
 F = 5, 4, 3, 2, 1 @ weight = 5
 M =5, 4, 3, 2, 1 @ weight = 1
 Weighted sum



Score =  xiwi
Ex. RFM 421 = Score 51
4
Let’s stick with this one!
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
Break Even Response Rate

BE = Unit Cost / Unit Profit

Example:
• Unit cost = .55
• Unit profit = $33
• Thus $.55 / $33 = 0.0167 or 1.67%
Number of Cells


5 x 5 x 5 = 125 cells
How many individuals per cell so that
response is significant?




Minimum  4 / BE
Ex. 4 / .0167 = 240 individuals per cell
# of customers +/- 30,000
Use Common sense:
5x4x4, or 5x4x3, or 5x2x2, or 4x2x3
15
Systematic Sampling:
Selecting every Nth case
Customer Database
300,000 Records
For Nth by 10, select every
tenth record.
Nth
30,000 Records
Result will be a
statistical replica of
the database
Result of Test for 30,000
#
1
2
3
4
5
RFM
555
554
553
552
551
Reach
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%
Case Study





# of customers 2,100,000
Test with 30,000
Left with 2,070,000
If 555 RFM  125 cells
16,560 customers per cell
18
Test Response Rate by RFM
Cell
Index of Response 0 = Break Even
500
400
300
200
100
0
-100
34/125 cells above BE
-200
555
455
355
255
111
Break Even Index (BEI)

BE: .0167 set to 0 or 100 as a reference point
Ex. Assume Response = .025 for a given cell

If BEI set to 0





BEI = [(Resp – BE)/BE] * 100
Ex.
[(.025 - .0167)/.0167]*100
Ex.
49.7 rounded 50
If BEI set to 100


BEI = [Resp/BE] * 100
Ex.
[.025/.0167] * 100 = 150
Profit from Test Program
Quantity
Rate
Amount
Gross Profit
402
$40.00
$16,080
Fixed Costs
30,000
$0.55
$16,500
Profits (Loss)
($420)
Test, Full File & RFM
Selects Compared
Test
Response Rate
Responses
Net Revenue
Quantities
Fixed Costs
Profits
Full File
RFM Select
1.34%
1.17%
2.76%
402
23,412
15,540
$16,080
$936,480
$621,596
30,000
2,001,585
563,040
$16,500
$1,100,581
$309,672
-$420
-$164,101
$311,924
RFM Procedure

Transaction file
• Run RFM on transaction file
• Create an new RFM dataset
• Merge with customer file

Customer file
• File is already prepared
• Run RFM on time since last purchase,
number of purchases, and money spent
24
SPSS Means Procedure

Compare Means  Means
DV  Response Variable (0/1)
 IV
 RFM (Means and N)


Copy output table to Excel
Sort all columns by mean response
 Descending order


Determine BE and economics
25
Selected RFM
RFM score
515
Mean
Cost
N
Income
.46
547
$
410 $
1,008
512
.42
1097
$
823 $
1,860
514
.42
530
$
398 $
892
513
.41
185
$
139 $
304
511
.38
318
$
239 $
488
411
.34
302
$
227 $
416
415
.34
565
$
424 $
760
414
.32
561
$
421 $
708
412
.31
1205
$
904 $
1,516
413
.30
185
$
139 $
224
312
.28
1543
$
1,157 $
1,704
311
.27
527
$
395 $
576
314
.27
724
$
543 $
768
315
.25
749
$
562 $
744
313
.24
132
$
99 $
128
211
.21
1053
$
790 $
904
213
.18
1318
$
7,667 $
$
62,162 $
Total
.07
82882
U. Cost
0.75
U. Profit
4
BE
0.1875
13,000 $ 5,333
21,920 -$ 40,242
26
Bits and Pieces

Recency with continuity:


Frequency?




Change in buying decisions
Purchases in year or # of items
Transactions in a year
# of visits, # of calls
Tests and Rollouts
Caution about RFM

Customer reach

File fatigue

Use RFM for testing

Use it to identify your best customers

Objectives? Profit, ROI, Reach
RFM Customer File
RFM Customer File
RFM Customer File
RFM Customer File
RFM Customer File
RFM Customer File
RFM Sort

Analyze

Compare Means
Means
RFM Sort, Import into Excel
RFM
111
112
113
114
115
121
122
123
124
125
131
Mean N
.1975 319
.1937 320
.1531 320
.1438 320
.1531 320
.0562 320
.0281 320
.0438 320
.0438 320
.0344 320
.0094 320
………..…
535
541
542
543
544
545
551
552
553
554
555
Total
.1219
.0719
.0688
.0594
.0656
.0500
.0219
.0188
.0281
.0250
.0281
.1484
320
320
320
320
320
320
320
320
320
320
320
39999
36
RFM Economics
Ex. Catalogue
Fixed Cost
$4.00
Gross Profit
$20.00
BE
$4 / $20 = .20
Sent to all
39,999
Cost
$159,996
Resp .1484
5,936
Gross
$118,720
Sent to > .20
10,240
Cost
$40,960
Buyers
4,367
Gross
$87,340
- $41,276
$46,380
37
RFM Economics
Email
Fixed Cost
$0.02
Unsub.
.025
Gross Profit
$20.00
Worst
Case
.050
BE
.02/20 = .001
CLV
$100
Sent to all
39,999
Cost
Resp .1484
5,936
Gross
Cust. Loss
20,000
Sent to > .20
10,240
Cost
Buyers
4,367
Gross
Cust. Loss
256
$800
$118,720
$2,000,000 - $1,882,100
$205
$87,340
$25,600
$61,535
38