1. Business Intelligence/ Decision Models
RFM Analysis

2. 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

3. 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

4. Old-fashioned RFM?
Never assume a CHAID program or even a regression model will outperform an old-fashioned RFM… (David Shepard)

5. Response by Recency Quintile

6. Response by Frequency Quintile

7. Response by Monetary Quintile

8. Big Ticket: Response to $5,000 CD Offer by Monetary
Monetary Quintile
Percentage of households promoted who purchased
1.68
1.17
0.88
0.66
0.32 5 4 3 2 1
0.5
1.5

9. RFM Code Construction 1 R F M One Sort Five Sorts Twenty-five sorts
Database 5 4 3 2 1 35 34 33 32 31
335
334
333
332
331

10. RFM Code Construction 2 R F M 5 4 3 2 1 5 4 3 2 1 5 4 3 2 1 DB
1st Sort DB
2nd Sort DB
3rd Sort

11. 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, $ , $ , $ , < $200,

12. RFM Code Construction 4 R = 5, 4, 3, 2, 1 @ weight = 10
F = 5, 4, 3, 2, weight = 5
M =5, 4, 3, 2, weight = 1
Weighted sum
Score =  xiwi
Ex. RFM 421 = Score 51

13. Let’s stick with this one!R F M
One Sort
Five Sorts
Twenty-five sorts
Database 5 4 3 2 1 35 34 33 32 31
335
334
333
332
331

14. Break Even Response Rate
BE = Unit Cost / Unit Profit
Example:
Unit cost = .55
Unit profit = $33
Thus $.55 / $33 = or 1.67%

15. 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 / = 240 individuals per cell
# of customers +/- 30,000
Use Common sense: 5x4x4, or 5x4x3, or 5x2x2, or 4x2x3

16. Selecting every Nth case
Systematic Sampling:
Selecting every Nth case
Customer Database
300,000 Records
For Nth by 10, select every tenth record.
Nth
Result will be a statistical replica of the database
30,000 Records

17. Result of Test for 30,000

18. 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

19. Test Response Rate by RFM Cell
34/125 cells above BE

20. 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. [( )/.0167]*100
Ex rounded 50
If BEI set to 100
BEI = [Resp/BE] * 100
Ex. [.025/.0167] * 100 = 150

21. Profit from Test Program

22. Test Vs Rollout Response Rates
Test = Lines Rollout = Bars

23. Test, Full File & RFM Selects Compared
Response Rate
1.34%
1.17%
2.76%
Responses
402
23,412
15,540
Net Revenue
$16,080
$936,480
$621,596
Quantities
30,000
2,001,585
563,040
Fixed Costs
$16,500
$1,100,581
$309,672
Profits
-$420
-$164,101
$311,924

24. RFM Procedure Transaction file Customer 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

25. SPSS Means Procedure Compare Means  Means Copy output table to Excel
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

26. Selected RFM $ 62,162 $ 21,920 -$ 40,242 RFM score Mean N Cost Income
515
.46
547 $
$ ,008
512
.42
1097 $
$ ,860
514
530 $ $
513
.41
185 $ $
511
.38
318 $ $
411
.34
302 $ $
415
565 $ $
414
.32
561 $ $
412
.31
1205 $
$ ,516
413
.30 $
312
.28
1543
$ ,157
$ ,704
311
.27
527 $ $
314
724 $ $
315
.25
749 $ $
313
.24
132 $ $
211
.21
1053 $
213
.18
1318
$ ,667
$ ,000
$ 5,333
U. Cost
U. Profit BE
0.75 4
0.1875
Total
.07
82882
$ ,162
$ ,920
-$ 40,242

27. Bits and Pieces Recency with continuity: Frequency? Tests and Rollouts
Change in buying decisions
Frequency?
Purchases in year or # of items
Transactions in a year
# of visits, # of calls
Tests and Rollouts

28. Caution about RFM Customer reach File fatigue Use RFM for testing
Use it to identify your best customers
Objectives? Profit, ROI, Reach

29. RFM Customer File

30. RFM Customer File

31. RFM Customer File

32. RFM Customer File

33. RFM Customer File

34. RFM Customer File

35. RFM Sort
Analyze
Compare Means
Means

36. RFM Sort, Import into Excel
Total
RFM Mean N
………..…

37. 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
- $41,276
Sent to > .20
10,240
$40,960
Buyers
4,367
$87,340
$46,380

38. 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
$800
Resp .1484
5,936
Gross
$118,720
Cust. Loss
20,000
$2,000,000
- $1,882,100
Sent to > .20
10,240
$205
Buyers
4,367
$87,340
256
$25,600
$61,535