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Figure 4 Recency-Frequency-Monetary Value (RFM) Matrix Hi recency Hi monetary value Hi frequency Example #1 RFM Scoring scheme: Buy interval <1 month = 5 1-3 months = 4 3-6 months = 3 6-9 months = 2 >9 months = 1 frequency >40 = 5 30-40 = 4 20-29 = 3 10-19 = 2 <10 = 1 total buy >$50k = 5 $20k-$50k = 4 $10k-$20k = 3 $5k-$10k = 2 <$5k = 1 Example #1 RFM Customer ID last buy* A 05/08 B 01/08 C 11/07 D 07/08 E 01/07 F 03/08 G 05/07 H 07/08 *vs. now, 07/08 frequency 12 18 35 1 6 40 5 20 total $ 6k 9k 40k 1k 5k 90k 2k 9k RFM score 422 422 322 322 244 442 511 511 122 211 355 553 111 111 532 532 Convention to rearr Most valuable F H D C A B E G Rank low= recovery Example #2 RFM 1) Data preparation Old variable recoded (or create a new variable) Recency If Last order placed w/in past 3 months: Last order w/in past 6 months Last order w/in past 9 months Last order w/in past year Last order w/in past 2 years then: 20 points 10 5 3 1 Frequency #purchases over past 2 years x 4 points, max = 20points (i.e., if #purchases x 4 >20, reset to =20) Monetary Value $spent over past 2 years x .10 (max = 20 points) 2) Weights (judgment) Recency score: 5 Frequency 3 Monetary value 2 3) Multiple variables by weights and sum to get “final weighted RFM scores” for targeting good customers Example #2 RFM Step 1) Data preparation The old variables are recoded (creating new vars) Recency If Last order placed w/in past 3 months: Last order w/in past 6 months Last order w/in past 9 months Last order w/in past year Last order w/in past 2 years then: 20 points 10 5 3 1 Frequency #purchases over past 2 years x 4 points, max = 20points (i.e., if #purchases x 4 >20, reset to =20) Monetary Value $spent over past 2 years x .10 (max = 20 points) Step 2) Weights (judgment) Recency score: Frequency Monetary value 5 3 2 Step 3) Multiple variables by weights and sum to get “final weighted RFM scores” for targeting good customers