Use RFM to Boost Your Response Rate
description
Transcript of Use RFM to Boost Your Response Rate
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Use RFM to Boost Your Response Rate
Arthur Middleton Hughes
Vice President / Solutions Architect
KnowledgeBase Marketing, Inc.
DMA Monday, October 17, 2005
1:00 – 2:00 PM
Georgia World Congress Center
Atlanta, Georgia
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MarketingDatabase
Data Access& AnalysisSoftware
Customer Transactions
Marketing Staff
Inputs from Retail, Phone, Web
How a modern database system works
AppendedData &
Modeling
Customer Service
Web Site
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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!
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Responsiveness & Profitability are not the same
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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
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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
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Responsive customers may not be the most profitable
Profitable Customers
Responsive Customers
Not all responsive customers are profitable
Not all profitable customers will respond when you write them.
LTV RFM
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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.
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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
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Response by Recency Quintile
3.49%
1.25% 1.08%0.63%
0.26%
0.00%0.50%1.00%1.50%2.00%
2.50%3.00%3.50%4.00%
5 4 3 2 1
Recency Quintile
Res
pons
e R
ate
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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
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Response by Frequency Quintile
1.99%
1.56%1.31%
0.92% 0.93%
0.00%
0.50%
1.00%
1.50%
2.00%
2.50%
5 4 3 2 1Frequency Quintile
Re
spo
nse
Ra
te
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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
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Response by Monetary Quintile
1.61%1.45% 1.46%
1.22% 1.23%
0.00%
0.20%
0.40%
0.60%
0.80%
1.00%
1.20%
1.40%
1.60%
1.80%
5 4 3 2 1
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Monetary Response to $5,000 Product
Monetary Quintile
Percentage of households promoted who purchased
1.68
1.170.88
0.66
0.32
5 4 3 2 10
0.5
1
1.5
2
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RFM Code Construction
FM
One SortFive Sorts
Twenty-five sorts
Database
5
4
3
2
1
35
34
33
32
31
335334333332331
R
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Appended RFM Codes
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Customer Database
Nth
Creating an Nth
300,000 Records
30,000 Records
For Nth by 10, select every tenth record.
Result will be statistical replica of database
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Result of Test Mailing to 30,000
# RFM Mailed Response Rate1 555 240 20 8.15%2 554 240 16 6.56%3 553 240 13 5.62%4 552 240 10 4.33%5 551 240 11 4.51%
6 545 240 9 3.78%7 544 240 12 4.98%8 543 240 6 2.88%9 542 240 10 4.26%10 541 240 7 3.10%
11 535 240 10 4.13%12 534 240 9 3.83%13 533 240 8 3.35%14 532 240 6 2.70%
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Test Response Rate by RFM Cell
-200
-100
0
100
200
300
400
500
555 455 355 255 111
Index of Response 0 = Break Even
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Profit from Test Mailing
Quantity Rate Amount
Goods Sold 402 $40.00 $16,080
Mailing Costs 30,000 $0.55 $16,500
Profits (Loss) ($420)
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Determine Break Even and Test Sizes
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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%
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Test, Full File & RFM Selects Compared
Test Full File RFM SelectResponse Rate 1.34% 1.17% 2.76%Responses 402 23,412 15,295Net Revenue $16,080 $936,480 $611,800No. Mailed 30,000 2,001,056 554,182Mailing Cost $16,500 $1,100,581 $304,800
Profits ($420) ($164,101) $307,000
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Test Vs Rollout Response Rates
0.00%
1.00%
2.00%
3.00%
4.00%
5.00%
6.00%
7.00%
8.00%
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
0.00%
1.00%
2.00%
3.00%
4.00%
5.00%
6.00%
7.00%
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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.
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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
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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.
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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
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Recent Case History
• User sells personalized product by mail
• 45,000 selected for a test
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Second Recency Quintile Had More Responses.
Why?
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Even so, First Recency Quintile Had Higher Sales
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Recent buyers spend more per order
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Lowest two recency quintiles did not break
even
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Frequency was very predictive of response
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Monetary did not predict response rate very well
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But Monetary does predict average sales by quintile
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RFM Cells clearly show who to mail to, and who to drop
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When NOTNOT 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
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3.49%
1.25% 1.08%0.63%
0.26%
0.00%0.50%1.00%1.50%2.00%
2.50%3.00%3.50%4.00%
5 4 3 2 1
Recency Quintile
Resp
onse
Rate
Response by Recency Quintile
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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
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Response by Frequency Quintile
1.99%
1.56%
1.31%
0.92% 0.93%
0.00%
0.50%
1.00%
1.50%
2.00%
2.50%
5 4 3 2 1Frequency Quintile
Re
spo
nse
Ra
te
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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
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Response by Monetary Quintile
1.61%
1.45% 1.46%
1.22% 1.23%
0.00%
0.20%
0.40%
0.60%
0.80%
1.00%
1.20%
1.40%
1.60%
1.80%
5 4 3 2 1
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RFM Code Construction
FM
One SortFive Sorts
Twenty-five sorts
Database
5
4
3
2
1
35
34
33
32
31
335334333332331
R
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Appended RFM Codes
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Result of Test Mailing to 30,000# RFM Mailed Response Rate 1 555 240 20 8.15% 2 554 240 16 6.56% 3 553 240 13 5.62% 4 552 240 10 4.33% 5 551 240 11 4.51%
6 545 240 9 3.78% 7 544 240 12 4.98% 8 543 240 6 2.88% 9 542 240 10 4.26% 10 541 240 7 3.10%
11 535 240 10 4.13% 12 534 240 9 3.83% 13 533 240 8 3.35% 14 532 240 6
2.70%
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Test Response Rate by RFM Cell
-200
-100
0
100
200
300
400
500
555 455 355 255 111
Index of Response 0 = Break Even
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Profit from Test Mailing
Quantity Rate Amount
Goods Sold 402 $40.00 $16,080
Mailing Costs 30,000 $0.55 $16,500
Profits (Loss) ($420)
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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%
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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.
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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%
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Test Response Rate by RFM Cell
-200
-100
0
100
200
300
400
500
555 455 355 255 111
Index of Response 0 = Break Even
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Test, Full File & RFM Selects Compared
Test Full File RFM SelectResponse Rate 1.34% 1.17% 2.76%Responses 402 23,412 15,295Net Revenue $16,080 $936,480 $611,800No. Mailed 30,000 2,001,056 554,182Mailing Cost $16,500 $1,100,581 $304,800
Profits ($420) ($164,101) $307,000
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Test Vs Rollout Response Rates
0.00%
1.00%
2.00%
3.00%
4.00%
5.00%
6.00%
7.00%
8.00%
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
0.00%
1.00%
2.00%
3.00%
4.00%
5.00%
6.00%
7.00%
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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
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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.
![Page 58: Use RFM to Boost Your Response Rate](https://reader035.fdocuments.net/reader035/viewer/2022081512/56815861550346895dc5bd85/html5/thumbnails/58.jpg)
Recent Case History
• User sells personalized product by mail
• 45,000 selected for a test
![Page 59: Use RFM to Boost Your Response Rate](https://reader035.fdocuments.net/reader035/viewer/2022081512/56815861550346895dc5bd85/html5/thumbnails/59.jpg)
Second Recency Quintile Had More Responses. Why?
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Even so, First Recency Quintile Had Higher Sales
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Recent Buyers Spend More per Order
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Lowest Two Recency Quintiles did not Break Even
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Frequency was Very Predictive of Response
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Monetary did not Predict Response Rate Very Well
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But Monetary does Predict Average Sales by Quintile
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RFM Cells Clearly Show who to Mail to, and who to Drop
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When NOTNOT 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!
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Half Life Data
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Graphing Half Life
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Half Life by Revenue
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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
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Books by Arthur Hughes
From McGraw Hill. Order at www.dbmarketing.com Contact Arthur: [email protected]