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Two New Directions for Data Mining
Charles Ling, PhD
Department of Computer Science
University of Western Ontario, Canada
Director, Data Mining Lab, UWO
[email protected]
http://csd.uwo.ca/faculty/cling
Two New Directions for Data Mining
 Action
Mining
 Active Cost-sensitive Learning
Charles Ling, PhD
Action Mining for Profitable CRM
Charles Ling, PhD
Department of Computer Science
University of Western Ontario, Canada
Director, Data Mining Lab, UWO
[email protected]
http://csd.uwo.ca/faculty/cling
CRM
Customer Relationship Management:
focus on customer satisfaction to improve profit
Two kinds of CRM
 Enabling CRM: Infrastructure, multiple touch
point, data integration and management, …
– Oracle, IBM, PeopleSoft, Siebel Systems, …

Intelligent CRM: data mining and data analysis
– Vendors/products
(http://www.kdnuggets.com/solutions/crm.html)
Three Intelligent CRM Tasks

Acquisition: direct marketing, application form,
promotion methods, …
 Customization: cross/up-sale, segmentation,
promotions, …
 Retention: Attrition/churn prevention
Goal: through data mining to improve customer
loyalty, satisfaction, and spending, resulting in
increased company profits
Action Mining
Beyond model building and customer profiling
Improve customer relationship: Actions  changes
What actions should you take to change customers
from an undesired status to a desired one
–
–
–
–
–
From churn to loyal
From inactive to active
From low spending to high spending
From non-customers to customers
…
and make the maximum profit (the ultimate goal)
Research Issues
Bounded Action Problem (BAP)
– Types of actions are limited to k
– How to find k action types to maximize profit

The problems are NP-hard
– Exponential to k

Our solutions: heuristic/greedy search based on
decision trees
– Proactive Solution
Charles Ling, PhD
How Proactive Solution Works
1. Get Customer Data (marketing DB)
2. Build Customer Profiles
3. Search Actions for Maximal Profit
4. Action Delivery
Step 1: Get Customer Data
Marketing DB: Segmentation, data preparation, pre-processing…
Define a “target”: undesired status and desired status
ID
Name
Age
Sex
Service Rate Prof …
Retained
(Target)
1001 John
50
M
H
L
A
…
Yes
3010 Sue
25
F
M
H
D
…
No
…
…
…
…
…
…
…
…
40
M
M
H
B
…
???
…
1112 Jack
Step 2: Build Customer Profile on target
Automatically by Proactive Solution with probabilities on the target
Service
M
H
L
Sex
F
Rate
M
L
H
Prob=0.1
Prob=0.9
Prob = 0.2
Prob=0.8
Prob=0.5
Step 3: Search Actions for
Maximal Profit
Proactive Solution searches more desired nodes in the profile…
ID
Name
Age
Sex
Service Rate Prof …
Retained
…
…
…
…
…
…
…
…
…
40
M
M
H
B
…
???
1112 Jack
Jack: …, Service = M, Sex = M, Rate = H, … Profit =$4000
Service
M
H
L
Sex
F
Rate
M
L
Prob=0.1
H
Prob gain
= -0.1
Serv:
MH
E.Profit= -400
Rate:
HL
Cost= $500
E.Net Profit= -900
Prob=0.9
Prob gain = 0.7
E Profit= $2800
Cost = 
E Net Profit= - 
Prob = 0.2
Prob=0.8
Prob gain = 0.6
E
Profit=$2400
E.Profit=$2400
Cost=$800
E
NetProfit=$1600
E.NetProfit=$1600
Prob=0.5
Prob gain = 0.3
E Profit=$1200
Cost=$400
E NetProfit=$800
Step 4: Action Deployment
ID
Name
Prob Actions
diff
1112 Jack
… 0.6
3010 Sue
0.5
3421 Bill
…
Action
costs
Service: M  H $800
Rate: H  L
SigAcc: 0  1
$500
Service: L  M
N/A
NetProfit
… $1600
… $700
$0
• Selective deployment: human intelligence, …
• Customer segmentation by actions
Reporting – on the web
Advanced Features

Accurate probability estimations
 Better evaluation methods – AUC of ROC
 Hard vs soft attributes – search many trees
 Beam-search
 Action correlation
Charles Ling, PhD
Case Study: Mutual Fund
An insurance company selling mutual funds
 Task 1: For the current fund owners, how to
improve their fund purchasing (from low to
high spending)?
 Task 2: Some representatives are good
performers but some are not; how to change
bad performers to be good performers?
 Task 3: Many customers do not currently own
mutual funds. How to market to them to buy
mutual funds?
Summary

From model building to action mining
(deployment)
 Business oriented: maximal net profit
 Proactive Solution: effective intelligent CRM
 Technically sophisticated
 Massive one-to-one customization
 Effective marketing and segmentation tool
Charles Ling, PhD