two new directions for data mining charles ling, phd department of computer science university of...
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Two New Directions for Data MiningTwo New Directions for Data Mining
Charles Ling, PhD
Department of Computer Science
University of Western Ontario, CanadaDirector, Data Mining Lab, UWO
http://csd.uwo.ca/faculty/cling
Charles Ling, PhD
Two New Directions for Data MiningTwo New Directions for Data Mining
Action Mining Active Cost-sensitive Learning
Action Mining for Profitable CRMAction Mining for Profitable CRM
Charles Ling, PhD
Department of Computer Science
University of Western Ontario, CanadaDirector, Data Mining Lab, UWO
http://csd.uwo.ca/faculty/cling
CRMCRMCustomer Relationship Management:
focus on customer satisfaction to improve profit
Two kinds of CRMEnabling 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 TasksThree Intelligent CRM TasksAcquisition: 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 MiningAction MiningBeyond model building and customer profilingImprove customer relationship: Actions changesWhat 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)
Charles Ling, PhD
Research IssuesResearch 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
How How Proactive SolutionProactive Solution Works Works
1. Get Customer Data (marketing DB)
2. Build Customer Profiles
3. Search Actions for Maximal Profit
4. Action Delivery
Step 1: Get Customer DataStep 1: Get Customer Data
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
… … … … … … … … …
1112 Jack 40 M M H B … ???
Marketing DB: Segmentation, data preparation, pre-processing…Define a “target”: undesired status and desired status
Prob=0.1
Prob = 0.2 Prob=0.9 Prob=0.5
Service
RateSex
M L H
MF HL
Prob=0.8
Step 2: Build Customer Profile on targetStep 2: Build Customer Profile on targetAutomatically by Proactive Solution with probabilities on the target
Step 3: Search Actions for Step 3: Search Actions for Maximal ProfitMaximal Profit
ID Name Age Sex Service Rate Prof … Retained
… … … … … … … … …
1112 Jack 40 M M H B … ???
Proactive Solution searches more desired nodes in the profile…
Prob gain = 0.6E.Profit=$2400Cost=$800E.NetProfit=$1600
Prob gain = -0.1E.Profit= -400Cost= $500E.Net Profit= -900
Prob gain = 0.7E Profit= $2800Cost = E Net Profit= -
Prob gain = 0.3E Profit=$1200Cost=$400E NetProfit=$800
Prob gain = 0.6E Profit=$2400Cost=$800E NetProfit=$1600
Jack: …, Service = M, Sex = M, Rate = H, … Profit =$4000
Prob = 0.2 Prob=0.9 Prob=0.5
Prob=0.1
Service
RateSex
M L H
MF HL
Prob=0.8
Serv: MHRate: H L
Step 4: Action DeploymentStep 4: Action Deployment
ID Name Prob diff
Actions Action costs
NetProfit
1112 Jack … 0.6 Service: M H
Rate: H L$800 … $1600
3010 Sue 0.5 SigAcc: 0 1
Service: L M$500 … $700
3421 Bill … N/A $0
• Selective deployment: human intelligence, … • Customer segmentation by actions
Reporting – on the webReporting – on the web
Charles Ling, PhD
Advanced FeaturesAdvanced FeaturesAccurate probability estimationsBetter evaluation methods – AUC of ROC Hard vs soft attributes – search many treesBeam-search Action correlation
Case Study: Mutual FundCase Study: Mutual FundAn insurance company selling mutual fundsTask 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?
Charles Ling, PhD
SummarySummary
From model building to action mining (deployment)
Business oriented: maximal net profitProactive Solution: effective intelligent CRMTechnically sophisticatedMassive one-to-one customizationEffective marketing and segmentation tool