Succesvol, efficiënt en operationeel
management van de customer life-cycle
Une gestion efficace et performante du cycle
clients
Greet Maris
Head of CRM Group
Thierry Van de Merckt
Project Manager
24.03.09 IMAGIBRAINE
Agenda
( Citi in Belgium
( Vadis Consulting sa
( How to capture Client Life Cycle from prospect to mature
client?
( Methodology & Tools
( Making things operational
( Business Added Value
Citi in the world
( World-wide financial services company organized into :
� Institutional Client Group & Corporate
� Consumer Banking
� Global Wealth Management – Private Banking
� Global Cards Group
( Present in + 100 countries
( Servicing 200 million customer accounts
( By over 300.000 employees
Citi in Belgium
Customers : 560.000 Employees : 1500
Points of sales : 212
Consumer Banking with specific focus on consumer credit
Citi in Belgium
BIG 4
+ 85% market share
Challengers
Consumer Banking in Belgium
Who is VADIS
( VADIS Consulting sa/nv
� Founded Jan 2004, as the preferred analytic partner
of WDMLocated in WDM building, Brussels
� Focuses on the implementation of Analytical
Solutions
� Software development & innovation (45% of turnover
in R&D)
� 17 high level consultants and developers in this field
� Very active in B2B analytical world
� Consulting & Integration activity as well
Our objective is to leverage internal and external data for our
clients in order for them to gain a significant competitive
advantage, in terms of market expansion, enterprise
profitability and global risk reduction.
Agenda
( Citi in Belgium
( Vadis Consulting sa
( How to capture Client Life Cycle from prospect to mature
client?
Managing Customer Life Cycle
Anticipate
&
Manage
Understand
( From prospect …
How to keep a growing process, where more and more information can be captured,
where a lot different interactions and events will influence the life cycle,
still to be efficient and operational?
How to keep a growing process, where more and more information can be captured,
where a lot different interactions and events will influence the life cycle,
still to be efficient and operational?
to client … to your best client
Capture Consumer Life Cycle
InteractionsEvents
Events
Events
Events
Defining elements describing life cycle is joint effort from external data provider,
marketeer, product manager and sales person, so that there is a fertilization
cross interactions and cross product lines.
Defining elements describing life cycle is joint effort from external data provider,
marketeer, product manager and sales person, so that there is a fertilization
cross interactions and cross product lines.
Market Situation
Product Usage
Portfolio
Family / DemographicA
cqu
isit
ion
Capture Consumer Life Cycle
( Think big
( Variables are based on RFM+
( Data driven approach
� Data dictionary – clear definitions
� Data audit
� Updates and historisation
In order to allow industrialization of full process, based on this data driven approach,
important to have the data updated and historized.
In order to allow industrialization of full process, based on this data driven approach,
important to have the data updated and historized.
Agenda
( Citi in Belgium
( Vadis Consulting sa
( How to capture Client Life Cycle from prospect to mature
client?
( Methodology & Tools
Methodology & critical success factors
1.500 computed variables account for the life-cycle stage of each client.
It’s a generic container for all predictive models, analysis and contact strategy design.
1.500 computed variables account for the life-cycle stage of each client.
It’s a generic container for all predictive models, analysis and contact strategy design.
Client
360°
Data
RFM
Events
Dynamics
Contact/Channel
Family/Co-Holder
Socio-demo
Business
Knowledge
Bank Products
Bank Processes
Contact Strategy
Client Life cycle
Analytical data
Events are combined within models (not outside)
( Event X: Age in months of the measured event since last run
of the modelCARD_Cash_LastAge
63,598
3,091 2,701 2,819 4,536
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
-1 0 1+2 3+4+5 6+7+8+9+10+11
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
Frequency Fraction_of_Target
No event
Chance for a client
to be interested by
our offer
Number of clients
having the computed
characteristic
Events are combined within models (not outside)
( Event X: Age in months of the measured event since last run
of the model
CARD_Cash_LastAge
63,598
3,091 2,701 2,819 4,536
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
-1 0 1+2 3+4+5 6+7+8+9+10+11
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
Frequency Fraction_of_Target
4.8 more chance to sell Y if proposed within the month of event X
Events are captured from operational systems, transformed in the analytical datamart,
and used with 10 other variables to get a lift of 7.9 on the top 5% cases.
Events are captured from operational systems, transformed in the analytical datamart,
and used with 10 other variables to get a lift of 7.9 on the top 5% cases.
Lift of 4.8 on 4% of clients
No event
Contact Strategy is part of the picture…
( Nbre of Past Contacts: Not always what we expect…
Learning loop is not only for Reporting. Models can use those “feedback” measures
on contacts and channels as well. Depending on the target, it might give highly different
results.
Learning loop is not only for Reporting. Models can use those “feedback” measures
on contacts and channels as well. Depending on the target, it might give highly different
results.
W e a lt h _ N b _ c a m p a ig n
6 8 8 0 8 3
2 2 3 8 7 5 5 3 6 1 0 7 80
1 0 0 ,0 0 0
2 0 0 ,0 0 0
3 0 0 ,0 0 0
4 0 0 ,0 0 0
5 0 0 ,0 0 0
6 0 0 ,0 0 0
7 0 0 ,0 0 0
8 0 0 ,0 0 0
0 1 2 3 + 4 + 5 + 6
0 .0 %
1 .0 %
2 .0 %
3 .0 %
4 .0 %
5 .0 %
6 .0 %
7 .0 %
F r e q u e n c y F r a c tio n _ o f_ Ta rg e t
C re d it_N b _c am p aign
484599
16205 15410 1840850354
27843 24533 33843 17213 15459 2506 1981 3159 55710
100,000
200,000
300,000
400,000
500,000
600,000
0 1 2 3 4 5 6 7 8 9 10 11 12 13+ 14+ 15
0.0%
0.2%
0.4%
0.6%
0.8%
1.0%
1.2%
1.4%
1.6%
1.8%
2.0%
F requenc y F rac tion_of_Targe t
( Socio-demo: Type of family
Socio_profession
0
10,000
20,000
30,000
40,000
50,000
60,000
WOR Other Values PEN EMP SEL NOP
0.0%
0.2%
0.4%
0.6%
0.8%
1.0%
1.2%
1.4%
1.6%
Frequency Fraction_of_Target
Socio-Demo combines usage and family
3.5 more chance to sell Y to Class 3 than to major Class
Socio-demo provided by WDM allows to include personal & family factors in the picture.
It also creates a smooth transition from Prospects acquisition to Clients fertilization.
Socio-demo provided by WDM allows to include personal & family factors in the picture.
It also creates a smooth transition from Prospects acquisition to Clients fertilization.
Lift of 3.5 on 9% of clients
Class 3 Class 1 Class 2 Class 4 Class 6 Class 5
Methodology & critical success factors
People People
Risk Mitigation
Data Model &
Method
Client
360°
Data
RFM
Events
Dynamics
Contact/Channel
Family/Co-Holder
Socio-demo
Business
Knowledge
Bank Products
Bank Processes
Contact Strategy
Client Life cycle
Analytical data
Robust
Scalable
Modelling
Good design
No deploy crash
No black boxes
Good validation
Good recoding
Methodology & critical success factors
People People
Risk Mitigation
Data Model &
Method
The Scoring task
( Task:
� Based on past experience, find a number of typical green profiles allowing to build a reliable proximity measure for computing probability of interest…
( Problem:
� Profile depends a lot of the variables used: how to find the best ones among many?
� What makes a real (in a statistical sense) difference?
High probability Low probability Medium probability
Performance
Model
selection
Random
selection
Percentage of selected population
Percentage of target
identified
?????
Methodology & critical success factors
Client
360°
Data
RFM
Events
Dynamics
Contact/Channel
Family/Co-Holder
Socio-demo
Robust
Scalable
Modelling
Good design
No deploy crash
No black boxes
Good validation
Good recoding
Business
Validation
Processes
Biases
Scoring
Joined Offers
Business
Knowledge
Bank Products
Bank Processes
Contact Strategy
Client Life cycle
Analytical data
People People People People
Risk Mitigation
Data Model &
Method
Tool &
Method
( Dynamics: elapse time in months when customer acquired
product X
Card_Nb_Active_months_HP
2,671 2,750 1,696 1,202 1,872 1,502 2,013 1,399 1,406 1,448
203,138
0
50,000
100,000
150,000
200,000
250,000
1 2 3 4 5 6 7+8 9 10 11 12
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
7.0%
8.0%
Frequency Fraction_of_Target Poly. (Fraction_of_Target)
Business MUST be there!
Something happens here.
Business process: after 9 months stopped to be included in campaigns…
Business interpretation MUST be done to eliminate business bias…Business interpretation MUST be done to eliminate business bias…
Methodology & critical success factors
Client
360°
Data
RFM
Events
Dynamics
Contact/Channel
Family/Co-Holder
Socio-demo
Robust
Scalable
Modelling
Good design
No deploy crash
No black boxes
Good validation
Good recoding
Business
Validation
Processes
Biases
Scoring
Joined Offers
Business
Knowledge
Bank Products
Bank Processes
Contact Strategy
Client Life cycle
Analytical data
People People People People
Risk Mitigation
Data Model &
Method
Tool &
Method
Methodology & critical success factors
Client
360°
Data
RFM
Events
Dynamics
Contact/Channel
Family/Co-Holder
Socio-demo
Robust
Scalable
Modelling
Good design
No deploy crash
No black boxes
Good validation
Good recoding
Business
Validation
Processes
Biases
Scoring
Joined Offers
Industria-lization
Fast deploy
Reliable scores
Alarm attention
Watch Oldness
“All inclusive”
Business
Knowledge
Bank Products
Bank Processes
Contact Strategy
Client Life cycle
Analytical data
People People People People
Risk Mitigation
Data Model &
Method
Tool &
Method
Tool &
Method
Agenda
( Citi in Belgium
( Vadis Consulting sa
( How to capture Client Life Cycle from prospect to mature
client?
( Methodology & Tools
( Making things operational
Full Process
ExclusionExclusion
AnalyticalDatamart
Trusted_Repository_current
Exclusion_History
DirectMarketing
Campaign & response
Operational
External data
Propositions_current
PropositionsHistory
OptimizationOptimization P of C
Results_current
Results_History
Model 1
Model 2
Model X
…
Data Drift Score Drift
Control Process
Industrialization
Results_current
Model 1
Propositions_current
ExclusionExclusion
Trusted_Repository_current
OptimizationOptimizationModel 2
Model X
…
AnalyticalDatamart
DirectMarketing
P of C
Model Z
When the process needs to be scaled up, important that as much as possible is
parameterized. An automated control process for the correctness of the models needs
to be in place with only manual intervention when required.
When the process needs to be scaled up, important that as much as possible is
parameterized. An automated control process for the correctness of the models needs
to be in place with only manual intervention when required.
Agenda
( Citi in Belgium
( Vadis Consulting sa
( How to capture Client Life Cycle from prospect to mature
client?
( Methodology & Tools
( Making things operational
( Business Added Value
Business Added Value
Product C
X-sell
1
1
1Product A
Product B
Business Added Value
Retention
Product C
X-sell
1
2
2Product A
Product B
Upsell
Business Added Value
1 1
1
Upsell Retention
Product C
X-sell
1
3
3Product A
Product B
Business Added Value
1 1
1
Upsell Retention
Product C
X-sell
1
4
4Product A
Product B
Business Added Value
1 1
1
Upsell Retention
Product C
X-sell
1
4
4Product A
Product B
1) Direct Marketing strategy (product driven) is adapted according to propensity
to buy scores, by doing the right offer, increasing your response and
this at the right time, maintaining your contact capital.
1) Direct Marketing strategy (product driven) is adapted according to propensity
to buy scores, by doing the right offer, increasing your response and
this at the right time, maintaining your contact capital.
?????
Conclusion
Manage life cycle
of your customer
Better targetting
Optimize contact strategy
and
Improve profitability
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