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Getting you there.
Marketing leads Optimization at Fortis RBB
Evolution of an analytical CRM strategy : from product-oriented approach
to customer-centric approach
SAS Belux Forum 2008 | Manuel Piette | 24 May 2017 | 1
Agenda
– Fortis introduction  Retail Banking Belgium  Analytical & Predictive Marketing
– Building blocks necessary for optimization
– Required analytical skills
– Industrialize response rate calculation
– Translate the marketing plan & strategy into an optimization algorithm
– The optimization process
– Some results
– Benefits & drawbacks
– Questions
SAS Belux Forum 2008 | Manuel Piette | 24 May 2017 | 2
Estimate
Evaluate Automate
Innovate
Fortis  RBB  Analytical & Predictive marketing
– Fortis is an international provider of
banking and insurance services to
personal, business and institutional
customers. We deliver a total package of
financial products and services through
our own high-performance channels and
via intermediaries and other partners…
Fortis
Retail Banking
Belgium
…
…
Marketing
Marketing
Intelligence
…
– Analytical & Predictive marketing is a team
dedicated to transform marketing needs
into reality by using data mining
techniques and state-of-the-art solutions
SAS Belux Forum 2008 | Manuel Piette | 24 May 2017 | 3
…
Estimate
Analytical &
Predictive
marketing
Evaluate Automate
Innovate
Building blocks necessary for optimization
– Build an analytical team with people having the required skills
– Industrialize your process to compute response rate automatically for each customerproduct pair
– Understand the business issues and convince management to solve it in a scientific way
– Translate the marketing plan & strategy into an optimization algorithm
– Integrate the solution in our marketing environment
Analytical dream team
Automate
response
rate calculation
Convince
Management
SAS Belux Forum 2008 | Manuel Piette | 24 May 2017 | 4
OR
Translation
Estimate
Integration
Evaluate Automate
Innovate
Required analytical skills
Generated business value by aCRM
Business Oriented & Computing & Data mining
+/- : Product/need driven solution
Feedback by product/need
Optimization
Predictive
Model
Business Oriented & Computing
+/- : Subjective approach
No feedback loop
Profiling
Model
Business Oriented & Computing
& Data mining & Operational Research
+/- : Customer centric solution
Marketing plan solution
Automatic feedback loop
OLAP
Queries
Complexity
SAS Belux Forum 2008 | Manuel Piette | 24 May 2017 | 5
Estimate
Evaluate Automate
Innovate
Industrialize response rate calculation : the process
Model Normalisation
Model construction
Business definition
Metadata Model transfer
Monitoring Results
Score 1
DMI Admin
Industrialisation
Score database
Score 2
Customer Data mart
Score 3
SAS Belux Forum 2008 | Manuel Piette | 24 May 2017 | 6
Estimate
Evaluate Automate
Innovate
Industrialize response rate calculation : The score database
Score database
Done automatically
every month
Id customer
1
1
…
1
2
…
2
…
1000001
1000001
…
1000001
…
id score
Model 1
Model 2
Id customer
1
2
3
4
…
1000001
…
T(Score 1)
High
DateScore Score
T (Score)
31/12/2003
10% High
14/10/2004
2% low
Model p
Model 2
14/10/2004
14/10/2004
Model p
14/10/2004
3% low
Model 1
Model 2
31/12/2003
14/10/2004
6% Meduim
1% low
Model p
14/10/2004
5% low
High
low
T(Score 2)
low
low
Medium
low
Medium
low
SAS Belux Forum 2008 | Manuel Piette | 24 May 2017 | 7
15% Medium
1% low
…
T (Score p)
Medium
low
High
low
low
Estimate
Evaluate Automate
Innovate
Translate the marketing plan & strategy into an optimization algorithm
• The business context :
• A marketing plan focused on sales
objectives and customers’ satisfaction
• The translation :
• Generate the best leads (offers) maximizing
our expected sales revenues respecting the
product mix strategy and contact strategy
• A lot of customers with different needs
and different service usage
• Appetite scoring
• A lot of marketing campaigns foreseen
• Integrate every contact in only one
optimization
• A limited budget, resources availability
and time to act
• Respect Constraints
Maximizing + Constraints problems
SAS Belux Forum 2008 | Manuel Piette | 24 May 2017 | 8
Operational Research solutions
Estimate
Evaluate Automate
Innovate
Translate the marketing plan & strategy into an optimization algorithm
The operational algorithm at hand :
• The “natural” solution
 Linear programming with SAS OR : The SAS LP procedure is used to optimize a linear
function subject to linear and integer constraints. Specifically, the LP procedure solves the
general mixed-integer program of the form :
Max c’x
Subject to :
A1x ≥ b1 and A2x = b2 and A3x ≤ b3
l≤x≤u
• The difficulties :
 decision variables (xijc : propose the product j to the customer i by the channel c) are
binary and there are plenty of them : # customers * # product proposed * # channel  the
number of possible combination where to search the best solution was about :
± 2 (12 000 000) : not reachable with standard computer
• The retained solution
 A mixed integer programming approach (Linear + Binary Integer Programming) + a lot of
SAS macro permitting us to industrialize the all process.
SAS Belux Forum 2008 | Manuel Piette | 24 May 2017 | 9
Estimate
Evaluate Automate
Innovate
Translate the marketing plan & strategy into an optimization algorithm
– A function to maximize :
 of leads value =  Hit RatioLead * DLTVLead
=    [xijc*P (Productj=1|customeri contacted by channelc) * DLTVij]
– Constraints : # leads allowed for our contact manager, maximum # leads per customer, minimum and
maximum # leads per product, contact strategy
Customer
Sample for a small customer base
Product’s Lead value
 of leads
value =
5 leads in total
composed by :
2 red, 1 black, 1 yellow, 1
dark grey
+ Max 1 lead per
customer
SAS Belux Forum 2008 | Manuel Piette | 24 May 2017 | 10
MAXIMUM
While
respecting all
constraints
Estimate
Evaluate Automate
Innovate
Optimization Process : Leads generation and self learning
Offer
Life time Value
Lead generators
Marketing Plan
Sales capacity
Max leads customer
Leads value
Optimization
Optimized Leads
Feedback loop to align
optimization to reality
Hit ratio
SAS Belux Forum 2008 | Manuel Piette | 24 May 2017 | 11
Contact & Sales
Estimate
Evaluate Automate
Innovate
Some results
Acquisition : Product X
Hit Ratio (production between : begin date to end date + 1 month)
14,0%
12,0%
The score band 19
generates three times
more sales than a 14
10,0%
8,0%
Tr
6,0%
4,0%
2,0%
0,0%
12
13
14
15
16
17
18
19
Scorebands : 19 = top5%, (18+19) = top 10%, …. , 0 = worst 5%
SAS Belux Forum 2008 | Manuel Piette | 24 May 2017 | 12
Estimate
Evaluate Automate
Innovate
Benefits and drawbacks
– Benefits
– The leads distributed follow a general strategy and no isolated campaigns anymore, take care of
our customers and take into account max profitability for the bank.
– An efficient algorithm was quickly developed with SAS OR software
– All the constraints and creative ideas of the marketers have been implemented “easily”
– The true hit ratio of campaign is directly entered into the optimization process
– Boosting the consciousness of the importance of propensity score and linking better predictive
modeling with marketing campaigns
– Low cost development
– Drawbacks
– Maintenance is time consuming
– Not integrated in one package with nice reporting capabilities (as it is in SAS MO, …)
SAS Belux Forum 2008 | Manuel Piette | 24 May 2017 | 13
Estimate
Evaluate Automate
Innovate
Getting you there.
Thank you
SAS Belux Forum 2008 | Manuel Piette | 24 May 2017 | 14