Marketing Optimization Example
Maureen McClatchey, Ph.D.
mmcclatchey@q.com
1/23/2013
Denver SAS User's Group presentation
1
Quote from Yogi Berra
“BASEBALL IS 90% MENTAL AND
THE OTHER HALF IS PHYSICAL”
1/23/2013
Denver SAS User's Group presentation
2
What is marketing optimization?
• Optimization enables us to determine
– the optimal set of customers to target in a
marketing campaign and
– the optimal communications (offer type) to use
for each customer.
1/23/2013
Denver SAS User's Group presentation
3
Marketing Optimization enables us to
• 1) determine the
optimal set of
customers to target in a
marketing campaign
• 2) and the optimal
communications to use
for each customer.
1/23/2013
• 3) You can choose the
objective to be
optimized. For example
– Maximize expected
revenue or profit
– Minimize expected cost
of campaign
– Maximize total number
of expected responses
Denver SAS User's Group presentation
4
Marketing Optimization Example:
• Business question design tailors predictive models
• Models applied to customers calling in to
Telecommunications Call Centers
– Customers asked for permission to use their
proprietary information as part of the call before
marketing begins.
• Partnership and collaboration among marketers, IT
and statisticians
1/23/2013
Denver SAS User's Group presentation
5
Goal of Marketing Optimization
• The goal is to obtain an assignment of each
customer to an offer type that optimizes the
objective
– e.g., maximize expected profit
• At the same time satisfy various marketing
constraints
– e.g., budget constraints, # offers restrictions,
channel capacities, contact policy restrictions
1/23/2013
Denver SAS User's Group presentation
6
Marketing Optimization Input Tables
• Input tables to eliminate ineligible assignments of
customers to offer types
– Customer table
– Customer table variables:
•
•
•
•
•
•
•
•
•
Identification number,
Location,
Probability( Attrition),
Revenue,
Expected Value(Attrition) = Probability(Attrition)*NPV,
Automatic payment for services,
Product subscriber,
Credit rating,
Demographic cluster values
– (macro or micro)
1/23/2013
Denver SAS User's Group presentation
7
How Does Lifetime Value Fit In?
• Calculate Lifetime Value (LTV)
• Create a rule so that customers with the
highest expected value of retention also have
the highest LTV
• Optimize the objective
1/23/2013
Denver SAS User's Group presentation
8
Campaign Table
1/23/2013
Campaign_Cd
Campaign_Desc
Camp_1
Retention campaign 1
Camp_2
Retention campaign 2
Denver SAS User's Group presentation
9
Communication Table
Campaign_Cd
Communication_Cd
Avg_Exp_Val
Avg_Prob
Camp_1
Comm_1
1
1
Camp_1
Comm_2
1
1
Camp_2
Comm_3
1
1
Camp_2
Comm_4
1
1
1/23/2013
Denver SAS User's Group presentation
10
Control Table
Campaign_Cd Communication_
Cd
Column_Nm
Numeric_Measure
Camp_1
Comm_1
Prob_Attrition_Reason1
Prob
Camp_1
Comm_2
Prob_Attrition_Reason2
Prob
Camp_2
Comm_3
Prob_Attrition_Reason3
Prob
Camp_2
Comm_4
Prob_Attrition_Reason4
Prob
Camp_1
Comm_1
Exp_Val_Attrition
Exp_Val
Camp_1
Comm_2
Exp_Val_Attrition
Exp_Val
Camp_2
Comm_3
Exp_Val_Attrition
Exp_Val
Camp_2
Comm_4
Exp_Val_Attrition
Exp_Val
1/23/2013
Denver SAS User's Group presentation
11
Additions to MO
•
•
•
•
Constraints
Minimum Responses
Contact Policies
Attrition probabilities in the customer table
need to be calibrated to recent behavior.
– Can be handled with a multiplier in a look-up table
1/23/2013
Denver SAS User's Group presentation
12
Additions to MO (cont’d)
•
•
•
•
•
Create a project
Create a scenario
Calculate the objective
Maximize adjusted profit
Expected value = probability(retention)*net
present value
1/23/2013
Denver SAS User's Group presentation
13
Additions to MO (cont’d)
• Enter constraints and contact policies
• Idea: Use a sequential algorithm at first. Then
use the sequential algorithm to create a
customer table in SAS. Compare results of
sequential algorithm to results using
Marketing Optimization.
• Optimize a scenario
• Results: Optimal offer for each customer
1/23/2013
Denver SAS User's Group presentation
14
Think about optimization
• What are we optimizing?
– Please carefully consider. Is there no harm?
– What are the benefits of optimization in your
biomedical research/pharmaceutical/business
setting?
• Think about what you are doing!
– Slow down a bit and reflect
– Ask yourself, “What are the pros?” “What are the
cons?” and most importantly, “What are the probable
consequences from this work?”
– Then do the ethical thing!
1/23/2013
Denver SAS User's Group presentation
15
Wish list
• Build in an ‘after-the-fact’ evaluation
component.
– What worked?
– What did not work?
– Quality improve the system
– Repeat recursively
1/23/2013
Denver SAS User's Group presentation
16