Transcript Slide 1
Marketing Optimization
Using SAS
Randy Sherrod
[email protected]
March 2008
1
Discussion Topics
What is the impact of marketing investment on
business metrics, e.g. sales?
How can we determine the level of marketing
investment that optimizes return?
What data is required?
What techniques are available?
2
Overview of Analytic Process
Data Collection: Historical Sales,
Distribution Channel, Pricing,
Marketing Investment, Competitor
Behavior, International
Macroeconomic Data
Data
Collection
Modeling
Optimization: Use the econometric
model as an input to an optimization
engine that identifies optimal sales and
marketing investment levels
Optimization
Modeling: Develop Econometric
Model(s) relating Historical Sales
with important drivers of business
Results
Results: Compares optimized
investment levels with actual,
yielding insight into opportunity to
increase sales through marketing
reallocation
Source: Cisco SMO
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Econometric Model Quantifies Relationship Between
Bookings and Drivers – First Step to Driving Optimal
Resource Allocation
Inputs
Outputs
Pricing
Distribution Channel:
Sales People, Resellers,
etc.
Marketing Investment
Econometric
Model
Driver Elasticities
Predicted Sales
Macroeconomics
Competitor Dynamics
etc
Source: Cisco SMO
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Elasticity Measurements that Quantify the Relationship
Between Drivers and Bookings
Definition
Relationship of Sales & Marketing
Investment
Elasticity measures the responsiveness
of Sales to changes in drivers,
calculated as:
Diminishing Returns, Elasticity<1
x
%∆ sales / %∆ driver
x
x
x
x
Relevant Cases
Sales
x
x
x
x
x
x
Elasticity<1 (inelastic):
Percentage change in sales is less than
percentage change in driver (ex. Increasing
marketing investment by 1% leads to less
than 1% increase in sales)
Elasticity>1 (elastic):
Marketing Investment
Percentage change in sales is more than
percentage change in driver
Source: Cisco SMO
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Background Observations
determine
the optimal level
of sales
force and
How
Whattorange
of elasticities
can we
expect?
marketing?
ForceSales
(+) Force=$400M, Marketing=$50M,
Sales
Initial Values:
Sales=$1B.
Total
Marketing
(+)
Estimated Elasticities: Sales Force=0.40,
TV (+)
Marketing=0.20
Suppose
there is an
Paid Search
(+)additional $40M to allocate, how
do you split between Sales Force and Marketing to
GDP
(+) Sales?
maximize
$40M=10% of Sales Force0.40*0.10*$1B=$40M
What
is the impact
increase
in Salesof GDP on marketing and
sales? What might this mean for the optimal
$40M=80% of Marketing0.20*0.80*$1B=$160M
level increase
of investment?
in Sales
6
Modeling Possibilities
Framework
Log-linear models with SAS:
1. Proc GLM
2. Proc Reg
3. Proc Surveyreg
4. Proc Genmod
5. Proc Mixed
6. etc.
Output from these procedures quantifies
the impact of marketing on sales
Source: Cisco SMO
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Modeling Details
Framework
Log-linear model with customer-level fixed effects:
Log Salesit=αi+β1log Competitor Advertisingt-1 + β2log Sales Forcet-1 + β3log
Marketingt-1 + β5log Cust Satisfactionit-1 + β6log GDPt-1 + Seasonality
Where:
i=customer
t=time
(-1)=lag 1 QTR
1. Imposes constant elasticity
2. Allows for many possible
response curve shapes
3. Explicitly accounts for synergies
between drivers
Source: Cisco SMO
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Modeling Details cont.
SAS Implementation
proc surveyreg;
class customer;
model log_sales=customer log_comp_advertising_1 log_sales_1
log_marketing_1 log_cust_satisfaction_1 log_gdp_1 q4 /noint solution;
cluster time;
Creates cluster-consistent standard errors
quit;
Estimated model can then be solved for optimal levels using proc
optmodel.
Source: Cisco SMO
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Questions?
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