Demonstrates the value of ROMI modeling (marketing mix) for a furniture retailers that turned around a stagnant growth situation.

1. Alpha
Furniture
Outlets
Marketing Optimization Model

2. Situation
• The following is a case study based on real data. Names have
been masked to protect confidentiality.
• Alpha Furniture Outlets recently hired a new CMO, Robert
Emory. Alfa suffered from anemic +1% growth and Robert
was charged to find ways to improve marketing productivity.
• Robert started by engaging in a marketing modeling project.
The purpose of this project was to determine what current
marketing activities were working and which were not. Most
importantly, the ultimate goal was to develop fact-based
evidence to drive and accelerate Alpha’s growth over the next
year.

3. Alpha Furniture Model Architecture
We begin with a framework or architecture for a brand model. The model will include
digital and mass media, Store Sales and Direct Marketing Campaigns
Digital Banner Ads
DM New Year Campaign
Digital Paid Search
DM Christmas Campaign
Store Sales
Competitor TV
National & Local TV
Press or Print Media
Radio & OOH Media
Seasonality
Weekly
POS Store
Sales

4. Model Validation
-1000
0
1000
2000
3000
4000
5000
1/5/2004 1/5/2005 1/5/2006 1/5/2007
Actual
Model
Variance
R2=96.1 Holdout R2=97.7 MAPE = +/- 7.7%
Holdout
Forecast
Below shows how our predictive model fits to actual sales and how well we were able to predict a blind holdout

5. About 6.3% of Alpha’s sales have been generated by marketing and advertising over
the past year. This equals 16.8 million in revenue from marketing. This is 2.88
revenue per dollar of investment and a net profit of $1.16 per dollar
93.7%
1.0%
0.9%
2.0%
0.5%
1.9%
6.3%
Alpha Sales Decomposition
Baseline
Campaign.NewYear
Campaign.Christmas
Campaign Store.Sales
Press
Internet
Outdoor
Radio
Local TV
National TV

6. Skipping the Christmas DM Campaign cost Alpha about 2% in
revenue growth. The largest factor driving positive growth was
Press or Print media. Overall growth is just 1.3%
-1.9%
-0.5%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.2%
0.4%
-2.5% -2.0% -1.5% -1.0% -0.5% 0.0% 0.5% 1.0%
Campaign.Christmas
Campaign.NewYear
Internet
National TV
Radio
Competitor3_Outdoor
Campaign Sales
Digital Banner Ads
Competitor1_Press
Competitor1_TVPress
Digital Paid Search
Basaeline
Outdoor
Competitor4_Press
Local TV
Press
Alpha Furniture Annual Marketing Variance
Annual % Variance Contr

7. Marketing Efficiencies: Revenue per $ Million is highest in print
followed by TV. Sales & Campaigns rather ineffective
-
2
4
6
8
10
12
14
16
0.01 0.01 0.02 0.14 0.66 1.09
3.94
5.97
11.46
14.22
RevenueMillions
Rev Per $MM
Rev Per $MM

8. Maximizing Marketing ROI. Increasing spending from $14.5 to
$18.3 million will generate additional +$0.8 million profit
-
5.0
10.0
15.0
20.0
25.0
30.0
1,120
1,130
1,140
1,150
1,160
1,170
1,180
1,190
1,200
0 10 20 30 40
Revenue
Marginal Cost
Marginal RevenueCurrent Spend
$14.5MM
Optimal spend where
Net returns maximized

9. Optimization recognizes the pivotal role of TV and Press. With
higher investments in these, Alpha can gain +4.3% ($48 million)
in revenue for the same budget
Contribution Current Optimal
National TV 9 0.05 1.08
Local TV 1,344 3.00 5.90
Radio 3 0.60 0.06
Outdoor 281 2.50 0.13
Digital Search & Banners 655 0.20 1.74
Press 1230 3.00 3.80
Campaign Sales 534 2.30 0.20
Campaign.Christmas 0 0.10 1.30
Campaign.NewYear 593 3.00 0.30
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
National TV
Local TV
Radio
Outdoor
Digital Search & Banners
Press
Campaign Sales
Campaign.Christmas
Campaign.NewYear
14.5 14.5