This document outlines the steps and timelines involved in a typical MarketSim modeling project. It begins with an initial kick-off and data gathering phase that takes 1-3 weeks. Then 4-5 weeks are spent on model development and calibration. Preliminary results are presented after 1 day. Recommendations are developed over 1-n weeks depending on complexity. Results and a second training session are delivered after 1/2 day. A 4-week cycle is established for ongoing data updates and projected results. Typical model accuracy is 5% error at the brand level and 10% at the SKU level. Case studies demonstrate how MarketSim can be used to optimize pricing, distribution, and marketing mix to increase profit margins.

1. 1
MarketSim Modeling
Key elements

2. 2
Steps in a MarketSim project
Item Detail Timeframe Notes
Kick-off & Business
question refinement
Understand the category
Set data gathering scheduling
1 to 2 days
ROMI Training First session ½ day
To the wider marketing
team
Data gathering See separate sheet 1 to 3 wks
Depends on Market
Research sophistication
Data set validation
Initial data validation, check for
completeness
2 to 3 days
Model development and
calibration
Depends on completeness
4 wks to 5
wks
Depends on category
complexity
Preliminary results
presentation
With key decision-maker to make sure
results make sense, deepen business
question understanding
1 day
Includes:
ROMI, Brand elasticity,
price elasticity,
distribution elasticity
Develop
recommendations; answer
business questions
Run simulations to perform
optimization, run sensitivity analyses
1 to n wks
Depends on business
question complexity
ROMI Training
Second session combined with results
delivery
½ day
To the wider marketing
team
Begin 4wkly cycle Develop data update timing & planning ½ day

3. Data sets
 Scanner/Transaction data – Nielsen/IRI
 Price (promoted/unpromoted) by brand by SKU by channel)
 Distr. (weighted distribution) by brand by SKU by channel
 Display/Feature (weighted distribution) by brand by SKU by channel
 Digital/social
 Own - Adobe, Google analytics/Facebook Insights and others
 Competitive – SocialBakers
 Brand Imagery – monthly, quarterly, 6-monthly, annually, (whatever is
available. If none available, field a study at begin and end of project)
 Brand association scores
 Initial awareness and persuasion; Prior use
 Usage and Attitudes for general category knowledge and dynamics
 Mass Media – From agency
 PR – if available for major events
 BTL (Trade) – From sales team for costs of consumer/trade promotions
 Product attribute (functional) breakdown
 Generated with help from client for functional attributes. This can also be read from
IRI product classifications
 Product profit margins by SKU – only needed if optimizing price or if ROI is
desired
 Internal data sources

4. MarketSim timeframes
 Strategic marketing decision support
4
Initial conditions
• Awareness
• Penetration
• Etc.
Initial agent learning
• (typically 6mo.)
Calibration
• (typically 24mo.)
Validation
• (typically
6mo.)
4wkly update process
Simulation/projection
• (12 or 24mo.)
 Validation is always the last 6 months. As opposed to statistical
modeling where the validation can be from any time period.
Because ABM has a history, it needs to be the last period.Today
3yrsago

5. MarketSim tactical marketing
decision support (4-weekly cycle)
 Tactical marketing decision support – rolling analysis & optimization
5
Actual data Projected data sets
Model re-validation
Projected results
We recommend beginning
with a 4weekly cycle, then
possibly moving to a bi-
weekly or weekly cycle later
on.

6. 6
Model & Simulation
Veracity
6

7. Typical model veracity
 At 4-weekly level comparing real sales to simulated sales
 5% MAPE at the brand level
 10% MAPE at the SKU level
 Better for larger SKUs
 Worse for smaller SKUs

8. Agent population v MAPE Error
 For a single brand (Unit sales), represents confidence
level of simulation agent population
0.0%
2.0%
4.0%
6.0%
8.0%
10.0%
25k 50k 100k 200k
%Difference
Population Size
MAPE Error v. Population Size

9. 9
Case Study
MarketSim™ Strategic Insights
FMCG Case Study: Food
9

10. 1.5
1.3
1.0
4.8
2.4
1.8
-
1.0
2.0
3.0
4.0
5.0
BTL Digital Billboards Print TV-Promo TV-Thematic
mROMI
mROMI Factors – PREMIUM 2010
mROMI - For every dollar spend on media, this is the incremental profit margin generated. It is done
using marginal increases (of 10%) in the advertising (except Digital and Billboards)
Marketing mix recommendation: Reduce Billboards by 50%. Increase Print by 100%.
Focus on Promo. Cut BTL by 25%. No change to Digital.
10
Breakeven

11. 0
0.5
1
1.5
2
2.5
This brand is recommended by doctors
This brand has a taste that my child
likes
This brand gives the best affordable
nutrition
This brand makes me proud to buy it
for my children
This brand helps me to be a good
mother
This brand helps my child progress in
life
This brand helps my child to become
more intelligent
This brand helps my child to be better
everyday
This brands knows all there is to know
about nutrition
This brand brings my child excellent
nutrition
This is a brand I can trust
This brand helps my child get the most
out of life
This brand offers me good value for
my money
This brand helps my childs immunity
PREMIUM SEGMENT
Premium Segment: Consumer
preferences top attributes‘Brand recommended by doctors’ is top attribute. Taste is second. 2 of 3 targeted attributes
are in top preferred attributes of top 14
Recommend messaging theme: ‘This brand helps me to be a good mother’ and
‘This brand helps my child progress in life’
attributes
11
• Product centric
• Child centric
• Mom centric
BrandD
This brand helps me to be a
good mother
This brand helps my child
progress in life

12. 12
(60.0)
(30.0)
-
30.0
60.0
-30% -20% -10% 0% 10% 20% 30%
Price (rel.) elasticity -
PREMIUM
(M USD)
GUM
IF
(800,000)
(600,000)
(400,000)
(200,000)
-
200,000
400,000
600,000
800,000
-30% -20% -10% 0% 10% 20% 30%
Price (rel.) elasticity -
PREMIUM
(vol – 1,000Kgs)
GUM
IF
Relative price elasticity - Mainstream
12
Decreasing price versus the category by 5% delivers 14.9M US.
This price change is a relative price change to the rest of the category.
Price elasticity of all SKUs in Growing Up Milk (GUM) and Infant Formula (IF) in +/-10% range are
linear. For both IF and GUM, lowering price leads to more profit. Especially strong for GUM.
Care must be taken not to invoke a price war, if the overall price is changed in the category.
We recommend further simulations to optimize pricing between variants
-5%

13. 13
3.4 4.0
1.0
17.8
13.6
4.6
-
5.0
10.0
15.0
20.0
25.0
Total contr margin 2009 Total contr margin 2010 Total contr margin 2011Q1
Incr. contribution margin
due to 10% increase in wghtd distr perc. (M USD)
GUM Mainstream
IFT Mainstream
Scenario analysis: Wghtd distr %
13
In 2010 and 2011 the base wghtd distr percentage is less than 2009
21.2
17.6
5.6
Increasing distribution by 10% delivers 17.6M US. We recommend a distribution increase of at least 10% above
existing values for all SKUs. (some with lower current distribution will be higher, others with current higher
distribution won’t increase as much) The cost will be the investment in trade marketing plus internal sales costs.
(10% of Trade 3.9M USD + 10% of BTL 6.2M USD + ??? Sales)
D/L distribution is declining. It has impact on advertising effectiveness
TBD: What is the cost of 10% increased weighted distribution percentage? Is it more than the trade marketing
expense in 2010 of 38.5M US?
Increasing the wghtd distribution is a medium to long term effort

14. 90.8
21.7
17.3
14.4
13.1
10.9
1.5
(5.2)
2010 Margin Increase
Distribution
10%
Increase
Print 100%
Decrease
Pricing 5%
Decrease
BTL 20%
Existing
Stores
Increase
Promo TV by
33%
Cut
Billboards
100%
Decrease
Thematic TV
by 0.08
73.7M US
Summary recommendations
14
Initial results through uni-dimensional simulation indicate opportunity
for 73.7M US in incremental margin (6-cities)
Assumes no net increase in marketing budget
5.
2

15. 15
15
• Drive long term strategic
change in marketing decision-
making methods
• Provide training to over 2,000
senior marketers, globally
• Build consumer centric
software (MarketSim family of
products)
 North America
 Russia
 Malaysia
 Hong Kong
 Vietnam
 Kenya
 Strategic decision-making support  Global experience
Sri Lanka
Singapore
Japan
Morocco
Indonesia
Tanzania
+1 404-816-4344, Atlanta, USA
+65 9185-6443, Singapore
www.ProRelevant.com