Marketing planning 3.0, a 5-part educational webcast series, kicks off with the talk from Copernicus' Jeff Maloy on the Holy Grail of marketing mix optimization--a virtual marketplace that makes it possible to evaluate the ROI of current marketing and media plans. Many marketers also are using this tool to simulate innovative marketing strategies and plans they have never tried before and forecast the likely results.

1. TRANSFORMATIONAL MARKETING MIX
OPTIMIZATION USING A VIRTUAL
MARKETPLACE
Jeffrey Maloy, Senior Vice President and Chief Marketing Officer
Tuesday, June 18, 2013

2. 2
WELCOME!
2 weeks, 5 webcasts, improved marketing effectiveness

3. 1. Transformational Marketing Mix Optimization Using a Virtual Marketplace
Date: Tuesday, June 18
Time: 1 pm EDT
Presenter: Jeffrey Maloy, SVP and CMO
2. Using a Virtual Marketplace to Evaluate Your Marketing Strategy
Date: Wednesday, June 19
Time: 1 PM EDT
Presenter: Eric Paquette, Senior Vice President
3. Optimizing Your Media Plan for the Bought-Owned-Earned World
Date: Tuesday, June 25
Time: 1 pm EDT
Presenter: Rolf Olsen, Vice President, Director, Marketing Analytics
4. Leveraging Marketing Investments with Marketing Mix Modeling
Date: Wednesday, June 26
Time: 1 pm EDT
Presenter: Irina Pessin, Managing Partner, Data2Decisions US
5. Marketing Analytics: 5 Things Every CMO Should Know
Date: Thursday, June 27
Time: 1 pm EDT
Presenter: Peter Krieg, President and CEO
3
SERIES SCHEDULE

4. For a PDF of this presentation and our advertorial on using big
data for marketing planning…
Email ami.bowen@copernicusmarketing.com
4

5. 5
WHO AM ?
Jeffrey Maloy
SeniorVice President
CopernicusMarketing Consulting& Research
LeadingourCPG practice
FormerDirectorof Marketing,with multiple brand managementand consumerinsightsassignments.
Developingrelationships with clients such as Kraft,P&G, Nestlé,and Hershey’s.
Helping myclients develop,execute and evaluate transformationalmarketingstrategies

6. THEN: NOW:
6
MARKETING IS BECOMING MORE COMPLEX

7. 7
FROM THIS…
27 4 11 18 25 1 8 15 22 29 5 12 19 26 3 10 17 24 31 7 14 21 28 5 12 19 26 2 9 16 23 30 6 13 20 27 5 12 19 26 2 9 16 23 30 7 14 21 28 4 11 18
$654,000
$654,000
$654,000
$654,000
$11,315,000
$11,315,000
$11,315,000
$11,315,000
$13,657,000
$13,657,000
$13,657,000
$2,962,000
$2,962,000
$2,962,000
$2,962,000
$1,200,000
$550,000
$550,000
$33,760,000
$33,760,000
$765,000
$765,000
$2,970,000
$2,970,000
$9,085,000
$2,325,000
$2,325,000
$1,025,000
$1,025,000
$525,000
$525,000
$225,000
$225,000
$64,920,000$64,920,000
$175,000 $175,000 $175,000
$75,000 $75,000 $75,000
$1,050,000 $775,000 $500,000
$450,000 $375,000 $200,000
$9,085,000
$255,000$350,000 $385,000 $385,000 $385,000 $255,000 $255,000$350,000 $350,000
$33,760,000
$255,000 $255,000 $255,000
$550,000
$5,627,000 $13,624,333 $9,985,667 $4,523,000
135 180 90180 135 90
35/83 43/107 27/5239/113 35/89 27/60
$483,000 $624,000 $305,000$670,000 $528,000 $352,000
285 243 243 243 132 265285 380 190
65/156 62/132 62/131 60/126 45/70 60/14263/155 70/210 54/106
$2,115,000 $1,275,000 $1,265,000 $1,335,000 $492,000 $974,000$2,053,000 $2,802,000 $1,346,000
200 168 166 163 82 163200 266 133
59/104 56/87 56/86 53/81 36/40 50/8257/102 64/135 46/68
$1,810,000 $1,020,000 $1,010,000 $1,080,000 $397,000 $785,000$1,738,000 $2,350,000 $1,125,000
77 50 34
M ay Jun
28/37 21/23 14/16
$312,000 $212,000 $130,000
CostJul Aug Sep Oct Nov Dec Jan Feb M ar Apr
66 HH GRPs/Week GM + DR TV 50/50 :30/:15
95 HH GRPs/week GM + DR TV 100% :30s 81 HH GRPs/week GM 35% :30s/65% :15s + DR TV 100% :30s
$1,200,000
45 HH GRPs/week DRTV Only 100% :30s
~45% reach/month
~55%+ reach/month
~50% reach/month + Dog Wet & Treats New Creative Launch (P4CB)
66 HH GRPs/wk GM + DR TV 100% :15
~45% reach/month

8. … TO THIS
8
Search
Aggregated Content
In-Store
E-Commerce
Content Syndication
Pre -Launch
Public Relations
Outreach to
Influencers
Sponsorships
Print Live Read Radio
Lifestyle PaidMedia
Paid Video
(TV, Digital)
AwarenessDriving Paid Media
Radio
WOM
Live Events
Paid Social
Mobile App Facebook App
Partnerships
YOURBRAND
HERE

9. 55% of CMO projects
utilize marketing analytics
before a decision is made
(Source: The CMO Survey, February 2013)
But…
72% of CEOs say
marketers are always
asking for more money
but can rarely explain how
much incremental
business it will generate
(Source: Forbes, 2011)
9
BUT NO “GET OUT OF JAIL FREE” CARD
?
WHO?
HOW MUCH?
WHAT?
WHERE?
WHEN?

10.  “Always On” Planning
 Sense and Respond
 Highly Targeted
 Paid, Owned And Earned Media
 Behavioral/ Programatic Buys
 Synchronized Swimming
 How and Why
Did It Happen
FROM:
 Marketing Plan Calendar
 Top-DownAllocation
 Mass Marketing
 Traditional Paid Media
 Demographic Buys
 Swim Lanes
 What Happened
TO:
10
A NEW APPROACH TO MARKETING AND PLANNING IS
NEEDED

11. “Traditional” Marketing
Evaluation Methods
 Regression-based(linear, top-
down) approaches
 Historical perspective
 Aggregate-level results
Most relevant in cases when:
 Less dynamic pace of change
 Less competitiveenvironment
 Heavier spending on traditional
(paid) media
 Less segmented market
 More conservative planning
approach (top-down allocation)
11
NEW TOOLS ARE NEEDED TO COMPLEMENT
“TRADITIONAL” TECHNIQUES

12. Enter: ComplexityScience
 A study of complex systems.
 Simulates how individual parts
(or “agents”) interact with each
other, and the likely outcome
for the system as a whole.
 Models dynamic, social
interactions.
What is an Agent:
 For our purposes, agents
generally represent consumers
or groups, and agent
relationships represent social
interactions.
 A discrete entity with its own
goals and behaviors.
 Mechanisms by which agents
interact can be described by
behavioral “rules.”
 May have the capacity to “learn”
(change the rules).
12
A COMPLEX MARKET REQUIRES COMPLEXITY
SCIENCE

13. Simulation models, such as
agent-based modeling is not
new.
Until recently, it primarily has
been used for simulating:
– Migration of species
– Spread of viruses and
diseases
– Supply chain
Now being used in fields in
which simulation modeling has
never been applied before
(markets)
13
TRULY “VIRAL” MARKETING

14. In the 2000s, some smart man asked this question:
“In this social age, why can’t
ABMs describe the spread of
marketing messages?”
Fortunately there
was no good answer.
14
WHY NOT MARKETING

15. A simulation approach to marketing mix optimization is especially
relevant when:
 Dynamic marketplace
 Forwarding-looking perspective
 Experimental marketing plans – paid, owned, and earned media
 Highly segmented market
 Want to understand impact on sales
and brand equity
 Test and Learn mentality
 Marketing never
sleeps
 Need to know
the How and Why
behind the What
15
WHY SIMULATION MODELING?
Bought Owned Earned

16. Marketing Plans
 Target Segments…….….
 Message Strategy……....
 Media Strategy (Paid,
Owned and Earned)….…
 Pricing Strategy……….…
 Product Strategy…….…..
16
CONNECTS NUANCES OF MARKETING PLANNING AND
EVALUATION

17.  Complex marketplace
 Diverse population
 Fragmented media
 “Always on” devices
 “Big Data”
Need for computing power
17
WHY NOW?

18. 18
TURNING 3V’S INTO 3W’S
How to turn “big data” into “smart data”?
 Answer: 3W’s:
When
Where
Why
Volume
Velocity
Variety
3 V’s
Economic
Data
Environ-
mental
Data
Media
Costs
POS
Data
Price/
Promotion
Data
Competitive
Data
GPS/RFID
Data
Survey
Data

19. 1. Build your “simulated society”
2. Assign “rules of engagement”
3. Calibrate and validate
4. Explore new frontiers
19
SO HOW DO WE BUILD THIS AMAZING MODEL?

20. First we build a “virtual” panel of agents:
Each agent is like a mini-database, waiting to be populated with data and
behavioral rules.
Panel must be representative
of relevant population on:
 Gender
 Age
 Income
 Ethnicity
 Corpo-graphics
 Geographic region
 Category incidence
21
1. BUILD SIMULATED SOCIETY

21. Establish decision rules for each agent and/or segment of agents:
How do they react when acted upon by:
• Other agents
• Marketing and Media
• External factors
Rules are based upon:
• Marketing sciences
• Secondary data (media consumption)
• Custom research (e.g., segment purchase behaviors)
• Top-down analysis (Marketing Mix Models)
• Advanced analytics
• Understanding of their “journey” and key decision points
22
2. PROGRAM THE AGENTS

22. 23
2. PROGRAM BEHAVIORS ALONG SHOPPER JOURNEY

23. Once rules are established, we run and refine the model until
results reflect “reality”:
24
3. CALIBRATE AND VALIDATE
 Examine model’s results, relative to
expectations
 Calibrate agent rules
− Are results logical,intuitive, reasonable?
− Possibly validate the modelon a “hold out” sample
 Proceed with caution
− As with any good model,results needed to be
combined with judgment

24. Now, we’re ready to dream. Test those risky plans in a risk-free
simulation.
25
4. EXPLORE NEW FRONTIERS
What if…
 Spend more/less?
 Shift to more digital tactics?
 Target new/different segments?
 Reposition brand?
 Competitive aggression?

25. Powered by CCM (agent-based simulation and
other advanced analytics), we analyzed multiple
strategic alternatives:
– Targeting strategies
– Messaging strategies
– Product focus
– Media mix and allocation
26
CASE STUDY
After multiple scenarios, we identified one that delivered…
Challenge
Analysis
Increase sales by +4-5% with a flat marketing budget.

26. + >$200 MM
+ >4% incremental revenue lift
27
CASE STUDY
Action
Results
From: To:
GM W 25-44 USH W 18-49
TV Digital, Mobile and Social
Holiday
Message
Promotional Message
Assortment
Focus
Bed & Bath Focus

27. 1. Simulation models (such as ABMS) can be
an effective tool in the analytic toolbox
2. Complex, dynamic models for complex,
dynamic markets
3. Simulate new, “stretch” scenarios
4. Understand the “how” and “why” behind
the “what”
28
CONCLUSIONS

28. Questions?
For a PDF of this presentation and our advertorial on using big
data for marketing planning…
Email ami.bowen@copernicusmarketing.com
29

29. USING A VIRTUAL MARKETPLACE TO EVALUATE
YOUR MARKETING STRATEGY
Eric Paquette, Senior Vice President
Wednesday, June 19, 2013
SAVE THE DATE (TOMORROW):

30. Jeffrey Maloy, SeniorVice President
(203) 831-2375
Jeff.Maloy @copernicusmarketing.com