Mapping the Future of
Marketing Success
Using MarketSim Agent-base Marketing Analytics
ABM Marketing Analytics
#PRMSTailWag
@ProRelevant
Objective

To show how agent-based modeling can work in consumer markets

To show how the MarketSim agent based modeling works (at least for the
purchase funnel)
MarketSim consumer behavior model
Consumer decision behavior
Purchase funnel
Probability of
seeing message
Relevance
Shopping
Inertia/loya
lty
Becoming
aware
Purchase
frequency
Purchase
Intent
Availability
The probability of choosing
one item over another is
based on the net utility
derived from each of these
three dimensions versus the
price to be paid for the item
Price
Probability of
choosing an item
$
¥
€
£
The modeling process
calculates a relative weight
for each dimension
MarketSim Animation
Purchase funnel



The following slides are an animation
to describe how Media drives
purchase intent and purchase
The impact of Pricing, Distribution
and Brand Relevance are also
important drivers of sales, and will be
made available in a separate
animation
The animation will progressively
describe the process, moving from a
simple example to a more complex
example
Probability of seeing
message
Becoming aware
Purchase
Intent
MarketSim Animation
Consumers
Agents
=>>

Agents represent consumers
 They
are virtual consumers
 They respond to market stimuli based on
rules and parameters you determine
 A full ABM describes consumer behavior
in a chosen category. When properly
calibrated it provides an accurate model
and simulation tool of real consumer
behavior in the category
Let’s begin
Example: Simplification 1: Media drives
Awareness. Awareness drives purchase.
Let’s assume that the only important consumer behavior is the ability for media
to drive consumer awareness
a)
The higher the awareness, the more items that would be purchased
b)
Media directly drives awareness: Awareness directly drives purchase
c)
Further let’s assume that everyone is not aware
Initial Awareness Simulation
Media
Investment
GRPs
Week 1
100
Consumers
Unaware
Consumers
Aware
Simulated
Purchases
1,125
Initial Awareness Simulation
Week 2
100
100
1,125
1,125
GRPs
Media
Investment
Week 1
Consumers
Unaware
Consumers
Aware
Simulated
Purchases
Initial Awareness Simulation
Week 2
Week 3
Week 4
Week 5
Week 6
Week 7
100
100
50
0
50
0
100
1,125
1,125
563
0
563
0
1,125
650
875
575
165
300
175
315
GRPs
Media
Investment
Week 1
Consumers
Unaware
Consumers
Aware
Simulated
Purchases
Actual
Purchases
Difference
-
475
250
12
165
263
175
810
MAPE:
93%
Initial Awareness Simulation
Week 1
Week 2
Week 3
Week 4
Week 5
Week 6
Week 7
100
100
50
0
50
0
100
1,125
1,125
563
0
563
0
1,125
650
875
575
165
300
175
315
GRPs
Media
Investment
Replay:
Consumers
Unaware
Consumers
Aware
Simulated
Purchases
Actual
Purchases
Difference
-
475
250
12
165
263
175
810
MAPE:
93%
 This
model indicates that there is a
correlation between the hypothesized
media and awareness, and awareness and
purchase, but most likely there is
something else going on.
 A traditional MMM might estimate in this
way, if all the nuances of consumer
behavior aren’t properly included in the
model
Simplification 1:

This simplification is made up of 2 rules with 2 (or more) parameters
1)
Number of Aware Consumers = A * (Media GRPs)
2)
Product Sales = B * (Number of Aware Consumers)
Calibration

If these two rules are correct and if we know the advertising from the past and if
we know the past ‘real’ sales then we can determine the value of the parameters
A and B that provide the best ‘fit’ for our model


Best fit (Error) is defined as the average error per period between actual and simulated sales
For the above example we have A = 3 and B = 3.75

With these two values for these two parameters the fit (error) is 93%.

Could we get the fit to be better?

How could we improve the fit? Obviously there is more to marketing than a simple
relationship between advertising, awareness and sales. What about purchase
intent? What about brand relevance? What about loyalty?

Let’s try A = 3 +0% and B = 2.25 -33%

With these new values the error is (56%)
Awareness Animation Improved Nr. 2
Media
Investment
GRPs
Week 1
100
Consumers
Unaware
Aware
Consumers
Simulated
Purchases
675
Awareness Animation Improved Nr. 2
Week 2
100
100
675
675
GRPs
Media
Investment
Week 1
Consumers
Unaware
Aware
Consumers
Simulated
Purchases
Awareness Animation Improved Nr. 2
Week 2
Week 3
Week 4
Week 5
Week 6
Week 7
100
100
50
0
50
0
100
675
675
338
0
338
0
675
650
875
575
165
300
175
315
GRPs
Media
Investment
Week 1
Consumers
Unaware
Aware
Consumers
Simulated
Purchases
Actual
Purchases
Difference
-
25
200
237
165
38
175
360
MAPE:
56%
Awareness Animation Improved Nr. 2
Week 1
Week 2
Week 3
Week 4
Week 5
Week 6
Week 7
100
100
50
0
50
0
100
675
675
338
0
338
0
675
650
875
575
165
300
175
315
GRPs
Media
Investment
Replay:
Consumers
Unaware
Aware
Consumers
Simulated
Purchases
Actual
Purchases
Difference
-
25
200
237
165
38
175
360
MAPE:
56%
3rd Animation


For the above example we have A = 3 and B = 2.25

With these two values for these two parameters the fit (error) is 56%.

Could we get the fit to be better?
Let’s try A = 2 -33% and B = 3 +33%

With these new values the error is (54%)
Initial Awareness Simulation Nr. 3
Media
Investment
GRPs
Week 1
100
Consumers
Unaware
Aware
Consumers
Simulated
Purchases
600
Initial Awareness Simulation Nr. 3
Week 2
100
100
600
600
GRPs
Media
Investment
Week 1
Consumers
Unaware
Aware
Consumers
Simulated
Purchases
Initial Awareness Simulation Nr. 3
Week 2
Week 3
Week 4
Week 5
Week 6
Week 7
100
100
50
0
50
0
100
600
600
300
0
300
0
600
650
875
575
165
300
175
315
GRPs
Media
Investment
Week 1
Consumers
Unaware
Aware
Consumers
Simulated
Purchases
Actual
Purchases
Difference
-
50
275
275
165
0
175
285
MAPE:
54%
Initial Awareness Simulation Nr. 3
Week 1
Week 2
Week 3
Week 4
Week 5
Week 6
Week 7
100
100
50
0
50
0
100
600
600
300
0
300
0
600
650
875
575
165
300
175
315
GRPs
Media
Investment
Replay:
Consumers
Unaware
Aware
Consumers
Simulated
Purchases
Actual
Purchases
Difference
-
50
275
275
165
0
175
285
MAPE:
54%
In summary: a simple two rule model

The error has been reduced to 54% MAPE

But more could be done

This model uses only 2 simple equations


Media and awareness

Awareness and purchase.
But it doesn’t tell the whole story. There’s much more to it.
Why is this important

For new brands we can now determine the trade-off between driving
awareness and other valuable consumer behavior dimensions. Based on our
objectives and our brand’s status in the market we can now determine key
tactics and strategies to drive value for our brand.

More awareness would help small or newly launched brands

More purchase intent would help larger more well-known brands
Adding more realistic awareness

After purchase, a consumer is usually always aware and this awareness lasts
for a long time. It is a step-function:

Media leads to awareness

Consumers are either aware or unaware (1 or 0). There are no partial awareness states
as in the previous example

If the consumer isn’t already aware, there is some probability, they will become aware
when seeing an advertisement

Probability of becoming aware if they see the media 50%

Awareness (either 1 or 0) = The probability of becoming aware is dependent on the media
quality and seeing the media

Awareness leads to purchase = 3 per aware agent

Purchase leads to near permanent awareness
Animation with Awareness Nr. 4
Media
Investment
GRPs
Week 1
100
Audience
Consumers
seeing media
Consumers
Aware
Unaware
Simulated
Purchases
600
Media
Investment
GRPs
Animation with Awareness Nr. 4
Week 1
Week 2
100
100
600
1,200
Consumers
Audience
seeing media
Consumers
Aware
Unaware
Simulated
Purchases
Media
Investment
GRPs
Animation with Awareness Nr. 4
Week 1
Week 2
Week 3
Week 4
Week 5
Week 6
Week 7
100
100
50
0
50
0
100
600
1,200
1,500
1,500
1,800
1,800
2,100
650
875
575
165
300
175
315
Consumers
Audience
seeing media
Consumers
Aware
Unaware
Simulated
Purchases
Actual
Purchases
Difference
-
50
325
925
1,335
1,500
1,625
1,785
MAPE:
430%
Media
Investment
GRPs
Animation with Awareness Nr. 4
Replay:
Week 1
Week 2
Week 3
Week 4
Week 5
Week 6
Week 7
100
100
50
0
50
0
100
600
1,200
1,500
1,500
1,800
1,800
2,100
650
875
575
165
300
175
315
Consumers
Audience
seeing media
Consumers
Aware
Unaware
Simulated
Purchases
Actual
Purchases
Difference
-
50
325
925
1,335
1,500
1,625
1,785
MAPE:
430%
But this can be improved further

Awareness doesn’t usually lead directly to purchase

For those consumers that are aware, there is some level of purchase intent

Purchase intent is delivered by seeing an advertisement. The level of purchase intent is
dependent on the quality of the advertisement

Each ad delivers 1 unit of purchase intent for those consumers that see the ad and are aware

Purchase intent always decays (typically exponentially, e.g., 50% per period) – for our
example, we assume it is linear decay. It goes from 1 to 0.5 to 0.0

But there can be no purchase intent if the consumer is unaware

Awareness can be forgotten if the consumer doesn’t see an advertisement (over some
period of time). There is some probability of becoming unaware for those consumers
that are aware, but have never purchased in the category

If the consumer becomes unaware they lose their purchase intent

Let’s assume that purchase takes place if purchase intent reaches a certain level

The quality of the creative and the quality of the media placement determines the
level of purchase intent delivered to the consumers with each media impression
Animation with Awareness & Purchase Intent
Media
Investment
GRPs
Week 1
100
Consumers
Audience
seeing media
Consumers
Aware
Unaware
NoPurchase
Purchase
Intent
Simulated
Purchases
600
Media
Investment
GRPs
Animation with Awareness & Purchase Intent
Week 1
Week 2
100
100
600
900
Consumers
Audience
seeing media
Consumers
Aware
Unaware
NoPurchase
Purchase
Intent
Simulated
Purchases
Media
Investment
GRPs
Animation with Awareness & Purchase Intent
Week 1
Week 2
Week 3
Week 4
Week 5
Week 6
Week 7
100
100
50
0
50
0
100
600
650
900
875
600
575
150
165
300
300
150
175
300
315
Consumers
Audience
seeing media
Consumers
Aware
Unaware
NoPurchase
Purchase
Intent
Simulated
Purchases
Actual
Purchases
Difference
-
50
25
25
15
0
25
15
MAPE:
6%
Replay:
Media
Investment
GRPs
Animation with Awareness & Purchase Intent
Week 1
Week 2
Week 3
Week 4
Week 5
Week 6
Week 7
100
100
50
0
50
0
100
600
650
900
875
600
575
150
165
300
300
150
175
300
315
Consumers
Audience
seeing media
Consumers
Aware
Unaware
NoPurchase
Purchase
Intent
Simulated
Purchases
Actual
Purchases
Difference
-
50
25
25
15
0
25
15
MAPE:
6%
Some results


Purchase intent is available only for those
consumers/agents that are aware. Purchase intent
is different from awareness, where purchase intent
is a value as opposed to an on-off function like
awareness
The new parameters associated with this simple
animation are:
Purchase
Intent
Those agents that are aware have some level
of purchase intent
Simulation #4
Simulation #5
4
4
Aware of Media
2 (50%)
2 (50%)
Purchase Intent
-
3 (Aware + 50%
previous week)
600
900
430%
6%
Seeing Media (100 GRPs)
Simulated Purchases
MAPE
MarketSim Agent-Based Modeling

The preceding animations represent the findings of consumer behavior based
on many years of experience modeling consumer behavior in many categories
and markets.

There are other aspects not yet included in the animations that are necessary
to build a complete model

How do consumers respond to pricing

How does the in-store experience influence their purchases

How does their brand perceptions influence their purchases

How do these parameters get determined? What is calibration?

Calibration leads to best fit where the error rates between simulated lead to the
lowest level of error and the errors are as random as possible
What we do, who we work with

Industries

CPG / FMCG

Financial

Insurance

Regulated utilities

Beverages

Carbonated, spirits

Dairy

Infant Formula

Personal Care

Software / Internet

Telecom

Airlines
44
The ProRelevant Team




Guy Powell / Atlanta

MBA University of Chicago, Published author (x3 books)

Global Speaker & Trainer Marketing ROI
Ramesh Sundararajan / Singapore

Post Graduate Engineering from BITS, Pilani

Masters in Management from The Indian Institute of Management
Steven Groves / Charlotte

Publisher author (x2 books), 7 years Computer Associates

Global Speaker & Consulting Businesses on Online Marketing & ROI
Pulak Ghosh / Delhi

Professor Quantitative Methods and Information Systems (IIM, Bangalore)

Chief Data Scientist & Member of the Board of Advisors.
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#PRMSTailWag
@ProRelevant