1. Marketing
Optimization
Modeling
Maximising ROI with your
current marketing budget

2. About Us
 Bottom-Line Analytics LLC is a consulting group focusing on marketing
optimization modeling.
 Our modeling experts have a total of over 100 years of direct experience
with marketing optimization modeling. This includes direct experience in over
35 countries and dozens of product categories.
 We are dedicated to the principles of innovation, excellence and
uncompromising customer service.
 Most important, however, we are dedicated to getting tangible and positive
business results for our clients.

3. Our experience

4. What is Marketing Optimization Modeling?
• A mathematical technique used to indentify and quantify the relationships
between your sales and the factors that influence them
Macro-
Economic
Factors
Social Media Distribution
Other Earned
Price
Digital Media
Sales
Mass Media:
Paid Digital
TV, Radio,
Media
Print, OOH
Promotion Seasonality

5. Visualize!
• If you will, a system whereby you can accurately predict the
impact of your marketing plans in advance.
• A tool which will provide a precise estimate of the return-
on-investment from your marketing budget and no more
cat fights with finance.
• A capability where you can be confident that every
marketing expenditure for each of many initiatives is
deployed to generate maximum growth.
• A Pipedream? Let Bottom-line Analytics prove to you how
this vision can become reality.

6. MMO helps to answer basic questions
 What are the most effective marketing channels – TV, Radio,
Outdoor, Print or Digital?
 What has been the ROI of paid search and banner ads?
 How effective is social media?
 Which marketing messages are most effective in driving sales?
 How responsive are my customers to changes in price?
 What is the most effective month-by-month plan for deploying my paid
and earned media?
 Does moving from a 30 to a 15 second commercial rotation make economic sense?
 What is the best way to allocate my marketing budget?

7. What makes us different?
1. We can help to reduce the waste in your marketing spend by optimizing it
across media channels with the highest ROI.
2. Our unique modeling approach allows us to quantify the synergistic effects of
multi-channel integrated marketing. Traditional media mix methods do not
allow for simultaneous and synergistic effects to be determined.
3. We have pushed the boundaries in modeling excellence and are able to measure
the impact of social buzz by incorporating our proprietary SEI (Social
Engagement Index)
4. We can show you how to increase sales between 4 – 8% with your current
marketing budget alone.
5. Our project turnaround time is only 6 weeks (subject to data availability)

8. Marketing
Optimization
Modeling
Deliverables

9. A Highly Predictive Sales Model
Our modeling technique proves to be highly predictive. We deliberately holdout
approximately 10% of the dataset to test for accuracy.
700,000
600,000
500,000
Overall predictive accuracy = 97.8%
400,000
Actual
Model
300,000
200,000
100,000
0
01.02.05
02.06.05
03.13.05
04.17.05
05.22.05
06.26.05
07.31.05
09.04.05
10.09.05
11.13.05
12.18.05
01.22.06
02.26.06
04.02.06
05.07.06
06.11.06
07.16.06
08.20.06
09.24.06
10.29.06
12.03.06
01.07.07
02.11.07
03.18.07
04.22.07
05.27.07
07.01.07
08.05.07
09.09.07

10. Overall Sales Decomposition
Decomposition of sales provides a snap shot of the overall importance of media
and marketing in driving total sales. In this case, 31% of total sales revenues are
“due to” marketing expenditures.
68.9% 31.1%

11. Sales Decomposition over Time
Decomposition of sales across time enables us to view the incremental
revenue contribution of marketing and promotional activity for specific
campaigns.
70,000,000
Incremental impact of back-to-school marketing efforts Online Paid Search Branded
60,000,000 Online Banners Events
Radio Seasonal
50,000,000 Print Multi-Advertiser Coop
Print Branded
Xmas Promo DM Campaign
40,000,000
Winter Care DM Capaign
Summer Care DM Campaign
30,000,000
Spring Skin DM Campaign
Valentines Day Campaign
20,000,000
Media TV Branded
Media TV Events
10,000,000 Media TV Seasonal
Baseline sales momentum Media TV Multi-Advertiser Coop
0 Media TV Single-Advertiser Coop
05/01/2007
02/03/2007
27/04/2007
22/06/2007
17/08/2007
12/10/2007
07/12/2007
01/02/2008
28/03/2008
Macro-Economy
Baseline

12. Marketing Return-on-Investment
The first step in improving marketing productivity is to determine precise financial
returns to marketing spending by campaign/activity.
Least efficient
channels/investments

13. Optimal spend solution across all channels
We conduct a mathematical optimization of your marketing spend and show you how to
generate between 4-8% higher revenues without increasing total marketing investment.
100%
90%
Xmas Promo DM Campaign
80%
Fall DM Campaign
Summer-DM Campaign
70%
Spring DM Campaign
Valentine's Day DM Campaign
60%
Online.Pd.Search. Branded
Online-Banners. Events
50%
Radio-Seasonal
Print-Branded
40%
Print-Multi-Advertiser Coop
Media-TV-Multi-Advertiser Coop
30%
Media-TV-Single Advertiser Coop
Media-TV-Branded
20%
Media-TV-Events
Media-TV-Seasonal
10%
0%
Incremental Revenue 000 Current Spend 000 Optimal Spend 000

14. Play out marketing scenarios
We can provide an interactive dashboard that allows you to simulate different
marketing mix scenarios and the resultant impact on sales.

15. Innovation
Unique Insights

16. Innovations: Multi-dimensional Media Measurement
Long Term
Effects Message
Mix
Copy
Short-Term
Quality
Effects
Effects
Social
Synergistic
Media
Effects
Buzz Effect

17. Assess marketing synergies
Marketing synergies can be assessed through simultaneous activation of campaigns.
The results of combined activation are always greater than the sum of the parts. This is a
clear indication of synergies from running truly integrated campaigns.
Print Media & Paid Search Synergies Direct Mail & Email Synergies
Revenue (£)
Revenue (£)
+31%
+23%
Print Media & Online banners Synergies Outdoor & Online Synergies
Revenue (£)
Revenue (£)
+42% +28%

18. Measuring Social Media
 Using linguistic theory we have devised a
metric that captures the behavioral patterns
of social networks.
 Our net positive social-media "engagement"
(SEI) mirrors company seasonal patterns
suggesting that the metric captures more
than just social networks, with a correlation
of 87%
 The SEI is used as a reflection of total
"word-of-mouth" and the consumer
experience

19. Developing the Social Engagement Index (SEI)
1. Mine all brand related social media
reviews and commentary.
2. Parse into positive & negative
Positive Negative review groups
Reviews Reviews
3. Apply Social Engagement Index
algorithm to “score” reviews
Net Positive SEI Index
Positive Negative
Scores Scores
4. Time code by week and aggregate metrics

20. ACID TEST: SEI has proven linkage with brand sales
 The linkage & correlation to sales
over time shows that SNI has
predictive power
 When incorporate this metric into a full
marketing mix model we see evidence
that this measurement is
representative of “word-of-mouth”
effects on brand performance.

21. Relative Importance of Social-Media Channels in driving
consumer engagement and brand sales
Much like other marketing and media metrics, we can deconstruct the different
elements of our SEI metric into the channels driving social engagement and brand
sales.
Source: Nielsen BuzzMetrics data as of November 27, 2011

22. Case Study One: A Retail Bank
Business objective: A mid-sized retail bank saw consumer loans drop 30% during
the Great Recession. Now, due to efforts by the Central Bank, consumer loan rates have been
dropping. Current rates of 6% are expected to drop to as low as 4% over the next two years. The
bank now has decided to step-up its marketing spend and efforts in order to reverse trends in loan
sales.
Solution: We undertook a comprehensive marketing-mix modelling effort which quantified
the impact of media, direct marketing and digital advertising on loan demand. In
addition, variables like GDP and consumer APR rates were included in the predictive model.
Result: Our modelling efforts estimated that every 1 percent reduction in consumer interest
rates has about a +11% impact on loan demand. Because of the “synergy” between media and
interest rates, this growth could multiply by almost a factor of 2X. One year after
implementation, the bank’s loan demand increased +27 percent and the client also increased its
local market share for consumer loans from 18 to 23 percent!

23. Case Study Two: Major USA based beverage & food retailer
Business objective: Client has suffered 18 months of declining sales due to the
global recession. They needed a new idea that would help re-charge sales and
growth, across their network of 15,000 stand alone retail stores. Our task was to measure and
compare returns from test markets for a new product. This product was a radical departure from
their common product offerings and many in their marketing department were sceptical of its
success. The test involved two markets. One market had minimal marketing and merchandising
support, while the other had the national equivalent of $50 million in marketing and advertising.
Solution: The marketing mix models were developed and set up such that we could measure
not only the impact of media and marketing on the new brand, but also the incremental impact or
lift this product launch had on total outlet sales.
Result: Our models found a high return to the heavy spend marketing of $7.89 per dollar
investment. We also found that this product launch actually stimulated a +3% increase in total
store or system sales. One quarter after launching this product nationally, this client reported its
first quarter of profit increase and growth in same-store sales in 18 months.

24. Case Study Three: A Hotel Chain
Business objective: Client is a major hotel chain consisting of 350 properties ranging
from extended-stay type of units to very high-end luxury hotels in resort areas. In 2009, this chain
was just coming off of a major downturn due to a lapse in business travel and conventions from
the Great Recession. They needed to follow the path outlined by Tom Davenport’s Competing
with Analytics and leverage marketing-mix models in order to gain competitive advantage in their
highly competitive industry.
Solution: We have conducted a series of three marketing-mix models by property and region
for this client. Each engagement identified opportunities to optimize their marketing spend and
generate growth from +8 to +12% by moving budge funds from less to more productive
marketing activities.
Result: From the initial engagement, the clients annualized rate of growth has accelerated
form -3 to +6 to +11 percent increase in revenue bookings year-over-year. The improved growth
and profitability has further enabled the chain to free up capital in order to make a key acquisition
that will expand their total footprint capacity by 20 percent.

25. Journey to increase ROI and Sales
• Initial meeting. A critical meeting where we understand your current
Step 1 business strategies and campaigns and jointly develop project objectives
• Data collection. We will work with local IT, Data warehouse experts and
Step 2 media agency to collect all relevant data.
• Data assimilation and review with client. Review and approval of all data
Step 3 inputs.
• Analytics & Modeling to provide key deliverables
Step 4
• Face to face presentation
Step 5
• Ongoing follow-ups and delivery of interactive simulator
Step 6

26. Contact Details
Michael Wolfe Masood Akhtar
Principal EVP EMEA
Bottom-Line Analytics, LLC Bottom-Line Analytics, LLC
mjw@bottomlineanalytics.com ma@bottomlineanalytics.com
www.bottomlineanalytics.com
404.841.1620
678.314.8446 +44 7970 789 663
metricsman2010 Masood.Akhtar97