1. Perspectives on Big Data
Digiday Exchange Summit
The New Programmatic Advertising Economy
Austin, September 19, 2013

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Source: Gartner
By 2017, CMOs will spend
more on technology
then their counterpart CIOs

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A Few Observations
1. Programmatic and even Big Data are just ubiquitous
industry terms. (What about DSP and DMP?)
2. Programmatic is not really about buying cheap media
Regardless that 20% of US Display Spending will be
Automated
3. Big Data has the potential to strategically solve
complex problems driving actionable marketing and
business intelligence to improve both efficiency and
effectiveness
4. Big Data is more about connecting structured and
unstructured data not about volume Zeta bytes or
petabytes
3

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A Few Observations
1. Attribution of Big Data is driven by:
 Variety : normalizing intelligent connections
between structured and unstructured data
types and sources
 Velocity: Speed of Real-Time-Decisioning
(addressing adaptive nature and
responsiveness of data)
 Volume : not about volume of data, but the
right data
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5. Requires New Approach, Talent,
Structures, Algorithms and Skill Sets
Old Marketing New Marketing
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6. Big Data Terroir
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Identify Predictive Patterns
Consumer as Patient Universe
Surgical/Forensic Approach to
Targeting Across all Media
Connecting the Right Structured and
Unstructured Data Sets
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7. It’s About Active Discovery and Metadata
Actionable Insights come in all sizes (Sparks and Fuses)
7
DMP/Media Partners
Predictive
algorithms
Dynamic/Fractional
Optimizations
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8.  A flexible approach in which marketers
respond quickly to their environment to
align consumer and brand goals and
maximize return on brand equity.
 Achieved through the integrated use of
fast- and slow-moving data sources to drive
actionable insights to adapt product,
pricing, distribution, and advertising.
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9. How Marketers Are Using Big Data
Netflix
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 Netflix used data to retain customers and
has reduced churn to under 4%
 Netflix tracks what customers
watch, search, their ratings, time of
day, day of week and device(s)
 75% of viewer activity is driven by their
personalization algorithm
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How Marketers Are Using Big Data
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 Target statistician Andrew Pole ran test after
test, analyzing the data, and before long some useful
patterns emerged:
 Women on the baby registry were buying larger
quantities of unscented lotion around the beginning of
their second trimester.
 In the first 20 weeks, pregnant women loaded up on
supplements like calcium, magnesium and zinc.
 Many shoppers purchase soap and cotton balls, but
when someone suddenly starts buying lots of scent-free
soap and extra-big bags of cotton balls, hand sanitizers
and washcloths, it signals they could be getting close to
their delivery date.
Target assigns every customer a Guest ID
number, tied to their credit card, name, or
email address with a history of everything
they’ve bought and any demo information

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Google Flu Tracker
Crowd Sourcing Data
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 Google developed an predictive algorithm based on
search trend data which was about two weeks faster
than traditional CDC methods of tracking flu
 This crowd source data enables CDC to be more
responsive to distribution priorities of flu vaccines
outbreak on a national and state level
 The math works like this: people’s location + flu-
related search queries on Google + some really
smart algorithms = the number of people with
the flu in the United States.
 However the algorithm needed to be modified based
on general interest and media which skewed data
 Lyn Finelli, head of the CDC’s Influenza Surveillance
and Outbreak Response Team, feels that such
crowdsourcing techniques continue to evolve and
show promise with other applications Flu Near You
and GrippeNet.fr

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How Twitter is Using Big Data
Social TV: Driving new Advertising Opportunities
 Twitter acquired Bluefin and Trendrr
both research companies focused on
social TV data analytics and measuring
Tweets Per Minutes (TPM).
 Miley Cyrus’ performance at recent
MTV VMAs generated over 300,000
TPM
 If you tweet about a show while it’s
airing on TV, chances are that you’re
also seeing the ads
 Media opportunity to target sponsored
tweets to create digital extensions to the
ads on TV
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95% of the public social conversation
around TV happens on Twitter.

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How Agencies Are Using Big Data
In-view Attribution
 Junior data analyst at Mindshare was
working on some attribution research
almost 3-years ago and discussed the
concept of in-view attribution.
 Mindshare contacted Adsafe and
discussed creating the product.
 Mindshare ran the first alpha test
 Following this trend:
comScore, DoubleClick, DoubleVerify,
Moat, MediaMind
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FB Sources to Drive New Levels of Efficiencies and Opportunities
How Agencies Are Using New Exchange Inventory
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1. Beta test for FBX produced over 20% increase
in conversion rates
2. FB API Partners identified other affinities by
“Serial Likers”. What are the other brands
categories that your target audience also “Like”.
 This drove a series of affinity tests that
demonstrated positive results Creating
advanced hyper-targeted knowledge bases
 Actively optimize results and identify pattern
changes including scale and “Sustainability”
over time

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Sustainability
 Most case studies reflect
performance driven
achievements, but are those
results sustainable?

16. Sustainability: Programmatic Challenges and Opportunities
Requiring New Data Driven and Analytical Approaches
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1. Demand for RTB inventory has greatly
accelerated across all vertical including
Automotive, Financial Services, CPG …
 Project Higher media cost (more advertisers
are bidding for same/similar inventory)
What worked yesterday is not a guarantee
of success tomorrow
 “Complacency just doesn't work“
3. Test, Test, Test: leveraging big data, small
data, but
 “Fail smart and fail quickly“
 Apply existing learnings to testing new and
re-explore challenged opportunities
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17. Sustainability: New Challenges and Opportunities
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4. Be relentless about solving problems
 Keep trying different approaches
5. Focus on new opportunities to leverage
Clients’ first –party data
6. Re-targeting is overused and delivers limited
scale
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18. Perspectives on Big Data
Brian M. Decker
Managing Director, Digital
Client Leadership, Mindshare
GroupM Sherpa
Brian.decker@mindshareworld.com
Twitter: briandecker6
18 This document is confidential and proprietary to Mindshare. Do not distribute without permission.

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(Thank you)
This document is confidential and proprietary to Mindshare. Do not distribute without permission.