1. The Future of Media:
IGNITION

2. Data Use in an Addressable World
Aggregate Atomic
Static Dynamic
Retrospective Predictive
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3. The Publisher Advantage within the Data Ecosystem
• It’s what’s inside that counts: What really makes for
great data? Why does it matter where it comes from
and can it scale?
• Results that matter: Does it drive the metrics
important to advertisers I’m working with?
• Getting a leg up: Does it give me an advantage in
the marketplace?
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4. Data Origins
1st Scale 3rd
Party Party
Relevance
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5. What makes for great data?
Consistent Scaled
Without this it’s hard to build Not just data scale, but execution
reliable models. scale too
Fresh Relevant
Speci ic to the types of data Measuring contribution to your
objective is key
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6. Data Usage Status Quo
3rd Party Centric Human Hypothesis
Reliant on other’s perspective of Targeting criteria developed
what’s best through intuition
Low Dimensionality Positive Signal
Limited number of attributes Models consider only attribute
considered presence
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7. Data Usage Next
1st Party (when Automatically
available) Modeled
If you know who your best Machine learning comes to the
customers are, use them forefront
High Comprehensive
Dimensionality Models
Digital media creates lots of Considering multiple attributes
data, use it (or lack of)
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8. Attributes of Targeting Approaches
Algorithms Is the model based on human hypothesis, or
algorithms? In most cases sophisticated
algorithms are superior, just look at search.
Data Relevance How relevant to the objective is the data that
is used to develop the targeting model?
Performance What Return on Investment (ROI) can
the targeting solution offer?
Scale Can it scale? High ROI with limited scale
doesn’t matter.
It’s all about performance and scale!
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9. Our de inition of data must be expansive
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10. Leveraging the Data
1997 Algorithm
Media bought based on Relevance
proxy. Good scale, but Performance
lots of waste Scale
2004 Algorithm
Relevance
Great targeting, less
Performance
waste through
retargeting, but no scale Scale
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11. Leveraging the Data
2010 Algorithm
Holistic understanding of Relevance
the consumer Performance
Scale
The Future Algorithm
Relevance
Predict the right place
Performance
and right time for
consumer conversion Scale
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12. Driving Results
that Matter
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13. Uniqueness
Case
Study Credit Card
 Case
 Study of the world’s largest credit card
One
companies, wanted Quantcast to identify
quali ied applicants who could make it through
their rigorous approval process.
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14. Uniqueness
Premium Business Budget
Card Card Card
Converters Are: Converters Are: Converters Are:
Age 44-54 Age 34-44 Age 34-44
Grad School College Children in HH
HHI $100k+ HHI $60-100k HHI $30k - $60k
Converters Are Interested: Converters Are Interested: Converters Are Interested:
Business News Travel Coupons
Travel Sports Personal Finance
Real Estate Weather Diet and Fitness
Converters Are Not Interested: Converters Not Are Interested: Converters Are Not Interested:
Fantasy Sports Horoscopes Politics
Social Networking Coupons Gambling
Parenting Personals Fantasy Sports
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15. Performance
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16. Scale
Performance is not
about clicks.
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17. Conversions only matter if you have scale
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18. What use is ROI without Return?
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19. Does it give me an advantage in the marketplace?
Capture greater
share of budget
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20. Does it give me an advantage in the marketplace?
Open up access to more
budgets within the
existing advertisers you
work with
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21. Does it give me an advantage in the marketplace?
Drive lift and CPM on
pages already sold and
incremental sell through
on pages that aren’t
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22. Does it give me an advantage in the marketplace?
Open the door for
a more holistic
conversation
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23. Questions?
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24. Quantcast Data & Technology
 10+ Billion Daily
 directly measured web assets  consumption events directly recorded
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