Konrad Feldman, CEO of Quantcast Big Data and the Future of Advertising and Marketing For marketers, data has become a critical asset throughout their role. Though not as “in your face” as great content or a creative video, data is the new lifeblood of their function. Not only is data essential for success, but the more data companies have, the more accurately and efficiently they can engage their customers and influence the market. Effective use of data in marketing and advertising will increasingly become a differentiating factor between businesses in this information economy. Konrad will explore the challenges, opportunities and what the future may hold for the use of big data in marketing and advertising.

1. Big Data and the Future of
Advertising & Marketing
Konrad Feldman
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2. Agenda
• Introduction
• Real-Time Advertising
• Big Data in Advertising
• Insights & Implications
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3. Quantcast
MEASUREMENT + ADVERTISING
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4. Measurement
• World’s best audience
measurement service
• Groundbreaking direct
measurement & insights
• For sites, publishers,
networks and advertisers
of any size
• 100% free for everyone
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6. Advertising
• Dynamic real-time
advertising
• RTB integrated
performance advertising
• Brand advertising
integrated with premium
publishers & networks
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7. Advertising Landscape
DISPLAY ADVERTISING GOES REAL-TIME
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10. Display Reemerges to Overtake Search
Display passes
Search
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11. Real-Time Bidding – Display’s Catalyst.
Real-Time rationalizes display. RTB’s rapid rise.
Billions
27%
RTB % of
$5
Display market
23%
$4
20%
$3
16%
$2
10%
$1
4%
$0
2010 2011 2012 2013 2014 2015
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12. Real-Time Bidding
MEDIA IS DATA
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14. Consumer’s Browser Ad Space Ad Exchange

15. The Exchange sends a
Bid Request, with information
regarding the individual ad
impression, to all Qualifying
Exchange Participants.
100s – 1000s
of Potential Buyers

16. 0:00:00.000
Exchange sends bid request to potential buyers 1 – 1000+ Advertiser Campaigns

17. 0:00:00.025
Exchange sends bid request to potential buyers 1 – 1000+ Advertiser Campaigns

18. What are the interests of this user?
0:00:00.040
0:00:00.035
0:00:00.030
0:00:00.050
0:00:00.045
Have they been shown impressions before
for this campaign?
How much do they consume on the Internet?
Where is this user in the world?
What device is the user browsing on?
Who is the publisher and what
is the context of this site and page?
How has this campaign performed on
this site in the past?
Is the impression above or below the fold?
What’s the time of day for the user?

19. What are the interests of this user?
0:00:00.060
Have they been shown impressions before
for this campaign?
How much do they consume on the Internet?
Determine Where is this user in the world?
Bid Value for
Highest Rated What device is the user browsing on?
Who is the publisher and what
is the context of this site and page?
How has this campaign performed on
this site in the past?
Is the impression above or below the fold?
What’s the time of day for the user?

20. 0:00:00.100
Bidding Race
Bids are submitted to the
Exchange by all participants.
Even if the impression is not
desired, $0.00 is bid to
indicate buyer’s capability
to respond.

23. AGE OF THE MACHINES

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32. Supporting Artificial Intelligence
BIG DATA TO THE FORE
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33. Big Data’s Innovation Cycle
Data
• Big data tends to follow
an iterative cycle within Capacity
Analysis
Capability
organizations
• These cycles are
accelerating
Data Use Analysts
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34. Quantcast Data Processing Architecture
Pixel Delivery Realtime Bidding Website Analytics
Realtime Decisioning Batch Processing Ad-hoc Queries
Realtime Engine Relational MapReduce Sawzall
Turbo
Storm Hadoop QuantSort RDBMSs
MapReduce
Keebler Redis Quantcast File System
Quantcast owned hardware
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35. Quantcast Data Processing Architecture
Pixel Delivery Realtime Bidding Website Analytics
Realtime Decisioning Batch Processing Ad-hoc Queries
Realtime Engine Relational MapReduce Sawzall
Turbo
Storm Hadoop QuantSort RDBMSs
MapReduce
Keebler Redis Quantcast File System
Quantcast owned hardware
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36. Quantcast Data Processing Architecture
Pixel Delivery Realtime Bidding Website Analytics
Realtime Decisioning Batch Processing Ad-hoc Queries
Realtime Engine Relational MapReduce Sawzall
Turbo
Storm Hadoop 0.15 QuantSort RDBMSs
MapReduce
Keebler Redis Quantcast File System
Quantcast owned hardware
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37. Quantcast Data Processing Architecture
Pixel Delivery Realtime Bidding Website Analytics
Realtime Decisioning Batch Processing Ad-hoc Queries
Realtime Engine Relational MapReduce Sawzall
Turbo
Storm Hadoop QuantSort RDBMSs
MapReduce
Keebler Redis Quantcast File System
Quantcast owned hardware
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38. Quantcast Data Processing Architecture
Pixel Delivery Realtime Bidding Website Analytics
Realtime Decisioning Batch Processing Ad-hoc Queries
Realtime Engine Relational MapReduce Sawzall
Turbo
Storm Hadoop QuantSort RDBMSs
MapReduce
Keebler Redis Quantcast File System
Quantcast owned hardware
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39. Big Data
BY THE NUMBERS
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40. Data
Real-Time Ingest
500,000+ / sec. Big Raw Data
Massive Transaction Volume 40+ TB / day
750+ Billion / mo.
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41. Computers
Real Estate
15+ Data Centers Machines
Largest Data Center 1,000+ Servers
40+ Racks
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42. Data Processing
Daily Processing Scaling Petabytes per day
30
25
25+ 20
15
Petabytes 10
5
0
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43. People who buys shoes online
More likely to visit... More likely affiliation...
Site Score Affiliation Score
runnersworld.com  Democrat 
halfmarathons.net  Libertarian 
athlinks.com  Independent 
runningintheusa.com  Republican 
flotrack.org 
running.about.com 
letsrun.com 
eatliverun.com 
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44. Advertising Insights: Clickers vs. Converters
• 85% of clicks come from just
8% of internet users
• Converters have a distinct
profile, which is nothing like Clickers (over-index low income)
the clickers
Converters (over-index high income)
• Most converters don’t click
ads. They view them
• Clickers are not the target
customer
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45. Traditional Display
50
Impressions Bought in
Aggregate 40
Priced as a Whole
30
Focus: Cost
CPA
Key Skill: Negotiation 20
10
-
CPM
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46. Real-Time is Different
50
Impressions bought
Individually 40
Priced Individually
30
Focus: Value
CPA
Key skill: Science 20
10
-
Example: Travel campaign
CPM
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47. Real-Time is Different
50
Impressions bought
Individually 40
Priced Individually
30
Focus: Value
CPA
Key skill: Science 20
10
-
Example: Travel campaign
CPM
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48. Consistent Feature of RTB Campaigns
Media Subscription Travel
125 4
100
3
75
CPA
CPA
2
50
1
25
-
-
CPM CPM
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49. Implications for Advertising and Marketing
• Data Science over Human Hypothesis
– People guide, computers execute
– Media buying must change to accommodate
• Marketers, BYOD (Bring Your Own Data)
– Leverage website and CRM assets
• Publishers, get data smart
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50. Konrad Feldman
kfeldman@quantcast.com