Solving the Remnant Inventory Problem By Ben Barokas As an industry, it’s taken us more than 15 years to get a grip on dealing with remnant ad inventory, but I think there’s finally a light at the end of the tunnel. Over the past two or three years in particular, the R&D that’s gone toward solving this problem has begun to drive substantive results for publishers, boosting eCPMs and easing the burden on their perpetually overworked ad ops teams. We’ve moved far beyond the static daisy chain into real time optimization, but how does it all work, and what are we doing to stay ahead of the problem? At its core, optimization is about “peeling off the layers” to reveal a clearer picture of what every impression is worth. Doing this at scale means accounting for a laundry list of ever-shifting variables (discrepancy, frequency, fill, user, content, geo) across countless sources of ad demand—and the problem isn’t getting any easier. The good news is, we’re on the cusp of another phase of innovation. Between Real Time Bidding (RTB) and a host of data infusion techniques, premium publishers in particular are poised to reap gains proportionate to the high quality of their content and audiences.

1. Solving the Remnant Inventory Problem
Ben Barokas, Co-Founder and CRO
August 18th 2009

2. About Us
 Founded in October 2007 Select AdMeld Customers
 Focus on premium
publishers
 80+ customers
 Manages more than 300
million ad impressions daily
 Raised $15M in venture
funding from Spark Capital
and Foundry Group
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© 2009, AdMeld Inc. All Rights Reserved.

3. Introduction
 How does discretionary optimization work?
– Create your ideal network portfolio
– Calculate the true value of every impression
– Deliver it with scalability and quality of experience
 What does it do for you?
– Boost your revenues
– Save you time, lower your costs
– Help protect your brand
 Looking forward
– RTB and Data
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© 2009, AdMeld Inc. All Rights Reserved.

4. Creating Your Ideal Network Portfolio
Analyze your site
Optimize your Understand
portfolio network inventory
Integrate and
Find the right mix
prioritize
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5. Diversification is Key
High
Fill
Low High
CPM CPM
Low
Fill
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6. Optimizing A Single Impression
Network A
Rev Share
$1.50
Network B
Rev Share
$1.20
Network C
Real Time Bid
$1.10
Network D
Fixed 3x24
$1.00
Network E
Rev Share
$0.50
© 2009, AdMeld Inc. All Rights Reserved. 5

7. Getting to True Value
Discrepancy Frequency Fill
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8. Discrepancy
 Many sources: internet latency, ad server latency,
user moving away from page to quickly
 Without discrepancy management, optimization is
ineffective
 Achieved 20% revenue lift at IAC through
discrepancy management alone
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9. Factoring in Discrepancy
Start Discrepancy eCPM
$1.50 40% $0.90 Network A
Rev Share
Network B
$1.20 10% $1.08 Rev Share
Network C
$1.10 0% $1.10 Real Time Bid
Network D
$1.00 15% $0.85 Fixed 3x24
Network E
$0.50 10% $0.45 Rev Share
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10. Frequency
 Early views worth most
 CPM is an average
across multiple views
 Many networks shift to
CPC or CPA at higher
frequencies
 Previously was done with multiple tags from networks
which carries a lot of overhead for premium publishers
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11. Factoring in Frequency
Discrepancy Frequency eCPM
Network A
$0.90 60% $0.54 Rev Share
Network B
$1.08 120% $1.30 Rev Share
Network C
$1.10 100% $1.10 Real Time Bid
Network D
$0.85 100% $0.85 Fixed 3x24
Network E
$0.45 100% $0.45 Rev Share
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12. Fill Rates and Pass backs
 Highest paying tags
usually have low fill
 Managing fill is
essential to calculating
revenue
 Daisy chains ensure an ad is shown
 What used to be done manually once a week, now
done dynamically for every impression
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13. Calculating Dynamic Daisy Chains
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14. Factoring in Fill
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15. True Value
Privileged & Confidential
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16. The Results
Network B Network D
Optimized
Choice
Rev Share Fixed 3x24 $1.16
$1.20 $1.00
Network A Network E
“Common”
Choice
Rev Share Rev Share $0.47
$1.50 $0.50
150% Revenue Lift
Over 100,000,000 impressions,
an additional $70,000
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17. Reality Check
 Doing this for large, premium publishers means:
– Calculating 5000 chain combinations per impression, in
real time, millions of times a day
– Accounting for geo, frequency caps and network latency
– Maximizing revenue during traffic spikes
– Backing it up with consultative services and expertise
– Executing against publisher business rules
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© 2009, AdMeld Inc. All Rights Reserved.

18. Managing Business Rules
Complete visibility into each ad,
without leaving your website.
• See the network that served the ad
• Report or disable problem ads
• View pricing, fill, targeting info, etc.
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© 2009, AdMeld Inc. All Rights Reserved.

19. Real Time Bidding
 A Shorter Road to True Value
With RTB, buyers bid dynamically for each impression instead
of setting blind rates (futures) beforehand
 Less Risk, Less Friction
With less risk, buyers confidently spend more at higher rates,
and pubs will have more access to demand sources
 RTB To Ramp Up in 2010
As adoption grows, so will efficiency and performance
 A Big Win for Premium Publishers
The most valuable inventory lies at the nexus of content,
context and audience. Premium publishers have all three.
Privileged & Confidential
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20. It’s All About Data
Privileged & Confidential
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21. Thank You
July 16th 2009