This document discusses how supply side platforms (SSPs) can help advertisers extend their audience reach by finding more engaged audiences across many publisher sites. It presents two case studies: (1) Expansion Audience Discovery uses a known "keystone" audience to uncover related audiences and content on other sites, and (2) Conversational Targeting uses semantic analysis to find conversations relevant to advertisers and target those discussions across thousands of sites. The results show these approaches can significantly expand audiences and often improve click-through rates compared to site-aligned campaigns. Going forward, the document proposes combining these technologies across a large network of sites to create high-scale, high-performance advertising opportunities.

1. Finding more of a good thing:
Using SSPs to extend audience reach
March 2012

2. What the Agency Says
I need more impressions,
I need more conversions,
I need more sites exactly
like Ginger.com
What the Exchange Hears
Blah
Blah, impressions, Blah
Blah, conversions,
More Ginger.com

3. THIS IS @
117,756
Publisher Sites
22.3M
Daily Uniques (192M Monthly
Domestic)
700M
Daily Real-time Exchange Transactions
TOP 10
Networks according to Comscore
Source: comScore Media Metrix July 2011

4. Brand/Performance - there's always that one site
• Portals have a lot of traffic, but the audience
isn’t that engaged.
• Ad Networks and Exchanges have a lot of traffic
but it’s not always clear what/where you’re
buying.
• How do you find more of that great audience in
that special niche?

5. Two Case Studies in Audience Finding…
Platforms or Supply Side sources have a wealth of
Big Data. FMP/Lijit is exploring two ways to find
more Great Audiences + Great Content in the
Independent Web.
• Expansion Audience Discovery:
– Using a known Keystone audience to uncover
content previously unknown and audiences not
currently served.
• Conversational Targeting:
– Using Semantic Technology to find conversations
and audiences relevant to Advertisers at scale.

6. Case Study 1: Expansion Audience Discovery
Keystone Site:
 Dooce.com / Author: Heather Armstrong
Find Other Sites:
 Dooce readers appearing on other Lijit sites
Select Genre Sites:
 Reduce resulting site set to sites with same genre
Calculate Expansion Audience:
 Similar Readers on Similar Sites

7. Case Study 1: Expansion Audience Discovery
• Observing Reader Appearances in 30 days. All Audience
– All Audience Cross Over: 100%
100% of Dooce Site Audience appeared on another sites Lifestyle Audience
in the exchange
– Keystone Audience: 27%
27% of Dooce Site Audience were seen again on sites in Target Site
Audience
the Lifestyle Genre
– Expansion Audience: 10X
Keystone
Audience that visited the same sites as the Keystone Audience
Audience but never visited the Dooce site.
Genre Expansion
– Genre Expansion Audience: 2X Audience
Audience that visited the same sites in the same Genre
as the Keystone Audience, but never visited the Dooce Expansion
Audience
site.

8. Case Study 2: Conversational Targeting
Find Organic Topics:
 For instance, tablet computing and
“We can imagine that a fair share of iPads got
target audience.
unwrapped this morning, and the first thing
you’re going to want to do is switch it on and
get a few awesome apps on there.” Find Candidate Articles:
 Using Sematic Analysis across
thousands of sites.
"For a chic carrying case that
doesn’t remind you of surfing the
crimson tide, try Blythe
Calculate Expansion Audience:
King’shandsome  Based on viewing patterns of that
iPadiSockit, which features a specific article.
"If you have a sling-flap closure and a front pocket
computer, iPhone, iPad, Blackb you can button up"
erry, or Android device, you Track Campaign Performance:
can download more books than
you will ever be able to read for
 Traffic and optimize performance
free." across target inventory.
Compare to Site Aligned Results:
 Comparison of performance to best
performing site aligned campaigns.

9. Case Study 2: Conversation Targeting Results
• Audience Expansion highly dependent on specificity of targeting
• Across the board CTR with Conversational Targeting proved Equal or Higher
Advertiser CT Target Overall CTR CT CTR Trend
Cloud 0.12% Higher
Microprocessors 0.08% Higher
Software Services 0.07%
Network 0.12% Higher
Operating Systems 0.08% Higher
Shopping 0.06% Equal
Fashion Item 0.06%
Fashion 0.07% Higher
Mobile Phone Mobile Phones 0.10% 0.11% Higher
Mobile Phone Mobile Phones 0.07% 0.10% Higher
Delivery Services SMB 0.09% 0.35% Higher
Autos 0.09% Higher
Vehicle Launch 0.05%
Green 0.05% Equal
Retail Sales Mobile Phones 0.46% 0.51% Higher
Software as Service SMB 0.06% 0.09% Higher
Mac 0.12% Higher
Computer 0.10%
Laptops 0.12% Higher
9

10. Conclusions: Next Phases…
Expansion Audience Discovery & Conversational
Targeting have both proved to be successful ways to
expand audience.
• Expansion Audience Discovery:
– Use a known audience to find new audiences and like content to
expand inventory.
• Conversational Targeting:
– Leverage relevant conversations to place brands where key
product decisions are being made.
Next Up: Use a combination of both technologies
across huge swaths of Independent Web to create
massive scale and high performance.