The Pool: Uncovering New Units

THE POOL: UNCOVERING NEW UNITS IN THE ONLINE VIDEO SPACE aol online video lane
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The Pool:
Uncovering New Units
In the Online Video Space
AOL Online Video Lane
1/8/13 11:05 PM
The Pool:
Uncovering New Units
In the Online Video Space
AOL Online Video Lane
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Copyright 2012 VivaKi, Inc. All rights reserved.
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contents
1
The Winning Ad units
2 5 The AOL Online Video Lane Process
7
Background
41
The Pool Mission Statement
The Pool Around The World
The Pool’s History in Online Video
The Lifeguards
Acknowledgements
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Field Trial findings
6 9 Conclusion
The Winning Units
Leveraging the q Units
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THE WINNING AD UNITS
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The Winning Ad units
The Pool began its research in the online video space in 2008 with
the recognition that media had become time-shifted, digitized,
shortened and readily available for consumers to enjoy whenever
and wherever they are. The Pool, which exists to uncover new
and improved advertising solutions, embraced the change in
media head-on and brought together marketers, advertisers and
publishers to work to uncover these solutions – ones supported
by consumers, advertisers and media companies.
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AOL STEPPED FORWARD
TO SPONSOR THE POOL'S
THIRD ONLINE VIDEO LANE
IN THE U.S.
The winning ad model of The Pool's first two U.S. lanes in online video was ASq
(Ad Selector Done Smart —“q” as in "I.Q."), an ad format that is similar to the industry’s
pre-roll standard, with one major difference: it gives users the power to choose their ad.
Given the ongoing growth of the space, and continuing confusion over new ad models being
offered, the time was ripe for further exploration and collaboration. AOL stepped
forward to sponsor The Pool’s third online video lane in the U.S. The goal of the lane
was simple: continue The Pool’s research in online video to accelerate its growth through
additional consumer-tested and approved ad models.
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Research through the AOL Online Video Lane uncovered three new q units, each of which
outperformed pre-roll, cementing their place in the overall online video ecosystem.
AOq ( A D OVER LAY DONE SMART ) allows users to delve deeper into the ad experience through
customizable tabs, which overlay on the pre-roll. These tabs pause the pre-roll and drive
viewers to in-player experiences that can include anything from product info pages to store
locators to photo galleries.
AP q ( AD POL L DONE SMART ) encourages users to control their ad experience. Users are presented with
a slate that allows them to choose from one of two options: a 30-second ad or a 15-second ad
with one closed-ended question following the commercial.
S O q ( SOC I A L OVER LAY DONE SMART ) is a simple execution that allows users to connect with a brand via
their social networks. The unobtrusive overlay can drive to any social network.
Depending on an advertiser’s preferences and objectives, one or more of the new offerings
would be a better option over the standard pre-roll model. For advertisers wishing to
provide a deeper interaction in online video, AOq is best. APq gives advertisers the
opportunity to gain new consumer insights (while offering people a choice during their
online video ad experience). SOq has a key social component to it. ASq, which was also
included in the lane, continues to demonstrate strong performance on all metrics as a
superior choice-based model.
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BACKGROUND
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B a ckgro u n d
TH E P OOL MI SSI O N STAT EMEN T: Create industry alignment on
advertising solutions through the process of pooling resources
and the uncovering of human insights.
The idea for The Pool began in 2008. VivaKi was actively involved in several external
ventures investigating the possibilities for new forms of advertising. The agencies were
enthusiastic participants but, at the end, they kept coming back to a very basic question:
Now what?
There were lots of ideas and interesting research, but not enough concrete actions at the
end. Everyone agreed that VivaKi and its clients had learned something but few were sure
how to put that fully to use in the marketplace.
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T h e Po o l Aro und the Wo rld
The success of The Pool’s first two lanes created a ripple effect around the globe.
November 2008
The Pool launches its first
lane of research in the U.S. with
a focus on online video.
February 2010
The Pool Founder Tracey Scheppach
releases results of its U.S. Online
Video Lane and announces ASq as
the winning ad model in front of
a sell-out crowd at the IAB Annual
Leadership Meeting.
April 2010
The Pool launches its first
international lane in China,
continuing its research in
online video.
October 2010
The Pool continues its
research in online video with
the announcement of its first
lane in the U.K.
March 2011
The Pool launches an online
video lane in Australia.
The Pool’s online video lane
in China confirms the findings
of earlier U.S. lanes and
announces ASq as the optimal
ad model for online video.
2008
July 2009
The Pool launches its
second lane in the U.S., this
time specifically focusing
on short-form online video.
May 2010
The launch of ASq is covered in
Advertising Age. The publication
notes “Vivaki's ‘Ad Selector’
could significantly change the
online video marketplace.”
September 2010
The Pool turns its focus to
display advertising in
the Middle East/North Africa
region with a lane in Dubai.
November 2010
The Pool launches an online
video lane in Spain.
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September 2011
France launches three lanes of
research — online video, in-banner
and IPTV.
November 2011
The Pool in Spain becomes
the fourth country to name
ASq the winning ad model
for its online video lane at the
IAB Festival Inspirational.
May 2012
The Pool in the U.K.
announces ASq as the winner
of its online video lane,
making it the fifth global
market to do so.
December 2012
The Pool in the U.S. announces AOq,
APq, ASq and SOq as the winners of
the AOL Online Video Lane.
In France, The Pool announces the
winners of its IPTV, in-banner and
online video lanes; ASq wins online
video for the sixth time.
2012
July 2011
The Pool launches a
cross-media metrics lane in
China. The lane, China’s second,
analyzes consumer behavior
and evaluates the effectiveness
of cross-media ads.
October 2011
In the U.S., The Pool launches its
first lane dedicated to tablets.
The Pool and AOL join forces and
announce The Pool’s third online
video lane in the U.S. to uncover
additional ad models in the online
video space.
December 2011
The Pool in China announces
the results of its cross-media
metrics lane.
September 2012
In Dubai, The Pool names
Tri-ad, a choice-based model,
the winning model of its
MENA Display Lane.
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So VivaKi executives began thinking of what the network could do to move forward
faster. They knew VivaKi had the expertise and experience, along with a strong drive for
innovation. They believed it had a client roster of equally forward-thinking companies who
would love to get involved. So they began reaching out to media and technology companies,
many of which were conducting their own individual research studies similar to those
VivaKi had undertaken. The network had even partnered with several of them on one-off
studies. Executives began thinking, “what if we worked together in a broader, deeper, more
collaborative way to discover and test new ideas for advertising on new media platforms that
could change the industry?”
From those conversations, The Pool was launched. The initiative brings together the leaders,
pioneers and futurists who want to help create tomorrow, today. The Pool’s participating
partners must commit themselves fully in terms of resources, experience and financial
obligations. Participating clients are also required to commit to the full program, providing
the assets that are tested and the funds to deploy the ad model in a live, in-market field trial.
At the end of the process, which can last about a year, Pool participants help scale and
monetize evolving media platforms. Along the way, participants have access to the
best-in-class talent, as well as first-mover knowledge to secure leadership advantage in
the marketplace.
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T h e Pool’s History In Online Video
The Pool’s first lane in the online video space launched in November 2008 and included six
major advertisers and seven media companies. Participating companies included:
Allstate
Capital One
BBE
Hulu
Applebee’s
Nestlé Purina Petcare
CBS
Microsoft Advertising
BlackBerry
AOL
Discovery
Yahoo!
Over the course of one year, The Pool conducted research that revolved around a
democratic and sequential 5-2-1 approach: five models tested qualitatively, two models
tested quantitatively and one model tested in the field trial. Throughout each phase,
the models were compared to the industry standard, pre-roll. The Pool considered
29 different ad models, tested 43 different executions, spent more than 8,000 hours with
industry peers and spent more than 230,000 hours with more than 25 million consumers.
All the research produced the winning ad model: ASq, which was evolved and developed
throughout The Pool process from the Ad Selector, a format brought by Hulu to the
kick-off meeting.
From the earliest stage of research in the first lane, The Pool began hearing consumers
differentiate between the experience of watching long-form content, such as TV shows
and short-form (i.e., under 5 minutes) video clips, such as YouTube, breaking news or
sports highlights. That distinction held true in Phase Two, the quantitative study, where
consumers appeared to respond differently depending on the length of content. While ASq
still came through as the optimal model for online video, the question remained: is there a
need for a different ad format specifically for short-form content?
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The Pool continued its research in online video in July 2009 with a focus on short-form
online video. Much had changed since The Pool’s initial dive into the water. The economic
downturn that started in September 2008 was in full swing, with advertisers spending
less and media companies feeling the pinch. Consumers, too, had changed in some ways.
They were even more comfortable in the online arena, spending more of their time
with the medium and demonstrating a willingness to engage with relevant and
choice-enhancing advertising.
What did not change from the first lane to the second was The Pool’s firm belief in the
need for collaboration and change, the coming together of key players in the industry
to accelerate the fortunes of a new media platform by aligning everyone around a
consumer-tested and approved new ad model.
The Pool expanded its roster of agencies and advertisers beyond Starcom MediaVest
Group (SMG) to all of VivaKi, which included the media and digital agencies in the
Publicis Groupe family: ZenithOptimedia, SMG, Digitas and Razorfish, giving it a
broader and richer mix of participating companies. At the same time, the success of the
first swim lane meant that more publishers wanted to participate. As a result, the second
lane included 10 publishers and 13 advertisers, more than double the relative numbers
from the first lane.
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These included:
Bank of America
Mars
BBE
Tremor Media
BlackBerry
Procter & Gamble
CBS Interactive
Denny’s
U.S. Cellular
Disney Pictures
Walgreens
Fancast/Comcast
Interactive Media
Warner Bros.
Digital Media
YouTube
General Mills
Walmart
FoxNews
YuMe
Kraft Foods
AOL
Microsoft Advertising
In the second lane, The Pool considered 28 different ad formats, tested 48 different
executions, spent over 13,000 hours with industry peers and spent over 860,000 hours
with more than 22 million consumers. Again, ASq was named the winning ad model
for the lane.
Overall, ASq has proven itself to be the optimal ad model for long- and short-form online
video in seven different studies spanning six countries (Australia, China, France, Spain,
U.K. and U.S.). In those studies, a total of 388 different model executions have been tested
with 278 million consumers over 19 million hours, with ASq consistently outperforming
the other models, with various iterations tested to ensure what is brought to market is
the best execution.
Yet, even with The Pool’s extensive research in this space, the question that remained
was whether there were other ad models for online video. The goal of the AOL Online
Video Lane was simple: continue The Pool’s research in online video to accelerate its
growth through additional consumer-tested and approved ad models.
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THE LIFEGUARDS
Here are the passionate people who have
helped make the vision of The Pool a reality.
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TRACEY SCHEPPACH
EVP, Innovations Director, VivaKi and SMGx, and Founder of The Pool
Tracey Scheppach is the founder and global leader of The Pool. She has championed and spearheaded the initiative since its early stages,
leading to global exploration and testing in online video. She has been at the intersection of media, technology and consumer behavior for
almost 15 years. In her current role, she is responsible for understanding the nuances and latest developments in emerging media and runs
SMGx’s Innovation Center of Excellence (COE), one of three pillars within SMGx. Tracey has been a vocal industry advocate for freeing TV
set-top box data and more addressable advertising to deliver more accurate ROI for clients. Her work and powerful voice in the industry have
gained her accolades such as Advertising Age Women to Watch (2008); Mediaweek’s Watch List (2009); iMedia Connection’s Top 25 Internet
Marketing Leaders and Innovators (2009) and inclusion in the prestigious American Advertising Federation’s Hall of Achievement (2009).
Tracey is a member of the 4As National TV Innovation committee and Invidi’s Advisory Board.
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HELEN KATZ
SVP, Research Director, Starcom MediaVest Group
Helen Katz is the research and insights guru for Starcom MediaVest Group. She spends most of her time crafting and conducting
research studies to better understand how consumers use and think about various digital video forms, with the goal of creating actionable,
enlightening and industry-changing outcomes. As the research lead for The Pool, Helen works with the research partners to execute robust
and compelling research across all phases of the program: qualitative, quantitative and in-market field trial. She has spent the past few years
immersed in the exploration of TV set top box data, addressable advertising and mobile ad models, as well as being a founding member of
several industry initiatives in the new media space. She is an ARF “Great Minds” award-winner and a member of the James Webb Young
Board at the University of Illinois, where she received her Master’s and Ph.D. degrees. Helen is the author of three textbooks on advertising
and media, the most recent being The Media Handbook (5th edition to be published by Routledge in 2013).
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BETH DOYLE
Innovations Director, VivaKi
Beth Doyle is an Innovations Director at VivaKi. In her role, she oversees operations for The Pool and serves as product manager for ASq.
Prior to joining VivaKi, Beth worked at Starcom and SMGx where she consulted agency teams on video innovation and strategy, while
buying emerging media and creating standards.
Beth was recognized as Mediaweek's Rising Star in 2010 and an “Agency Innovator” by
The Internationlist in 2012. She regularly returns to her alma mater, the University of
Notre Dame, to speak to students about emerging media and technology. Beth earned her
MBA from DePaul University, with a concentration in change management.
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SAMANTHA MERRITT
Manager, VivaKi
Samantha Merritt is a manager on The Pool, responsible for leading The Pool’s day-to-day operations. These responsibilities include, but are
not limited to, leading ad model development, project management and serving as the primary point of contact for senior executives on the
agency, brand and publisher sides.
Prior to her current role, she served as digital associate on the BlackBerry team at Starcom. In the 17 months she spent with the team,
Samantha gained expertise on account and client management, as well as planning, buying and reporting across digital vehicles. She earned
her BA in advertising from Penn State.
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KEVIN RITT
Associate, VivaKi
Kevin Ritt joined VivaKi’s Pool team in February 2012 as an associate responsible for helping
manage each lane of The Pool in the U.S. His day-to-day responsibilities include project
management, data analysis and research coordination.
Prior to joining The Pool, Kevin was an assistant media planner at Draftfcb Chicago’s MC
Media where he worked on the agency’s Miller Lite account. He is a graduate of the University
of Notre Dame, where he earned his bachelor’s degree in marketing.
ELLIS CHAMBERS
Associate, VivaKi
Ellis Chambers joined The Pool as an associate in July 2012 from JWT Inside in Atlanta.
As a member of The Pool team, Ellis works to make sure that each U.S. lane meets its
deliverables and deadlines. His day-to-day responsibilities include project management,
data analysis and market research.
During Ellis’s time at JWT Inside, he worked on accounts such as UCLA Health System,
DaVita and Dignity Health. He is a graduate of the University of Georgia, where he earned
his bachelor’s degree in advertising.
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Acknowledgements
While the Lifeguards – in close partnership with AOL, marketers and research partners –
managed the overall process, there were a host of other experts, thought leaders, visionaries,
research gurus and tech geniuses who contributed to this effort. Without their devotion,
The Pool would just be an idea on the back of a napkin.
Amanda Dixon
Team One
Ellis Chambers
VivaKi
Amanda Mollet
Spark
Emily Johnson
AOL
Andrea Johnson
AOL
Ezra Suveyke
VINDICO
Ariel Stiglitz
VINDICO
Gaurika Chadha
Saatchi LA
Badinn Chobhaphand
AOL
Helen Katz
VivaKi
Ben Chardell
Starcom MediaVest Group
Hillary Hawker
AOL
Beth Doyle
VivaKi
Jaclyn Skaja
comScore
Brandon Stewart
AOL
Jamey Wishner
VINDICO
Carly Weinstein
comScore
Jarod Knight
Team One
Catherine Becker
AOL
Jeff Marshall
AOL
Charles Gabriel
AOL
Jennifer Scholnick
AOL
Chris Spengler
AOL
Jennilee Jacobs
AOL
Christian Kugel
AOL
Jessica Perin
Starcom MediaVest Group
Dan Pineda
Team Sprint
Jill Griffin
Starcom MediaVest Group
Darlene LaChapelle
AOL
Josh Dysart
VivaKi
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Kelly Chiricotti
Spark
Saneep Mittal
AOL
Kerry Brown
AOL
Scott Navarro
AOL
Kevin Blaine
AOL
Sean Mills
VivaKi
Kevin Ritt
VivaKi
Shelby Saville
Spark
Laura Centore
comScore
Steven Torices
Saatchi LA
Lauren Damron
AOL
Susan Crawford
AOL
Leigh Freund
AOL
Susan Shostack
AOL
Liz Brock
Team Sprint
Tony Gemma
Starcom MediaVest Group
Lynette Conover
Team One
Tracey Scheppach
VivaKi
Mary DeBrunner
VivaKi
Wendy Segal
comScore
Mason McCoy
VINDICO
Megan Black
Team Sprint
Megan Buehner
AOL
Mike Srilapa
AOL
Nicole Haygood
Spark
Paul Janness
AOL
Rishi Pahuja
AOL
Robin Sheedy
VivaKi
Ronnie Dickerson
Team Sprint
Samantha Merritt
VivaKi
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THE AOL ONLINE VIDEO LANE PROCESS
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Th e AO L O n l in e Vide o L ane P roc e ss
Due to The Pool’s extensive research in online video—both in
the U.S. and around the world—it was agreed that repeating the
qualitative and quantitative stages of research was unnecessary
for the AOL Online Video Lane.
Instead, The Pool went straight from brainstorming ideas to the field trial phase with five
advertisers including Fancy Feast, Lexus, Microsoft and Sprint. AOL and VINDICO each
provided ad model concepts, and employees from all VivaKi agencies were invited to submit
their ideas as well. A total of 72 models were anonymously evaluated and voted on by
key personnel from VivaKi, AOL and VINDICO, and the top three models were selected
for inclusion in the lane along with ASq.
The winning ad models went into a live, in-market field trial, during which the participating
advertisers activated the new ad models across the AOL ON video network. All the
way through this process, The Pool benchmarked these models against the current industry
standard of pre-roll.
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IT WAS CLEAR BY THE END OF THE
FIELD TRIAL THAT ALL THE TEST
AD MODELS OUTPERFORMED THE
BENCHMARK PRE-ROLL UNIT ON
ONE OR MORE METRICS.
The Field Trial
The research approach for the field trial was a live, in-market test where advertisers placed
ads in both new and existing ad units across the AOL ON video network. It was clear
by the end of the field trial that all the test ad models outperformed the benchmark pre-roll
unit on one or more metrics. For example, AOq and APq showed lifts in click-through,
engagement, awareness and recall, while SOq out-performed pre-roll in completion,
click-through, engagement and purchase intent. ASq again demonstrated its strength
as an ad model, and was the strongest format across all metrics. From these findings, it was
concluded that all the new ad models have a place in the market, depending on advertiser
preferences and campaign goals.
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PRE-ROLL
AOq
APq
ASq
SOq
AOq
RATE
APq
ASq
SOq
PERCENT DIFFERENCE/LIFT VS. PRE-ROLL
COMPLETION RATE
75%
75%
67%
78%
79%
0%
-7%
+5%
+1%
CLICK-THROUGH RATE
0.55%
0.67%
2.21%
0.77%
0.41%
+22%
+195%
+5%
+5%
ENGAGEMENT
0.72%
0.94%
3.88%
2.44%
0.52%
+31%
+288%
+165%
+6%
PRE-ROLL
AOq
APq
ASq
SOq
AOq
LIFT VS. CONTROL
APq
ASq
SOq
PERCENT DIFFERENCE/LIFT VS. PRE-ROLL
TOP-OF-MIND AWARENESS
+24%
+41%
+48%
+57%
+25%
+71%
+129%
+171%
No difference
TOTAL UNAIDED AWARENESS
+10%
+26%
+41%
+34%
No Lift
+160%
Significant Lift
+209%
-
ONLINE AD RECALL
+45%
+39%
+63%
+74%
+33%
No difference
No difference
+90%
No difference
MESSAGE RECALL
+175%
+433%
+400%
+320%
+233%
+147%
+60%
+60%
No difference
PURCHASE INTENT
+17%
+13%
+11%
No lift
+31%
No difference
No difference
-
+35%
T h e Re s e arch Part n e rs
There were two key research partners included in the field trial. VINDICO provided the
behavioral tracking of consumers’ exposure to each ad model. For consumers’ attitudinal
response, captured via an online consumer survey, the research partner was comScore.
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Ad M o d e ls Te ste d
The four models included in this
research were:
AOq
A NAVIGATION BAR AT THE TOP ANIMATES IN AND OVERLAYS THE VIDEO, AND EACH TAB ON THE NAVIGATION
BAR DRIVES TO A SEPARATE IN-PLAYER EXPERIENCE. IF A VIEWER CLICKS A TAB, THE PRE-ROLL PAUSES,
AND THE VIEWER CAN EXPLORE THE FULL IN-PLAYER EXPERIENCE BEFORE RETURNING TO THE PRE-ROLL AND
THEN THE VIDEO.
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APq
A SLATE APPEARS PRIOR TO CONTENT AND ASKS VIEWERS TO CHOOSE BETWEEN WATCHING EITHER A 30-SECOND
AD OR WATCHING A 15-SECOND AD WITH A CLOSED-ENDED SURVEY QUESTION TO FOLLOW (ALL IN-PLAYER). IF THE
15-SECOND AD IS SELECTED, THE VIEWER MUST COMPLETE THE SURVEY.
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ASq
A SINGLE ADVERTISER OR MULTI-ADVERTISER SLATE APPEARS PRIOR TO CONTENT ASKING VIEWERS TO CHOOSE A
VIDEO AD TO WATCH BEFORE CONTENT RUNS. IF NO CHOICE IS MADE, A DEFAULT VIDEO AD RUNS.
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SOq
AN OVERLAY ALLOWS ADVERTISERS TO DIRECT VIEWERS TO VARIOUS BRANDED SOCIAL MEDIA PAGES THROUGH
THEIR PRE-ROLL UNITS. ADVERTISERS CAN ADD THE LOGOS OF UP TO FOUR SOCIAL NETWORKS, INCLUDING
FACEBOOK, TWITTER, YOUTUBE, GOOGLE+ AND PINTEREST AND CAN CONTROL AT WHICH POINT THE LOGOS APPEAR.
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The field trial was conducted between November 2011 and August 2012, with executions
running from one to four months depending on the advertiser. A total of 79 million
impressions were delivered across the five participating advertisers.
Below is a summary of what ad models were tested by which advertiser, including the type
of content in which their ads appeared.
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ADVERTISER A
FORMATS TESTED
AOq
x
APq
x
ADVERTISER B
ADVERTISER C
x
ADVERTISER D
x
ADVERTISER E
x
x
x
SOq
x
ASq
x
x
x
x
x
4 months
1 month
3 months
2 months
3 months
May – Aug
June
Apr– Jun
Feb– Mar
Nov– Jan
CREATIVES USED
6
1
5
4
5
PLACEMENT TYPES
Demo-target
Entertainment
Demo-target
Content Channels
RON
Behavior target
Music
Advanced targeting
Look-A-Like Target
Sponsorship
Tech
LENGTH OF CAMPAIGN
Demo-target
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FIELD TRIAL FINDINGS
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Fie l d Tria l Fin d in g s
B e hav io ra l Re s ult s
The key metrics for our behavioral research were the completion rate, or percent of ads
watched to the end, and the click-through rate, defined as the percent of video ads clicked
through to the advertiser’s landing page. Measures of engagement varied, depending on the
ad unit. For the pre-roll benchmark, it was simply gross clicks to the video and/or banner.
For ASq, it was the gross number of clicks including video choice, video click or banner click
divided by the number of ASq slates. For all the new q units, engagement covered those,
together with additional interaction opportunities pertinent to each model. For AOq, that
included “Open Tabs,”“Learn More” and “Watch YouTube Videos.” With APq, engagement
included “Select an Ad,”“Answer ‘Yes’” and “Click Logo,” while for SOq, consumers could
“Click to Facebook” [or any other social network] or on the brand logo.
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The primary type of analysis on the behavioral data was lift over pre-roll. Since each
q unit was tested with a different number of advertisers, only those brands using a particular
model were included in the pre-roll aggregate to ensure this was an “apples to apples”
comparison. That is, if Advertisers A and B were the only ones to test AOq, then only their
pre-roll benchmark ads were used as the point of comparison. Note that implementation
issues affected ASq Chosen ads early on in the field trial. After the issue was corrected,
a small sample size remained. Results on ASq Chosen are therefore reported for
directional purposes but are not robust enough to provide statistically significant
performance benchmarks.
AOq
APq
ASq
SOq
LIFT VS. PRE-ROLL
BEHAVIORAL METRICS
Completion Rate
x
Click-through Rate
x
Engagement
x
x
x
x
x
x
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C o mp let io n Ra te s
ASq and SOq ads were watched to completion most often. In addition, ASq showed the
highest campaign lift in completion at +5%. Viewers seeing shorter ads (:15) were more
likely to complete the ad than those exposed to the longer (:30) commercials.
COMPLETION RAT E BY FORMAT(%)
Pre-Roll
Format
AOq
75%
75%
APq
72%
67%
ASq
74%
78%
SOq
78%
79%
50%
100%
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COMPLETION RATE BY FORMAT(%)
Advertiser A
Advertiser B
Advertiser C
Advertiser D
Advertiser E
74%
PreRoll
80%
65%
85%
When examined by individual advertiser,
results did vary. The two highest campaign
lifts were seen with the ASq for Advertiser
C and Advertiser D. While the APq model
delivered the lowest completion rates, its
click-through and engagement rates were
among the highest.
69%
68% (-8%)
AOq
80% (0%)
68% (+5%)
87% (+2%)
68% (-1%)
72% (-3%)
APq
63% (-9%)
83% (+28%)
92% (+8%)
ASq
66% (-4%)
80% (0%)
SOq
66% (+2%)
87% (+2%)
50%
100%
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C l i ck-T h ro ug h Ra te s
In terms of the video click-through rates, the strongest results were seen for ASq and
APq, compared to pre-roll. The highest individual lift occurred for APq, +209% for
Advertiser E, with ASq at +45% for Advertiser D. In contrast to completion rates,
the longer commercials (:30) were clicked more often across all formats and advertisers.
CLICK-THROUGH RAT E BY FORMAT(%)
Pre-Roll
Format
AOq
.55%
.67%
APq
.75%
2.21%
ASq
.73%
.77%
SOq
.39%
.41%
1.5%
3%
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Engagement Rates
The highest overall engagement rates were seen with ASq and APq. The former
produced a 165% lift over pre-roll, while for the latter, it was +288%. Both AOq and SOq
also generated lifts in engagement, at +31% and +6%, respectively. When looked at
by advertiser, the largest lift in engagement was seen for Advertiser C in ASq at +688%,
followed by Advertiser A with a +435% lift on APq.
Those who did engage with the new units were 13% more likely to complete the video
compared to pre-roll. This ranged from a lift in completion of +4% for SOq engagers to
+27% for those who engaged with APq.
The type of engagement varied by unit. On AOq, it was in the form of video and banner
clicks. The highest proportion of tab interactions occurred with Advertiser E and
Advertiser C. With APq, Advertiser E’s high engagement came primarily from video clicks,
whereas for Advertiser A, the largest proportion of engagement was in choosing an ad.
That advertiser also saw a higher proportion of survey completes.
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ENGAGERS VS. OV ERALL COMPLETION RATES
Overall Completion Rate
Engagers Completion Rate
Total
75%
85%
AOq
75%
80%
APq
67%
85%
ASq
78%
92%
SOq
79%
82%
50%
100%
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EN GAGEMENT RATE BY FORMAT(%)
Pre-Roll
Format
AOq
.72%
.94%
APq
1.00%
3.88%
ASq
.92%
2.44%
SOq
.49%
.52%
2%
4%
Engagement in SOq was driven mostly by video clicks with the largest share of clicking on
social buttons seen on Advertiser C. Advertiser B’s execution produced the most banner
clicks. Each advertiser for this particular unit offered a different selection of social network
choices. Advertiser D, with four different offerings, saw the highest share going to YouTube.
That was true for Advertiser C as well, where YouTube was one of three social network
choices. With Advertiser B, only two options were included, and the majority of engagers
selected Facebook.
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SOCIAL INTERACTION ENGAGEMENT BY ADV ERTISER(%)
Google +
Youtube
Twitter
Facebook
Advertiser D
11%
44%
8%
36%
Advertiser C
62%
17%
22%
Advertiser B
46%
54%
50%
100%
ASq provided the strongest type of engagement for two of the three executions in users
selecting an ad (Advertisers D and C). With the third, Advertiser E, it was video clicks that
generated the highest engagement type.
In sum, the behavioral results showed ASq and SOq beat pre-roll on all three measures,
while AOq and APq did so for click-through and engagement.
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Attitudinal Results
In order to assess consumer attitudes during the field trial, distinct tracking pixels were
appended at the start of the video; these pixels dropped an exposure cookie and stamped
the time of exposure. Recruitment node tags were tied to video companion banners as
well as bonus impressions or placed on high traffic areas of AOL to intercept users exposed
to each campaign. Both test and control samples were recruited from the nodes via an
online survey invitation. Control respondents were recruited prior to the campaign launch,
while test respondents were exposed to only one ad unit and surveyed on a minimum delay
of 10 seconds, ensuring video completion.
The initial strategy was to launch the recruitment from companion banners. For some
campaigns, survey completion rates were very low when using just this approach, which was
limited to bonus impressions on actual video pages. Subsequently, an alternate methodology
was implemented using a general recruitment node placed on high-traffic areas of the
AOL ON video network. This resulted in intercepting users who had, in some cases, been
exposed many days prior to survey completion. Therefore, respondents with exposure more
than four days prior to completion were excluded from the analysis.
The research included an unexposed control group for each brand and five test ad units
(three or four tested per brand). A total of 11,120 surveys were completed from within the
AOL ON video network. Data were weighted on age, gender and income for each ad model
to match the behavioral campaign delivery data. The control group was also weighted
to match campaign delivery for each ad model, and similar to the behavioral analysis, only
those brands utilizing a test model were included in the pre-roll comparisons. Additional
proportional weighting was used when aggregating brands to ensure equal distribution
of brands by ad model.
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The analysis of the survey measures involved looking at differences between test and
control groups for each individual unit and comparing those per-unit lifts with the lift for
pre-roll to see if the new unit generated higher (and statistically significant) lifts than did
the pre-roll benchmark. In the following charts, the point differences between each exposed
and control comparison and percent increases are shown only when they are statistically
significant. Point differences should not be directly compared between the groups, but the
percentages can be used for this purpose.
Sample sizes and campaign details are shown below.
ADVERTISER A ADVERTISER B ADVERTISER C ADVERTISER D ADVERTISER E
05.03–08.31
06.11–06.30
04.05—06.30
01.30—03.31
11.14—01.22
Controlled
1309
1127
1574
2012
965
Pre-roll
277
453
193
207
100
AOq
384
280
249
148
129
APq
530
–
–
–
154
ASq
–
–
173
112
178
SOq
–
251
163
152
–
2500
2111
2352
2631
1526
FORMATS TESTED
TOTAL
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Overall, the q units successfully lifted unaided brand awareness, online ad recall and
campaign message association at levels that were equal or greater to pre-roll in effectiveness.
And as seen with the behavioral results, the specific strengths of each q unit varied,
suggesting that selection depends on overall campaign goals.
Top-of-mind brand awareness increased across the board, with three of the units – ASq,
APq and AOq – significantly outperforming the pre-roll benchmark. Those lifts were
+57%, +48% and +41% higher than their control numbers, respectively.
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TOP-OF-MIND UNAIDED AWARENESS
Control
Pre-Roll Exposed
Control
New Unit Exposed
17%
AOq
21%
+4 pt 24% lift
17%
24%
+7 pt 41% lift
24%
APq
29%
+5 pt 21% lift
23%
34%
+11 pt 48% lift
24%
ASq
29%
+5 pt 21% lift
23%
36%
SOq
+13 pt 57% lift
12%
16%
+4 pt 33% lift
12%
15%
+3 pt 25% lift
25%
50%
Indicates significance at 95% confidence level vs. control
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TOTA L UNAIDED AWA RENESS
Control
31%
34%
31%
AOq
Control
New Unit Exposed
+3 pt 10% lift
39%
Total unaided awareness was also lifted for
three of the units, all of these being more
effective than the pre-roll benchmark. AOq
saw a +26% lift while APq’s lift was +41%.
ASq registered a +34% lift over control.
Pre-Roll Exposed
+8 pt 26% lift
30%
APq
34%
29%
41%
+12 pt 41% lift
38%
ASq
42%
+4 pt 11% lift
38%
51%
+13 pt 34% lift
31%
34%
31%
33%
SOq
50%
100%
Indicates significance at 95% confidence level vs. control
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ONLINE AD RECA LL
Control
Pre-Roll Exposed
Control
New Unit Exposed
22%
AOq
32%
+10 pt 45% lift
32%
+9 pt 39% lift
23%
With online ad recall, all the ad units
produced lifts in online ad recall compared to
control groups. Only ASq realized a lift that
was significantly higher than that of pre-roll,
at +74%.
24%
APq
39%
+15 pt 63% lift
39%
+15 pt 63% lift
24%
23%
ASq
32%
+9 pt 39% lift
23%
40%
+17 pt 74% lift
21%
SOq
27%
+6 pt 29% lift
21%
28%
50%
+7 pt 33% lift
100%
Indicates significance at 95% confidence level vs. control
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CAMPAIGN MESSAGE RECALL
Control
Pre-Roll Exposed
Control
New Unit Exposed
4%
AOq
11%
+7 pt 175% lift
3%
16%
Correct campaign message recall,
associating the campaign slogan with
the advertised brand, was strongly
impacted by exposure to all units,
particularly for AOq (+433%), APq
(+400%) and ASq (+320%), where
the lift was significantly higher than
the pre-roll benchmark.
+13 pt 433% lift
4%
APq
14%
+10 pt 250% lift
4%
20%
+16 pt 400% lift
5%
ASq
15%
+10 pt 200% lift
5%
21%
+16 pt 320% lift
3%
SOq
9%
+6 pt 200% lift
3%
10%
+7 pt 233% lift
12.5%
25%
Indicates significance at 95% confidence level vs. control
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BRAND FAVORABILITY
Control
Pre-Roll Exposed
Control
New Unit Exposed
36%
AOq
43%
+7 pt 19% lift
35%
35%
All q units except AOq showed a lift in brand
favorability after exposure, although none was
significantly higher than for pre-roll.
49%
APq
60%
+11 pt 22% lift
48%
53%
+5 pt 10% lift
41%
ASq
50%
+9 pt 22% lift
40%
48%
SOq
+8 pt 20% lift
26%
31%
+5 pt 19% lift
31%
+5 pt 19% lift
26%
50%
100%
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Similar to brand favorability, all units but AOq produced lifts in likelihood to recommend
versus control, but none were significantly higher than for pre-roll.
LIKELI HOOD TO RECOMMEND
Control
Pre-Roll Exposed
Control
New Unit Exposed
32%
AOq
38%
+6 pt 19% lift
32%
34%
45%
APq
53%
+8 pt 18% lift
51%
+7 pt 16% lift
44%
38%
ASq
44%
+6 pt 16% lift
38%
43%
+5 pt 13% lift
23%
SOq
27%
23%
27%
+4 pt 17% lift
+4 pt 17% lift
50%
100%
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PURCHAS E INTENT
Control
Pre-Roll Exposed
Control
New Unit Exposed
24%
AOq
28%
+4 pt 17% lift
23%
26%
+3 pt 13% lift
39%
APq
45%
+6 pt 15% lift
38%
42%
+4 pt 11% lift
31%
ASq
35%
+4 pt 13% lift
The purchase intent measure, in which
it is often difficult to see a lift, registered
a significant increase for AOq, APq and
SOq compared to the control group.
For SOq, it also significantly outperformed
pre-roll (+31% lift compared to +13%
for pre-roll).
31%
33%
SOq
13%
16%
+3 pt 23% lift
13%
17%
+4 pt 31% lift
25%
50%
Indicates significance at 95% confidence level vs. control
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AD MODEL RECA LL AND EN GAGEMENT
Recall Ad Unit Type
Selected Ad or Interacted with Ad Unit
AOq (n=1,190)
39%
9%
APq (n=684)
19%
12%
ASq (n=463)
20%
12%
SOq (n=566)
41%
11%
25%
50%
After exposure to an ad unit, consumers were asked if they remembered the type of ad they
had seen and whether they had made a selection or interacted. Results showed that people
did—to a greater or lesser degree—remember a “non traditional” type of ad unit; greater
numbers could recall the interaction units (AOq and SOq) than remembered the choice
units (APq and ASq). However, about the same proportion of those exposed to each q unit
said that they had engaged with that unit.
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S u m mary
Below is a summary of all the key attitudinal metrics and how they compare to pre-roll.
PRE-ROLL
AOq
APq
ASq
SOq
AOq
LIFT VS. CONTROL
APq
ASq
SOq
PERCENT DIFFERENCE/LIFT VS. PRE-ROLL
TOP-OF-MIND AWARENESS
+24%
+41%
+48%
+57%
+25%
TOTAL UNAIDED AWARENESS
+10%
+26%
+41%
+34%
ONLINE AD RECALL
+45%
+39%
+63%
+74%
+33%
MESSAGE RECALL
+175%
+433%
+400%
+320%
+233%
PURCHASE INTENT
+17%
+13%
+11%
No lift
+31%
+71%
No Lift
+160%
No difference
+147%
No difference
+129%
+171%
Significant Lift +209%
No difference
+60%
No difference
No difference
-
+90%
No difference
+60%
No difference
-
+35%
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Based on these findings, both AOq and APq outperformed pre-roll on three attitudinal
measures (top-of-mind awareness, total unaided awareness and message recall). ASq
demonstrated, again, that it is superior to pre-roll on all awareness and recall measures.
And SOq did significantly better on purchase intent.
AOq
APq
ASq
SOq
LIFT VS. PRE-ROLL
ATTITUDINAL
METRICS
Top-of-Mind Awareness
x
x
x
Total Unaided Awareness
x
x
x
Online Ad Recall
Message Recall
Purchase Intent
x
x
x
x
x
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Re s e a rch C onc lusio ns
In looking at both behavioral and attitudinal results from the field trial, it is evident that
all q units have a place in an online video portfolio, depending on advertiser preferences
and campaign goals.
ASq SHOWED THE HIGHEST OVERALL PERFORMANCE OF ALL FORMATS ACROSS METRICS
AOq SHOWED LIFTS OVER PRE-ROLL IN CLICK-THROUGH RATE, ENGAGEMENT, AWARENESS AND RECALL
Allows deeper experience without navigating away from content
APq WAS THE TOP PERFORMER IN CLICK-THROUGH RATE AND ENGAGEMENT AND ALSO OUTPERFORMED
PRE-ROLL ON AWARENESS AND RECALL
Provides opportunity for choice and for viewer feedback
SOq WAS THE ONLY NEW q UNIT TO BEAT PRE-ROLL ON ALL THREE BEHAVIORAL MEASURES (COMPLETION,
CLICK-THROUGH RATE AND ENGAGEMENT) AND WAS THE ONLY UNIT TO INCREASE PURCHASE INTENT
Offers opportunities for deep interaction on various brand pages
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PRE-ROLL
AOq
APq
ASq
SOq
RATE
AOq
APq
ASq
SOq
PERCENT DIFFERENCE/LIFT VS. PRE-ROLL
COMPLETION RATE
75%
75%
67%
78%
79%
0%
-7%
+5%
+1%
CLICK-THROUGH RATE
0.55%
0.67%
2.21%
0.77%
0.41%
+22%
+195%
+5%
+5%
ENGAGEMENT
0.72%
0.94%
3.88%
2.44%
0.52%
+31%
+288%
+165%
+6%
PRE-ROLL
AOq
APq
ASq
SOq
LIFT VS. CONTROL
AOq
APq
ASq
SOq
PERCENT DIFFERENCE/LIFT VS. PRE-ROLL
TOP-OF-MIND AWARENESS
+24%
+41%
+48%
+57%
+25%
+71%
+129%
+171%
No difference
TOTAL UNAIDED AWARENESS
+10%
+26%
+41%
+34%
No Lift
+160%
Significant Lift
+209%
-
ONLINE AD RECALL
+45%
+39%
+63%
+74%
+33%
No difference
No difference
+90%
No difference
MESSAGE RECALL
+175%
+433%
+400%
+320%
+233%
+147%
+60%
+60%
No difference
PURCHASE INTENT
+17%
+13%
+11%
No lift
+31%
No difference
No difference
-
+35%
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AOq
APq
ASq
SOq
LIFT VS. PRE-ROLL
BEHAVORIAL
METRICS
ATTITUDINAL
METRICS
Completion Rate
x
x
Click-through Rate
x
x
x
x
Engagement
x
x
x
x
Top-of-Mind Awareness
x
x
x
Total Unaided Awareness
x
x
x
Online Ad Recall
Message Recall
Purchase Intent
x
x
x
x
x
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CONCLUSION
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The Win n in g Un its
It is clear that all three new q units, together with ASq, have a role to play in the online
video world. Depending on an advertiser’s preferences and objectives, one or more of
the new offerings would be likely to provide superior results over the standard pre-roll
model. Each q unit excels in different areas, and all units benefit consumers, media
companies and advertisers.
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Best for: Fe at uring seve ral Ad Options/
p ro d u ct s in one unit
Variations: Numbe r of tabs, tab options,
in clu s ion of minimize but ton
Opportunities: Inc lude soc ial me dia,
s u rvey que st ions and aDDit ional Video
ch o ices into unit
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Best for: Offe ring e asy e ngage ment and
feedback abilit ie s to viewe rs
Variations: que st ion t ype , c alls to action
Opportunities: Re -target to viewers who
a n s we r posit ive ly
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Best for: Offe ring e asy e ngage me nt
a n d in c re asing pe rformanc e
Variations: Single vs. mult iple
a d vertise r slate s
Opportunities: explore thumbnail
p erfo rmanc e and re -target ing
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Best for: Allowing viewe rs to e asily
a ccess soc ial me dia
Variations: Numbe r of but tons, social
m ed ia net works, ove rlay location
Opportunities: Bring soc ial inte raction
in to the ad playe r, allowing viewers
to share or like your brand without
leaving site c onte nt
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LEVERAGING THE q UNITS
The q units are available to all publishers, advertisers and agencies. All publishers who are
VPAID compliant and integrated with VINDICO support the q units.
Interested advertisers should contact their media partners for more information and
specifically request the ASq, AOq, APq and SOq to be included in their online video plans.
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THE POOL: UNCOVERING NEW UNITS IN THE ONLINE VIDEO SPACE aol online video lane
50864_Cover.indd 1
The Pool:
Uncovering New Units
In the Online Video Space
AOL Online Video Lane
1/8/13 11:05 PM