RESTON, Va., April 7, 2021 /PRNewswire/ -- Television
leaders are always evaluating how they can improve the viewer
experience and ensure quality business outcomes for their
advertising partners. That's why Comscore (Nasdaq: SCOR), a trusted
partner for planning, transacting and evaluating media across
platforms, is excited to share that a Syracuse
University research paper analyzing audience retention,
powered by insights from Comscore, won first place in the Open
Paper Competition for the Broadcast Education
Association (BEA) Research Division.
The paper, entitled "Developing an Ad Viewing Retention Model
for TV Comedy Through Machine Learning," presents a model that can
potentially be used to predict audience retention at various levels
of ad pod saturation, thus allowing networks to curate commercial
breaks to optimize the viewer experience.
The research team applied its proprietary machine learning to
Comscore's signature TV Essentials® second-by-second television
viewing data, program ratings, and to Comscore's Exact Commercial
Ratings® data to identify key attributes and patterns that
optimally predict commercial viewership.
Key Insights
- Predictability was achieved at up to an 80% accuracy rate.
- The model validates that ad retention is highest at the
beginning of the pod and during shorter breaks.
- A surprising finding is that the program's view-through
percentage is a strong attribute in predicting audience retention.
This suggests that program content may play a role in maintaining
commercial audiences.
"We're excited to see that our ongoing collaboration with
Syracuse University is driving
actionable results and that Comscore's powerful insights are
continuing to fuel research and innovation across the industry,"
said Nancy Beall, Executive Vice
President, Commercial.
The paper was authored by Fiona
Chew, Professor of television, radio and film,
and Beth Egan, Associate
Professor of advertising, along with Chilukuri K. Mohan, Professor of electrical
engineering and computer science, Sanup Araballi, Dongqing Xu and Amanda Qi Ni. This is the team's
second BEA win together after their 2019 paper "TV Program-Ad Genre
Congruence and Ad Avoidance: Applying Neural Networks to Assess
Effects" took top place in the BEA's research division.
The research was funded by a CUSE Grant and is an
interdisciplinary collaboration between the Newhouse School and the
College of Engineering and Computer Science, with information
provided by Comscore. The paper will be presented at BEA's virtual
annual conference in April
2021.
Comscore TV Essentials® provides television buyers and sellers
with precise, massive-scale measurement of national television
programming and advertising. Leveraging TV viewing from more than
60 million screens and more than 30 million households across the
U.S., TV Essentials offers a level of granularity and stability
absent from traditional television measurement services – including
more precise and more reliable ratings for large and niche networks
alike – all day, every day.
With more than a decade of experience measuring television
viewership from return path devices across tens of millions of
households in all local markets, Comscore is a trusted source for
television viewing data. Comscore is also a leader in advanced
audiences, which allow the industry to go beyond age and gender to
transact on consumer behaviors, interests and lifestyles. This
enables TV stations, networks, advertisers, agencies and media
companies at both local and national levels to effectively find and
reach their ideal audiences to maximize their revenues.
About Comscore
Comscore (NASDAQ: SCOR) is a trusted
partner for planning, transacting and evaluating media across
platforms. With a data footprint that combines digital, linear TV,
over-the-top and theatrical viewership intelligence with advanced
audience insights, Comscore allows media buyers and sellers to
quantify their multiscreen behavior and make business decisions
with confidence. A proven leader in measuring digital and TV
audiences and advertising at scale, Comscore is the industry's
emerging, third-party source for reliable and comprehensive
cross-platform measurement. To learn more, visit
www.comscore.com.
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SOURCE Comscore