Moving from Video Interruption to Integration Through Contextual Advertising
Moving from Video Interruption to
Integration Through Contextual Advertising
Video advertising has become a highly effective tool
for brands and marketers to communicate their messages to online audiences. In
the year 2018, $10.228bn were spent in digital video advertising in the United
States alone.
Since its inception, video advertising has faced the
criticism of being inherently interruptive in nature. Online users tend to skip
or ignore ads that appear to them as annoying or interruptive. This
non-engagement of users with the ads is a serious headache for marketers, and they
are struggling to find the way out.
Research shows that brands are now increasingly
concerned about the interruptive user experience when running their video
advertising campaigns. For brands, user experience has become a significant
factor to consider while devising their video advertising strategy. Brands are
trying to make in-video ads more engaging and less annoying for users. In order
to draw effective user engagement, ads should be able to capture the user
attention in the first few seconds.
Video ad formats also play an important role in driving
better user experience and engagement. By deploying better formats, marketers
can make their advertising strategy more effective. According to eMarketer,
sixty percent of video ads fall in the in-stream category. Majority of the
marketers are currently deploying interruptive in-stream ad formats that can be
easily skipped or ignored. Pre-roll and post-roll are used more often over
other formats such as overlay video and mid-roll. Overlay ad format, which
places an ad over the video content, offers an advantage over other in-stream
formats of not overtly interrupting the underlying video content being watched
by the user. Thus, overlay ads are less annoying and tend to provide better
user experience.
Mid-roll format is least favored by the marketers,
especially for short video content, because it is highly interruptive.
Therefore, marketers are currently mainly utilizing pre- and post-roll
in-stream ad formats for achieving their advertising goals and the whole video
content itself is being left uncapitalized. Here, the overlay format comes to
rescue. It allows marketers to capitalize on the unutilized video content
without being interruptive to users.
Brands have identified certain obstacles in the path
of video ad innovation. These include inadequate budget, lack of in-house
expertise, misaligned in-house teams, lack of agency relationship, and lack of
strong external technology partnership. To achieve their video advertising
goals, brands and marketers should focus on innovative, non-interrupting ad
formats. But only using the right in-video ad format will not work, marketers
should make use of robust, efficient and effective advertising technology such
as AI advertising, and give utter importance to context. They should serve
contextually relevant in-video ads that are well-aligned with the content the
user is consuming.
According to the industry experts, video advertising
strategy in the future will be impacted by factors such as demand for
non-interruptive ads, growth of over-the-top and connected TV ad formats,
growth of social networking and video sharing advertising formats, and demand
for contextual advertising.
Users’ demand for non-interruptive ads on connected TV
has grown over the years in sync with the growth in its viewership. Currently,
in-stream video advertising on this platform is largely interruptive in nature.
Contextual video advertising offers an effective solution to marketers to
mitigate this interruption on connected TV and enhance user experience.
By using the right mix of in-video ad formats and
contextually aligned ads, advertisers can turn upside down the user experience
from being interruptive to engaging. To display contextually aligned video ads,
a highly effective solution is afforded by AI powered in-video context
detection technology.
However, AI-powered solutions that are dependent on machine
learning, NLP and semantic analysis, miss the mark when it comes to understanding
the sub-text, nuanced contexts and complex relationships words have in written
or spoken language.
Computer vision powered contextual advertising technology
provides very high degree of context relevance. This technology works by
accurately detecting contexts in video such as faces, emotions, logos, objects,
scenes and activities in order to display in-video ads that are in line with
what the user is actively engaging with. Highly contextually relevant ads
appear non-interruptive and appealing to users, and boost the chances of users
watching or clicking them.
With AI-powered contextual video advertising,
marketers can seamlessly integrate ads with the video content the user is
watching, thereby providing a non-interruptive, highly engaging user
experience.
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