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viewers which is often used alongside the
viewers preferences when they first on-
boarded, to curate personalized content
recommendations. This includes what
the viewer searched for, what videos they
played and at what time of day, whether
they watched to the end, how long it took
them to watch, how long each viewing ses-
sion lasted, as well as video ratings and
popularity. Put all of this together and mix
in some clever algorithms, and video ser-
vices then know which movies and shows
the viewer will enjoy watching the most.
Unfortunately, it’s not quite that sim-
ple because the way that viewers engage
with content is incredibly nuanced. Difer-
ent viewers like diferent things, and this
goes much deeper than diferent genres
or types of content. For example, out of an
audience who all like a certain genre, let’s
say, action and adventure, the same trail-
er may not necessarily hook in all view-
ers. What appeals to one consumer may
not necessarily appeal to another. Video
providers can attract a wider variety of
viewers to a particular show if the trailer
is personalized to appeal to their individ-
ual tastes. This is an area that AI is driving
forward, with new software able to create
custom images, videos and trailers to sup-
port the decision making process.
For example, if a viewer sees a trailer
featuring their favorite actor, that will ap-
peal to them most, while another viewer
may not be interested in that actor but may
prefer shows that have a strong female
lead, so a diferent trailer may work bet-
ter for them. By showing diferent viewers
trailers that are personalized to appeal to
their individual preferences, providers are
much better able to encourage viewers to
watch content. Similarly, thumbnails can
also be personalized in much the same
way as trailers can, in order to have the
most impact. This process involves choos-
ing the single frame from a show or movie
that is most likely to resonate with the in-
dividual viewer and using it as the thumb-
nail. By selecting the frame that best cap-
tures their interest, the platform increases
the chances that viewers will click on the
title and start watching.
Impact of AI on personalization
Before the advent of AI, video services
relied heavily on static user profiles, lim-
ited metadata, and manual tagging of con-
tent for personalization. With AI, the pro-
cess is faster and more accurate, which
makes it both more efcient and efective.
Using AI and ML, providers can identify
nuanced patterns in user behavior, which
enable dynamic and adaptive personaliza-
tion that evolves with the user’s preferenc-
es in real time.
AI vastly speeds up the processes that
enable personalization. Let’s consider
tagging as an example. For content rec-
ommendations to be accurate, video pro-
viders need to understand and know the
content of shows and movies down to the
minutia detail. In the past, this would have
involved teams of staf, some in-house and
some freelance, sitting down and watch-
ing every show in detail then accurately
tagging it.
Yet these days, with AI, the entire key-
word tagging process can be automated.
And additionally, it can also add a great
deal of detail which would not have been
practical when the process was done man-
ually. Detailed keyword tagging helps vid-
eo services to better identify similarities
between content so that recommenda-
tions can be more diverse but still be ac-
curate and appeal to viewers. In this use
case, it’s easy to see that AI not only saves
time and efort, but also makes the process
more efective.
Beyond personalization, AI plays a cru-
cial role in enhancing the user experience
by optimizing streaming quality. Take Net-
flix, for instance, which leverages machine
learning algorithms to monitor network
conditions in real time and dynamically
adjusts video quality. By assessing factors
such as bandwidth, device type, and geo-
graphic location, Netflix ensures the best
possible video resolution while reducing
bufering and interruptions. This seam-
less performance not only keeps users
engaged but also encourages them to stay
on the platform because loading times are
fast and playback is smooth.
What will personalization mean in
tomorrow’s world?
Efective personalization is fundamen-
tal to a video provider’s success. Without
it, the viewer won’t be able to easily find
content they want to watch, and addition-
ally the content that they may enjoy may
not appeal to them at first glance. AI is en-
abling video services to deliver faster and
more precise recommendations with an
improved user experience. Already AI can
help providers to infer mood and deliver
emotionally and situationally appropriate
recommendations. The question is, how
might this develop and improve as time
goes on and AI technology continues to
advance?
It will most likely become even more pre-
cise and intuitive as AI systems are used to
analyze subtle behavioral cues like voice
tone and biometrics to understand the us-
er’s mood and anticipate their preferenc-
es. I expect the content creation function-
ality of AI will continue to advance, even
being able to create unique content expe-
riences, such as diferent opening scenes
or alternate endings, designed to provide
each viewer with the experience that they
will enjoy the most. I have a feeling that we
are only at the beginning of what AI-driven
personalization can deliver — it’s going to
be an exciting ride for sure.
A customer experience expert, Nikki
has been with Accedo for more than 8
years and has driven some of our largest
UX engagements across the APAC region.
She is skilled in UX & UI, Strategy and
Research. She leads Accedo’s team of
designers in Asia Pacific. When not at
Accedo you can find her on the Rugby
League field, passionate about playing and
coaching young women in the sport.
Continued from previous page
Yet these days, with AI, the entire keyword tagging
process can be automated. And additionally, it can
also add a great deal of detail which would not have
been practical when the process was done manually.
By DAK DILLON
Managing Editor, NewscastStudio
From sophisticated targeting in con-
nected TV to AI-driven predictive mod-
els that anticipate audience behavior, the
broadcast adtech landscape is undergoing
a reinvention driven by emerging technol-
ogy like artificial intelligence.
New research confirms advertisers’
growing commitment to programmatic
strategies, while industry executives pre-
dict that AI will continue to unlock un-
tapped revenue potential. Here’s how it’s
playing out in practice.
Programmatic, CTV surge ahead
A recent “2025 State of Programmatic
Report” by Proximic, a division of Com-
score, found that 72% of advertisers plan to
increase programmatic spending in 2025,
strongly emphasizing privacy-compliant
approaches. Connected TV is at the center
of this spending surge, now commanding
28% of ad budgets — double what it was in
2023. According to the report, nearly half
of marketers reallocating their program-
matic CTV budgets by shifting funds away
from linear TV.
“Connected TV emerged as a clear win-
ner, and privacy-focused strategies like
contextual targeting are becoming essen-
tial for marketers aiming to deliver highly
efective, privacy-centric campaigns,” said
Rachel Gantz, managing director at Proxi-
mic by Comscore.
This shift isn’t surprising given that
consumer viewing habits favor stream-
ing over traditional cable bundles. At the
same time, the appetite for more automat-
ed buying practices has grown, with data
from Advertiser Perceptions showing an
uptick in programmatic guaranteed deals
on subscription video-on-demand (SVOD)
platforms.
What does all this mean
for broadcasters?
It suggests that ad budgets — historical-
ly the lifeblood of linear television — are
increasingly in play. Linear TV isn’t disap-
pearing overnight, but it’s facing renewed
competition from CTV and digital services
that can better target and measure audi-
ences. That shift, executives note, is where
AI can make a substantial diference.
“By analyzing viewer data, AI is able to
pinpoint content that resonates with au-
diences the most,” said Siddarth Gupta,
principal engineer at Interra Systems.
“Personalized ad insertion further max-
imizes revenue by matching ads to indi-
vidual preferences or the type of content
being viewed at the time.”
In other words, AI-driven personaliza-
tion is no longer a novelty; it’s a business
imperative, helping broadcasters capture
attention in a hyper-competitive ad mar-
ket.
Personalization and contextual
advertising in broadcast
Amid privacy crackdowns and the slow
demise of third-party cookies, advertisers
are turning to new, “ID-free” solutions that
rely on contextual and first-party data.
Proximic’s programmatic report noted
that 48% of marketers expect to rely pri-
marily on ID-free strategies by the end of
2025, and 52% plan to increase their use
of contextual data for targeting. These fig-
ures underscore the importance of align-
ing ads with relevant content or themes
rather than just behavioral profiles.
“AI can enhance content monetization
… enabling dynamic ad insertion, ensur-
ing more relevant ads and driving higher
engagement and revenue,” said Yang Cai,
CEO and president of VisualOn. This per-
sonalized approach is central to strategies
like contextual targeting, where AI scans
video or webpage content to place ads that
mesh seamlessly with the viewer’s experi-
ence.
Beyond simple text analysis, AI models
can detect visual cues, sentiment and even
brand safety issues within video content.
That granular understanding helps adver-
tisers avoid mismatches — like a children’s
toy ad running against adult-themed pro-
gramming — and allows them to place ads
when a viewer is most receptive.
Stefan Lederer, CEO and co-founder of
Bitmovin, said one of AI’s greatest strengths
is “to efciently and accurately search, tag
and categorize content … unlocking new
advertising revenue potential through
AI-powered contextual advertising.”
This means that archival footage or
niche programming can suddenly become
revenue-generating assets, provided the
right sponsors are matched to the right
content.
Monetizing content with AI: Going beyond
traditional advertising to unlock new value
ADVERTISING
Continued on next page
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can email editor@newscaststudio.com
with a brief pitch.
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tions of contributing, please see Page 2
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