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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. Differ-
ent viewers like different things, and this
goes much deeper than different 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 different trailer may work bet-
ter for them. By showing different 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 efficient and effective.
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 staff, 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 effort, but also makes the process
more effective.
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
buffering 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?
Effective 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 different 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.
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