sort of ‘serendipity’ of discovery of something
you wouldn’t normally watch.”
“We don’t believe people are going to be
looking to do wholesale start-over strategies,”
reveals Christensen. “The technology has
advanced to a level now where you can solve
these issues with point solutions – but it needs
to be thought through end-to-end. Otherwise
it will never work. To increase their level of
personalisation, there are capabilities that need
to be built into different parts of the platform.
There’s no one point solution that’s ever going
to get you there. You need insights about the
content, you need insights about the end user,
you need the ability to present that to the end
user, and you need recommendation engines
and lean-back capabilities to keep the end user
engaged. But If somebody tries to convince you
that you have to replace your entire platform –
that’s not the way to do it.”
ALGORITHMS. “Providers can help to make
their consumer facing UIs and apps better by
continually iterating upon and improving the
algorithms their discovery and recommendation
tools employ,” suggests Adams. “Using more
granular data to better describe a show along
with more contextual data points around that
show, such as how long a viewer spent watching
and how many episodes were binge watched in
succession, will help drive a more targeted set
of programme suggestions. Because
content recommendation algorithms
run on descriptive metadata, it goes
without saying that using the highest
quality data and richest visual
imagery can also have a significant
impact on delivering better, more
satisfying user experiences.”
“UI-UX specialists have done
their homework and noted that
people do not consume the same
content every time they turn on
their preferred viewing device,”
adds Smith-Chaigneau. “The parameters that
influence them are mood, time/day of the week,
location, and device.”
“Whether a service upgrades its current
infrastructure or creates a new platform
altogether, the aim is consistent: to create a
frictionless experience for consumers,” states
Signorelli. “AT&T is employing a revamped
service platform with HBO Max to best
consolidate its multifaceted content portfolio.
Netflix, on the other hand has edited and
upgraded their format for many years now. Each
operator will need to employ whichever method
works best given the structure of their services
and content in conjunction with improved use of
data and consumer profiling.”
BUBBLES. “Successful content presentation
and recommendation creates the impression of
always discovering something new,” observes
ruwido’s Maier. “The recommendation engines
of some providers generate content-filterbubbles
that
continuously
provide
viewers with
the same
content and
nothing new.
To reach user
experience
excellence, it
is essential
to provide
the perfect
“Successful
content
recommendation
creates the
impression
of always
discovering
something new.” –
Ferdinand Maier,
ruwido
alignment of personalised content combined
with seamless interaction supporting several
modalities. ruwido has been investigating for
years now, how to manage this by intelligently
mixing AI-approaches with traditional modelling
approaches of human activities or tasks.”
“Providers should focus and create shortcuts
on two core cases,” recommends Fröhlich. “First,
they should prioritise the continue-to-watch
function. This might be an obvious one, but
many platforms have not yet perfected this point.
Especially cross-device watching often fails to
satisfy. Second, discovery should be a priority.
Users want to get relevant recommendations. If
platforms don’t manage this, they should focus
on optimising the search function instead.”
“Like in other technologies, there are
“TiVo has
focused on
Natural
Language
Processing.” -
Charles Dawes,
Xperi
many failed or poor
recommendation systems,
which simply haven’t
delivered any meaningful uplift or change
in consumer behaviour,” advises Docherty.
“ThinkAnalytics are seeing video service
providers coming round for ‘a second go’
at implementing a more comprehensive
system which includes not just search and
recommendations but also all the analysis/
insight behind that. Today, using a cloud-native
learning platform, it is possible to launch in
weeks, not months and to see a fast uplift in
engagement, delivering a great ROI.”
GOAL. “This really depends on what the
provider already has and what the ultimate
goal is for their content discovery experience,”
suggests Xperi’s Dawes. “In our recent
experience, many companies are looking for a
solution that allows them to make steps into a
next generation of service without completely
throwing out the baby with the bathwater. TiVo’s
Next-Gen Platform was designed with this in
mind and allows a provider to actually mix both
approaches. This approach allows you to
replace the core platform with the latest
advancements in IPTV whilst providing access
to multiple clients that can be upgraded or
replaced depending on the differing needs of the
customer base.”
There is no easy journey to the top, but it
starts with getting your data under control,”
says Bergström. “Regardless of your starting
position, you will need high-quality data as
the foundation for your recommendation and
personalisation strategy. Start by enhancing the
quality of your data, getting a clear ID-structure
in place and begin measuring how users are
interacting with your platform. Once you have
done that, evaluate the possibilities of your
current platform – does a strong foundation in
data give you the benefits you need or do you
need to upgrade your platform to something that
is more dynamic.”
Christensen says that if you really
want to drive true personalisation – which
everybody wants to do – you need to have a
broad definition for that. “It goes far beyond
recommending content based on what the
viewer looked at the last time. It goes into
having a deep understanding of what content is
engaging the user and, more importantly, why.
In order to do that you have to go far beyond the
traditional level of content metadata: you have to
understand that this is about the psychographics
that drive engagement with the content.”
NIRVANA. “Here’s the nirvana point
with personalisation: The video and offer
presented to me were the right things to get
me to subscribe; once I subscribed, the service
presented me the right things I should be
watching to keep me engaged and watching
more; any ads were the right ones to keep me
engaged in the monetisation opportunities; and
finally, when I was thinking about cancelling,
the service put the right asset or offer in front of
me to keep me from churning. There are many
services trying to solve various points of that
puzzle but not many are managing it as part of
an ecosystem,” declares Christensen.
EUROMEDIA 13