FEATURE: BIG DATA
SINCE ITS DEPLOYMENT
IN 2009, SIMS HAS
PROVED A HUGE ASSET
TO FORD, DYNAMICALLY
RECOMMENDING THE
OPTIMAL NUMBER
AND TYPES OF MODELS
DEALERSHIPS SHOULD
ORDER
unprecedented move, Netflix ordered
two seasons upfront, something
unheard of in the TV industry.
Despite Hollywood executives openly
questioning the logic as a pilot episode
hadn’t even been filmed at the time of
purchase, Netflix was convinced it was
making a shrewd investment.
Why? Because it had analysed user
behaviour. Armed with the knowledge
that House of Cards would be a political
drama directed by David Fincher and
starring Kevin Spacey, Netflix drilled
down through its data to see whether
subscribers would be receptive to such
a show. Predictive analytics gave a
high probability that the drama would
be a hit with customers based on the
following:
• David Fincher directed film The
Social Network was a popular choice
on Netflix and was watched from
beginning to end.
• The British version of House of Cards
had a strong viewership.
• Those who viewed the British version
also watched Kevin Spacey films and/
or films directed by Fincher.
The predictive analytics turned out to
be correct. House of Cards was a critical
and commercial hit when it debuted in
2013. The show attracted three million
new subscribers to the streaming
service and was nominated for 14
awards after its first season, winning
four of the categories. Such was the
ROI, that this jump-started Netflix’s
original programming strategy. The
company currently has over 30 shows
in production including other acclaimed
hits such as Orange is the New Black
and Daredevil. Growth has continued
with the service doubling its subscriber
base from 36.3 million at the beginning
of 2013 to over 69 million in 2015.
Recently, Netflix decided to make
an even bolder move based on data.
The firm decided not to renew its
$1bn deal with movie distributor Epix,
determining that user demand for
42
INTELLIGENTCIO
mainstream films such as The Hunger
Games and Transformers did not
justify investment over the creation of
original content.
Netflix has not only leveraged the
power of Big Data to drive decisions
about the creation of original
programming, it’s also deployed
machine learning to provide every user
with a personalised homepage.
“To algorithmically create a good
personalised homepage means
assembling one page per member
profile and device from thousands
of videos that may be relevant for
a member and from easily tens of
thousands of potential rows, each
with a variable number of videos.
On top of that, we need to balance
several factors that often compete
for precious screen real estate. Our
approach to personalisation and
recommendation largely focuses on
helping our members find something
new to watch, which we call discovery,”
Justin Basilico, Research and
Engineering Manager noted on the
Netflix Blog.
“To do this, we can use a machine
learning approach to create the
scoring function by training it using
historical information of which
homepages we have created for our
members, what they actually see, how
they interact, and what they play.”
The above examples demonstrate the
power of analytics and Intel believes
it can provide businesses with the
compute power, visualisation tools and
infrastructure to apply these principles
across verticals from financial through
to healthcare industry.
Businesses can draw on the experience
Intel has had working within multiple
partners including CERN, which has
been tackling one of the biggest data
projects on the planet. Collecting
data at the research facility has
provided significant challenges as the
Large Hadron Collider used during
experimentations has produced up to
1PB of data per second.
www.intelligentcio.com