watch, with an input-output ratio of 1:18. Diversified
attempts at content layout and continuous cross-
border, such as the layout of the live broadcast of
sports events: 2024 live broadcast of Tyson's and
Paul's “fight of the century” attracted 108 million
people to watch. Attracting 108 million viewers and
1.43 million new users, and obtaining the exclusive
broadcasting rights for the 2022 Women's World Cup
through cooperation with FIFA, the company has also
found a second growth curve.
Offline IP scene extension: 2025 theme parks,
dynamic theme parks, short-term, fast turnaround
park enjoyment, differentiated competition Disney.
Shift from subscription fee model to
subscription+cash. Paid subscriptions account for
98% of total revenue. Pure content-driven model. Ad
revenue doubles by 2024 to 70 million MAUs, but
penetration is only 9%, far below Disney+'s 30%,
need to supplement ad infrastructure. Globalized
supply chain + localized synergies. 190 countries
coverage, “Tower of Babel” strategy: content
localization (e.g. Korean dramas, Indian movies) +
globalized logistics infrastructure. More than 60% of
international paying subscribers, through regionally
successful local content, back into the global market,
e.g. Squid Game (Su & Zhang, 2014).
Netflix uses big data and artificial intelligence
technology to build a huge and detailed user behavior
database (Lu, 2024). The database covers multi-
dimensional behavioral data such as users' viewing
history, ratings, dwell time, fast-forward and rewind
operations, search records, etc. After collecting the
data, Netflix has built up a large and detailed database
of user behavior. After collecting the data, Netflix
utilizes complex machine learning algorithms to
deeply analyze the data.
Taking the viewing track as an example, the
algorithm is able to identify the various types of film
and television works watched by the user, different
generations and different regions respectively, and
then derive the user's typological inclination, such as
whether the user prefers science fiction or is fond of
romantic dramas (Joonas, Mahfouz, & Hayes, 2023).
for the scoring data, not only is it a simple difference
between high and low scores, but the algorithm is able
to combine the differences in the user's scores for
various elements of film and television dramas (plot,
acting, picture, etc.) to For the rating data, it is not
only the simple difference between high and low
ratings, but also the algorithm can combine the
differences in users' ratings of various elements (plot,
acting, picture, etc.) to further segment users'
preferences; for the residence time data, it can
identify users' attention to a certain plot or paragraph,
and combined with the differences in scenes, the
algorithm can derive the difference in users' attention
to the characteristics of the content elements of
different movies and TV shows.
Therefore, Netflix will produce a
recommendation list belonging to each user
corresponding to the results of in-depth mining. If
through mining, it is found that a user prefers to watch
suspenseful American dramas, and in this suspenseful
American drama, he likes to watch American dramas
with tight plots and a lot of reversals, and the
American dramas he likes to watch have high scores,
and he stops and stays for a longer period of time
during the process of watching the American dramas,
the recent popular suspenseful American dramas are
prioritized to be shown in the recommended list of the
user, e.g., Stranger Things, which is a suspenseful
American drama, and the drama is a suspenseful
American drama, e.g., Stranger Things. The show is
a suspenseful, science fiction and youth type of
suspenseful American drama, and will also be similar
to the “Stranger Things”, but may not be so hot, but
in some aspects of the high evaluation of the
suspenseful American drama show, such as: “True
Detective” Season 1, in order to meet the different
needs of different users to watch the suspenseful
American dramas.
Netflix analyzes users' behavioral data to
personalize the configuration of content production
and purchase. In terms of content production, Netflix
analyzes data to gain insight into the market and user
preferences, which in turn influences the production
and production of original content (Ramlakan, &
Gupta, 2025). For example, Netflix has analyzed the
data and learned that the viewing preference of true
crime documentaries continues to increase, and it
pays more attention to content with in-depth
investigations and unique perspectives. Based on this,
Netflix launched “Making a Murderer,” which
centers on several classic true crime cases, reflecting
the cases through in-depth analysis and unique
perspectives, and quickly gained the attention of
users, and broke the record of 10 million views soon
after its launch.
In addition to selecting partner content, Netflix
relies on data to make decisions about content
acquisition. Because consumers in different countries
and regions prefer different content, Netflix sources
content based on local consumer preferences. For
example, in some Asian countries, audiences prefer
Korean dramas, so Netflix purchases more Korean
dramas, including the world-famous “Squid Game” is
one of them. In addition, in the case that there is a
greater preference for certain stars, directors, in the
user group, Netflix will source the corresponding