Audience analysis and content personalization according to the buyer persona.
Being a platform aimed at consumers with a very wide age range, Netflix must ensure that its content is reaching the right audience. For this, it is necessary to do an analysis of their consumers and discover the interests of each one of them through machine learning algorithms.
What is machine learning?
Machine learning is positively related to artificial intelligence.
It is the ability of a software (machine) to learn through algorithms thanks to the entry of data into the system.
In other words, it is automatic learning based on information that is collected and analysed. In this case, the software can ''guess'' what type of content you are going to see on Netflix from the content you have already seen.
For example. If you like romantic movies, the cover will show you the one on the left, on the contrary if you like thrillers you will see the one on the right.
To make the Netflix offer attractive to their customers, they have a formula based on the personalization of suggestions, according to their history. But this customization goes further, as Netflix also adapts the covers of the series and movies it offers depending on the content we have consumed. Thus, the same product has several bodies with different aesthetics, and each client sees one according to their tastes and what they see most; be it romance, science fiction, action, horror, etc. (Stranger Things series case)
Have you ever noticed this?
The same series but with a different cover
In addition to the personalization for film tastes, there is also segmentation based on actor preferences. This is the case of Pulp Fiction; the clients will see the classic cover with Uma Thurman if they have seen the content of that actress as the main character. On the other hand, if the customer has seen Grease or Saturday Night Fever recently, Travolta will appear on the cover.
Content personalization influences users when deciding what content to consume. It convinces that the content is worthwhile and manages to capture the attention of consumers with different tastes to see the same series or movie.
Analysis: Ariadna Verdú
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