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How Netflix uses artificial intelligence to establish its content strategy

Sam Proust by Sam Proust
October 4, 2021
in Technology
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How Netflix uses artificial intelligence
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In the race to position itself in the market, Netflix has pioneered the use of new technologies and the latest tools to read the market, better understand consumers and deliver the content they expect. His story often ends up being mentioned every time people talk about how data can help companies find their niche in the market.

Netflix has used big data to understand viewers’ tastes and the patterns behind them. Big data has helped them personalize the experience for consumers, but also to determine trends that point to the kinds of content that can be successful. His first big hit, the House of Cards series , was one of the consequences of that reading of data.

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Big data told them that it could succeed, but also how they should adjust their marketing and advertising campaigns to make it work. But the VoD platform has also become a success story in the use of artificial intelligence to shape its content strategy and its customer service. It is not a secret: Netflix itself talks about it on its corporate blogs and the US media have already made several analyzes about what the platform does and how it reaches its niche markets.

Netflix uses artificial intelligence to better understand how and what content will succeed and how to link with potential audiences who might see it. As they explain in Engadget , AI allows them to understand the connections between some content and others and to establish audience models.

How does AI work for it? Netflix uses what they call the transfer learning model, transfer learning . The AI ​​learns from a source and thereby improves the results of an objective: it studies which titles in its catalog connect with the original contents of the platform and what type of viewing those contents will generate. As they explain on Ubergizmo , they use the data of what they know you like to determine how successful the content will be and what viewing practices they might expect from their viewers.

In addition, the work of artificial intelligence allows them to understand how the contents fit together from a thematic point of view. Netflix, they explain in the American medium, creates a map of similarities that using metadata, tags and synopses of movies, series and programs is able to connect some titles with others. This creates very granular types of content. You can’t just divide something by ‘comedy’, it can also be adjusted to be coming-of-age comedies.

AI predicts in which regions it will perform best
The AI ​​allows, therefore, to separate the contents and to establish groups that will work in a similar way or will arouse the same interests. Also, and this is prominent when establishing marketing strategies, it lets them get ahead of the market. The model allows them to compare audiences in different countries and anticipate what types of content will work best in a country.

Thus, they can adjust their marketing strategy or their marketing campaign, for example by working on subtitles or dubbing beforehand because they know that this audience will want that content or by betting on making an important marketing campaign in that area so that consumers discover that content.

Frame by frame analysis
This is not the first time that Netflix has been looking at how Netflix uses machine learning and AI to reach consumers. A few years ago, their technology already earned them a purchase recommendation from investment analysts on Wall Street because their neural networks and proprietary algorithms allowed them to improve their content recommendations and also fine-tune their content purchase and production, as collected then MarketWatch .

They were not doing something that could not have been done before by their competitors, an expert explained then, but they had done it in a way that the others had missed. Netflix could analyze, the analysts pointed out, the content frame by frame to determine which scenes – and therefore what type of content at a much more granular level – aroused the most engagement.

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