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The Network Effect and Impact on the Media

The widespread use of streaming services in the modern media space can be considered a trend of the last decade. A good understanding of all the tools and methods of product promotion is what makes the difference in this highly competitive environment. Network effect is one of the key factors any content maker should pay attention to. The essence of the network effect is simple: the more often a consumer uses a product, the more valuable that product becomes to other users. It is easy to see how the network effect works in various media cases.

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One of the most popular broadcasters of the recent time, Netflix, can serve as an example of the positive impact of network effects. This company started with DVD delivery and then moved on to online streaming. When profit margins began to change, third-party content providers began to leave the platform, and Netflix had to re-engage and to start producing its own content. These radical changes allowed the company to succeed. At the moment, Netflix’s subscriber base exceeds 200 million, and the company’s revenue is expected to be around $20 billion in 2021. Disney Plus, being almost similar streaming video platform, also adheres to the subscription model, although being a fan-service for Disney company. Thus, among streaming services, it is the subscription model that looks the most competitive and profitable.

Some similarities in development can be seen between Netflix and YouTube. However, there are two significant differences. First, it is a different monetization model. YouTube has only recently begun to introduce a subscription model for users, and for most of its existence income has been from advertising inserts in the player. The second feature is that content on YouTube is produced by users themselves. As it scales, there is more and more content, so a very logical conclusion is recommendation system, for this reduces the signal-to-noise ratio. Each user gets the content based on their preferences. Each user gets the content they are more likely to like based on their preferences. It should be noted that approximately the same algorithm has been working successfully for some time at Netflix.

One of the features of personalized content on YouTube has been a kind of bias toward later content-makers, while earlier ones will get some privileges in terms of recommendations for users. A good example here is Joe Rogan, one of the most well-known podcasters, who started uploading his interviews with celebrities back in 2009. This made him one of the first content makers and led to a steady growth in audience and, which resulted in an increase in influence. However, that growth stopped with the signing of an exclusive contract with Spotify, whose monetization is mostly based on subscriptions. By moving to another platform, he lost the positive influence from the network effect that other content makers on YouTube were producing.

However, there are many positive examples of scaling after switching to a subscription model. One of such examples is certainly This sports resource was founded by experienced authors who left their previous job and started their own site. Thus, their content reduced the signal-to-noise ratio to almost zero when compared to their previous place of publication. Their audience began to receive only the articles they liked. The network effect created a steady increase in subscribers, and the subscription model led to exponential revenue growth for the new company.

To sum up, hasty decisions can lead to irreparable consequences, both financial and image. Only a good awareness of all the principles and phenomena of the modern media market protects the content maker from collapse and leads to the top. The network effect is a very powerful factor, which can have both positive and negative effects on the media. It is very important to take it into account and calculate all possible risks before making important decisions.

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