How Is Artificial Intelligence Controlling What You Stream on Netflix or Hulu?
Artificial Intelligence (AI) is a widely used technology in many fields, and streaming giants like Netflix and Hulu are not an exception. There are a lot of streaming service providers; therefore, every provider is going the extra mile to ensure they attract clients. AI gives Netflix and Hulu users a more personalized and friendly experience. They suggest content based on recent activities,
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Creating Customer’s Journey: Netflix Artificial Intelligence
Netflix and Hulu create a consumer’s journey that captures the users’ preferences and experiences in a single image. In addition, the image contains extensive data that includes the needs, motivating factors, and overall platform experience.
AI used by Netflix and Hulu creates its consumer journey and continues to personalize your user experience. And they aim to solve any shortcomings or gaps in your user experience. As much as Netflix artificial intelligence recommends shows based on your recent interests and browsing history, it does not recommend top shows limited to certain regions. However, you can consider changing your Netflix region to a country like US with a more extensive library of shows, by tricking your location settings using VPN or proxy services.
The personalized experiences and recommendations allow you to create your own experience and gain control of your entertainment streaming. In addition, AI dismisses what is not working and puts more work on what is working.
Calculated Moves or Not?
Most of Netflix’s decisions on marketing their original shows seem highly deliberate because they are. Netflix’s marketing team makes decisions whose purpose is to maximize its potential to excite its viewers using netflix artificial intelligence. The team uses artificial intelligence to merchandise shows and foretell their success in a way that no other entertainment house has ever achieved.
Deliberate marketing helps determine the audience size and finds connections through transfer learning. The variables learned from the “source task” improve the “target task” performance. Source tasks can take the form of a question like “what titles are the same as a Netflix original?”
Artificial Intelligence also helps in thematic comparisons. For example, Netflix creates a similarity map in which AI uses a specific show’s tags, metadata, and summaries that provide links to other titles.
Customized artwork/ image thumbnail
They say that presenting a meal may entice or discourage you from partaking in the meal. There is a similar situation in movie recommendations. For example, the image thumbnail shown in the recommendations row may encourage or discourage you from watching a movie without knowing what it entails.
Netflix and Hulu want to ensure the image they choose to showcase will positively affect you as the user. So they use Artificial Intelligence to create a personalized thumbnail to achieve that outcome. Using data from your clicking behavior and that of other users with similar interests, it will look at which thumbnail had the most clicks. They will then try that specific thumbnail since it will likely work on you.
Artificial Intelligence also considers the movies being suggested side by side or at the same time when personalizing the artwork. It ensures that the thumbnail presented next to it blends well.
Audience Sizes
Hulu and Netflix use artificial intelligence to compare the audience size in a particular country of a similar show they are about to release. If a specific show is likely to do well in India, the streaming giants will market the show and prepare subtitles earlier.
The systems have access to a wide range of information. And it means that they are not limited to only the data of either Netflix or Hulu. The wide range of information access affects all audiences in the services offered.
Creating A Universe of User Profile Interests
Using artificial intelligence, Netflix can collect data and create a user profile. The user profile is made based on numerous distinctive characters. The universe of user-profiles aims to help group users with similar interests.
By grouping users with the same interests, they can use data from one user to predict the behavior of other users. For example, the algorithm uses favorite movie genres, titles, actress/actor.
Keeping Tabs and Luring
An average user is estimated to lose their interest within the first minute to their second if nothing is worth watching, depending on their interests. Artificial intelligence technology keeps tabs of previous interactions to personalize the user’s experience to their best interests.
So, the data collected by Netflix and Hulu show that users have different viewing habits depending on the day of the week, location, device, and even time of the day. AI then is set to predict and provide the viewer with the best experience. The algorithm increases customers’ consumption time and helps maintain the fan base.
Streaming Quality
Netflix’s artificial intelligence technology uses previously collected viewing data to forecast bandwidth usage. The bandwidth usage helps Netflix decide when to cache regional servers for quicker loads when the demand is high.
Evidence Algorithm in Netflix Artificial Intelligence
Artificial intelligence has an evidence algorithm that helps users decide if what they have selected is what they want to stream. The variables used include; information on the show predicted star rating and icons shown on the row.
It shows whether the movie has won an award or the icon that the user will probably choose from the row for the algorithm to create a personalized experience.
Wrapping Up!
In a modern changing world, maybe artificial intelligence controlling what you stream is not a bad idea. As AI creates a more personalized experience for the users, users can also cultivate a feeling of control over Netflix and Hulu. But, on the other hand, they gain a deeper understanding of what drives their fan base, therefore, improving the consumer’s experience.
Brantlee Bhide is a project manager at HB Consultancy. She has 16 years of experience working as a project professional across varying industries, countries, and cultures. She operates in both business and technical domains using an approach that she developed.
