Have you ever noticed that when you are watching your favorite show (or have finished it) on Netflix, the platform suggests similar shows, as if it already knows what you want to watch next? There’s actually a lot of science and computing behind it, and you’ll be surprised to find out how platforms like Netflix and HBO Max can pull that off.
There is a lot of data that goes behind all of those curated suggestions, based on the type of content that you consume. The driving force behind the concept is big data in streaming, which basically gives you access to a more personalized streaming experience.
However, your streaming and data processing require a stable internet connection so that you can stream in the best picture quality, and the platform runs AI content recommendations in the background. In that case, it is highly necessary that you choose an internet connection that works best for both of these factors.
You can look up for options but we recommend to pick Spectrum Internet for its outstanding connectivity without data caps. Simply connect with Spectrum customer services, and get to know all your options before deciding on one. Once you have the internet connection of your choice, you can stream to your heart’s content for some data-driven entertainment.
Coming back to streaming platforms, here are the amazing ways in which streaming platforms utilize big data to suggest hyper-personalized content.
Advanced Data Collection
Streaming platforms pay a lot of attention to data collection so that they can give you recommendations based on what you watch. The streaming platform algorithms keep a close eye on what you watch so that they can fetch shows of a similar nature.
These services gather enormous amounts of data, which includes watching history, search queries, watch times, social media activity, and biometric data (but only if you give it permission to do so). The culmination of all this data lies in the foundation of the recommendation process, which allows you to have a hyper-personalized streaming experience based on what you want to watch.
Artificial Intelligence and Predictive Analytics
Streaming platforms also make use of machine learning algorithms so that they can analyze the data they collect and predict viewer preferences with a lot of accuracy. For instance, if you just finished watching Breaking Bad, the platform will likely suggest that you watch Narcos next, since both these shows have a somewhat similar theme.
Artificial Intelligence is primarily used to identify the micro-genres of your preference and subtle patterns in your viewing habits so that the platform can anticipate what you might be watching next or recommend something new to watch that has a similar nature. This way, you don’t run out of shows and movies to watch and can stick to the genre of your preference. In fact, these platforms can also help you figure out what to watch next, even if you don’t already know what to watch next.
This helps you keep your options open, and who knows, you might even like another genre and start watching that one instead.
The viewer behavior analytics analyzes your behavioral patterns so that it can recommend something that suits your temperament and taste.
If you want to find out more, this article explains how streaming platforms use AI to curate recommendations for you, improving your overall streaming experience.
Editing and Dynamic Content Insertion
Have you noticed that for every person who opens a streaming platform, the recommendations and posters are always different? This is based on the visitor’s watching experience and their preferences. However, dynamically altering the content isn’t as easy as it seems, which is why there is technology behind it that handles the job.
These subtle changes can range from showing different movie posters for everyone based on their interest (for instance, one person might see comedy movie posters while another might see action movie posters) to showing snippets from shows and movies, part of their soundtrack, and even iconic character dialogs to grab the watcher’s interest. This can help improve the viewer’s taste so that they don’t run out of options.
Interactive Storytelling
What I love most about streaming is when I get to watch something interactive, such as Black Watch: Bandersnatch, in which the movie progresses according to the choices that I make throughout the movie. This makes it possible for us to have multiple possibilities in the movie, leading to different endings as well. All of this is done through big data, machine learning, and AI as well.
The viewer’s choices are logged and then analyzed to refine future content offerings and all the possibilities that branch out once a decision is made in the movie.
If they can do it with one movie, I hope they make a lot more as well, since I remember the movie being very engaging back in 2018. Imagine all the possibilities in the future (no pun intended). So here’s to hoping they make similar movies in the future, making us feel like we’re a part of the movie too.
You can head to this article to find out whether interactive films are really the future of streaming or not.
Technology and Micro-Targeted Advertising
If streaming platforms are smart about it, they can use hyper-personalization for advertising as well. Advertisers can leverage this technology to create highly targeted and specific ads that grab the attention of viewers without the ad going to waste.
The ads can be shown to individual viewers based on what their interests are, which can help change the way of the streaming revenue by increasing it exponentially. Therefore, not only is this technology useful for streaming platforms, but for advertisers as well.
So there you have it, this was everything you needed to know about hyper-personalization in streaming platforms so that you can improve your overall watching experience! I highly recommend that you give Bandersnatch a shot, too, so that you can experience what a personalized movie feels like, making the outcome based on what you decide throughout.
