“Recommended for You”: How Netflix’s Algorithm Sells the Illusion of Choice

Apr 17, 2025

By: Julia Zhou

When you open Netflix, there’s always something ready for your mood, your vibe, and your taste. It feels effortless, like the platform knows you. And maybe it does—or at least its algorithm does. According to Statista, Netflix has over 300 million subscribers globally and generated $39 billion in revenue by the end of 2024. Netflix’s position as the global leader in streaming is no accident. It is clear that Netflix’s powerful recommendation engine understands your preferences and subtly reshapes them. 

Courtesy of Shutter Speed via Unsplash.com

Beneath the seemingly effortless one-click interface is one of the most influential marketing machines in the world, where your engagement data constantly fuels future recommendations. What feels like your own choice is often just the most clickable option curated by Netflix, not necessarily the best one.

The Algorithm Behind the Curtain

More than 80% of what users watch on Netflix comes from algorithmic suggestions of their recommendation system. Every user journey—from awareness to “conversion” (in this case, pressing play)—is mapped out by backend systems, pushing content that matches users' past behaviors. Netflix knows exactly how you watch by collecting your data about viewing habits, time of day, devices used, genre preference, pause times, skipped intros, rewatched scenes, or drop-off after 20 minutes. With this vast data, it builds and feeds predictive models that curate auto-play trailers, homepages, and even the order of episodes.

Personalization

Courtesy Via Netflix.com

In 2017, Netflix publicly shared that it customizes cover images to appeal to individual viewer profiles. Take Emily in Paris, for example. Even if you’re not actively searching for a rom-com, having watched shows like Gossip Girl might get Emily in Paris featured on your homepage—likely with a glamorous shot of Lily Collins in front of the Eiffel Tower. But if you usually lean toward comedy, you might get a different cover: maybe a goofy moment of Emily running into her ex. On the other hand, Stranger Things might display Eleven’s telekinetic powers to sci-fi fans, a close-up of Mike and Eleven for romance lovers, or a dark Demogorgon shot for horror enthusiasts. 

Netflix is constantly "repackaging" the same product, tailoring content to your tastes, keeping you engaged and coming back to the platform. What makes Netflix’s content marketing effective is that it doesn’t just promote what to watch, but offers users the illusion of choice, making it feel like you discovered the content yourself.

The Feedback Loop

In a world of countless streaming platforms and shrinking attention spans, Netflix’s goal isn’t just to recommend shows. It’s to keep you watching, subscribing, and feeding the system. Every click, pause, and scroll generates data, which helps the algorithm make smarter and more personalized recommendations. The more you engage, the harder it becomes to look away. 

Say you finish Love Is Blind. Soon after, your homepage starts overflowing with Single’s Inferno, Too Hot to Handle, Perfect Match, and other dating reality shows. The system could become self-fulfilling. You watch what’s recommended. Netflix sees that you watched it. It recommends more of the same. Over time, your content diet narrows, not because you don’t want variety, but because the platform believes predictability is what keeps you clicking.

14 Best Dating Shows on Netflix to Find Love via Netflix Tudum

This is both powerful and dangerous. Relevance can drive retention, but it can also limit discovery and personal growth. The strategy raises ethical concerns about how far platforms should go in tailoring experiences to user behavior. Over time, users might sink deeper into their comfort zones, eventually stopping their exploration of new content. At that point, would they even know what they truly want to watch? The algorithm’s heavy reliance on data tracking becomes questionable when its primary goal is to maximize engagement rather than support curiosity, learning, or meaningful exploration. When data is used to keep us watching instead of thinking, we have to ask ourselves: Is personalization just another form of manipulation? Who Gets a Spotlight?

Courtesy via Netflix Engagement Report 2H 2024, Top 10 TV shows via Netflix Tudum

Netflix also plays a role in deciding what becomes a hit. Its curated Top 10 lists aren’t always organic, and because it controls what gets recommended most, the rankings are often tweaked to align with what Netflix wants to promote.

For instance, when Wednesday premiered, it was a well-made show that also received heavy promotion from the platform. It was everywhere: homepage banners, autoplay trailers, and constant placement in genre rows. The result? Viral TikTok dances, trending gothic fashion, and 1.24 billion viewing hours in its first 28 days. Meanwhile, shows like 1899, a mind-blowing multilingual series from the creators of Dark, got far less promotional support and were canceled after just one season. Even with high-quality content, a show's success often depends on whether it’s favored by the algorithm or seen as commercially viable.

The Hidden Cost of Seamless Streaming

Netflix operates as both a brand and a media buyer, controlling both the content and the platform. This can create pressure for producers and industry professionals. Since Netflix evaluates whether shows are ‘hype-worthy,’ creatives pitch their work to a system that prioritizes algorithmic performance over artistic depth and storytelling. Renowned director and producer Cary Fukunaga, known for his work on Netflix’s Maniac, has spoken about the influence of Netflix’s algorithm on his creative decisions:​​ “Because Netflix is a data company, they know exactly how their viewers watch things. So they can look at something you're writing and say, We know based on our data that if you do this, we will lose this many viewers. So it's a different kind of note-giving. It's not like, let's discuss this and maybe I'm gonna win. The algorithm's argument is gonna win at the end of the day.”

As users, it’s easy to get swept up in the seamless, satisfying experience Netflix offers—shows that match our mood, autoplay that keeps us hooked, and endless content that feels made just for us. But behind that ease is an algorithm designed to keep us watching, not to expand our worldviews. As our taste palettes are increasingly shaped by data-driven systems, it's worth asking what we’re not seeing. We need to be intentional with seeking out stories beyond our comfort zones, exploring different cultures, and challenging our usual genres.

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Julia Zhou is a sophomore studying Media, Culture, and Communication with a minor in Web Programming and Application. She loves writing, traveling, and making matcha.