As the COVID-19 pandemic rages on, more and more people are turning to streaming services for their entertainment needs. But streaming services have been steadily gaining in popularity since 2015, when just over half of U.S. residents paid for some sort of subscription-video-on-demand service (SVOD), such as Netflix and Hulu. As of 2020, that number had climbed to an impressive 78%.
Today, consumers have a wide variety of SVOD service providers to choose from, and each platform wants to attract and retain as many customers as possible. As such, the tech behind popular streaming platforms is constantly evolving to better meet consumer demand, and individual user experience is of paramount importance. Streaming services in 2021, including relative newcomers Disney+ and HBO Max, are utilizing powerful artificial intelligence (AI) and machine learning algorithms to keep users coming back for more.
But how does tech such as machine learning give users a highly personalized experience? The answer lies in big data and continued innovation into these promising technological advancements. Here’s what you need to know about how various streaming giants use AI, machine learning, and big data to retain customers and improve their overall journey.
Defining AI and Machine Learning: What’s in a Name?
Netflix, the kingpin of the U.S. streaming market, has been at the forefront of machine learning and AI for several years. According to Wired, the platform’s recommendation system was responsible for 80% of viewer choices in 2017 alone. That system, using AI, analyzes a viewer’s chosen content based on content tags as well as user behavior data ranging from how long one watches a particular show to time of day, and even cultural context.
Netflix collects so much user data that software intervention is necessary to make sense of it all, much less tailor recommendations based on the information. That’s where machine learning comes in. Machine learning expands on the concept of artificial intelligence to help an algorithm or software, whether used by a streaming platform or in some other capacity, effectively make its own decisions.
For its part, the Netflix research team is heavily invested in machine learning and uses the tech in various ways. Personalization is arguably the most well-known, but Netflix also utilizes machine learning when developing original shows and content. In recent years, Netflix has become a force to be reckoned with in the movie industry, and the company couldn’t have gotten there without machine learning.
The Role of Big Data in Streaming Platforms
Despite its ability to effectively think for itself, however, machine learning can’t do it alone; along with daily intervention from humans, AI tech gets a major boost from big data as well. And when used by streaming platforms, the machine learning-big data partnership creates a competitive advantage over other companies. The massive amounts of data collected by Netflix, Hulu, and other streaming platforms are typically too complex for traditional data processing software to handle, and big data is up to the task.
Additionally, big data helps identify frivolous data and subsequently discard it from the machine learning process. For users of streaming services, the veracity of data can further refine recommendations for even better personalization. And when customers don’t have to continuously scroll through haphazard options to find interesting and/or relevant content, they’re more likely to stay loyal to a particular platform.
It’s important to note, however, that even the most advanced machine learning processes aren’t infallible. For example, Netflix’s machine learning algorithms came under fire in 2017, accused of providing “biased and discriminatory outcomes.” The increase of original programming on the streaming platform in recent years has also raised concerns that user recommendations skew towards Netflix originals.
Driving the Consumer Journey in 2021 and Beyond
Once a fringe element of the entertainment industry, streaming platforms have become an integral part of everyday life, and a big business, to boot. As of 2020, researchers determined that the global streaming market was valued at $50 billion. What’s more, the streaming industry is expected to grow at least into 2028, thanks in large part to continued advancements in AI technology. The personal nature of streaming is one of its strongest selling points, so much so that personalization is now an expectation of the customer journey in numerous other industries in addition to entertainment.
Increasingly, companies of all sizes are creating customer journey maps that aim to capture the entire user experience in a single, usable image. Yet the word “map” in this context is a bit of an oversimplification, as the customer journey diagram contains an extensive amount of data, including user motivation, needs, and overall experience. The AI utilized by streaming services effectively creates its own version of the customer journey map. Then, it takes that map to further personalize the customer experience and identify any gaps or customer pain points that need to be addressed.
Key Takeaways
In our rapidly changing modern world, machine learning is crucial to the modern customer journey, and streaming services are leading the charge. AI and machine learning create personalized recommendations that subsequently allow customers to create their own experience with streaming platforms, dismissing what doesn’t work and emphasizing the features and programs that do.
And it’s a win-win situation for both parties: Users cultivate a sense of control over their entertainment while streaming companies (from Netflix and Hulu to Disney+ and Amazon Prime) gain greater insight into what drives their customer base, further elevating the user experience.
Luke Smith is a writer and researcher turned blogger. Since finishing college he is trying his hand at being a freelance writer. He enjoys writing on a variety of topics but technology and entertainment topics are his favorite. When he isn’t writing you can find him traveling, hiking, or gaming. You can find Luke on Twitter @lukesmithwrites