A Brief History of Netflix Personalization and the Importance of Mastering the Basics

A Brief History of Netflix Personalization and the Importance of Mastering the Basics

Part Two: From 2007 to 2021

Introduction:

In this article, we will explore the fascinating journey of Netflix's personalization efforts from 2007 to 2021. We will delve into the various milestones and strategies that Netflix implemented to improve the user experience and retention rates. Additionally, we will discuss the importance of mastering the basics in any field and how it can lead to significant advancements and success.

Netflix Streaming Launch and the Netflix Prize (2007):

In 2007, Netflix made a groundbreaking move by launching its streaming service. This marked a significant shift in the company's approach to delivering content to its users. Alongside the streaming launch, Netflix introduced the "Netflix Prize," offering a reward of $1 million to any team that could improve the predictive power of their collaborative filtering algorithm by 10%.

The Power of Ratings and Multiple Algorithms (2007-2009):

During the Netflix Prize competition, participants discovered that recent ratings provided by members held more predictive power than older ones. This realization led to a crucial insight: all ratings are not created equal. Netflix recognized that incorporating more algorithms into their system could enhance its accuracy and provide better recommendations to users.

The Disappointing Results of the New Algorithm (2010):

In 2010, Netflix tested the new algorithm developed through the Netflix Prize in a large-scale A/B test. They hoped that this algorithm would improve member retention rates. However, the results were disappointing, as there was no measurable difference in retention. Despite this setback, Netflix decided to share all their learnings from the Netflix Prize, allowing other companies to study and benefit from their findings.

The Birth of the Movie Genome Project (2011):

In 2011, Netflix introduced the "Movie Genome Project," a new movie genome algorithm called "Category Interest." This algorithm enabled Netflix to suggest movies to users while providing context for why a particular movie may be of interest to them. It was a significant step forward in personalization, allowing for a more tailored and accurate movie recommendation system.

Understanding Netflix's Personalization Algorithms (2011):

Netflix's personalization approach consists of three key components. Firstly, they create a forced-rank list of titles for each member, prioritizing content based on the likelihood of pleasing the user. Secondly, they identify the most relevant filters for each member, allowing the algorithms to present a subset of movies and TV shows from the forced-rank list. Lastly, they understand the most relevant rows for each member, considering factors such as the platform, time of day, and explicit/implicit movie taste data.

Proof of Personalization's Impact on Retention (2011-2013):

By 2011, Netflix had accumulated enough evidence to show that personalization significantly improved retention rates. They realized that personalization not only delighted customers but also helped them "right-size" their content spend. With knowledge of member tastes, Netflix could accurately predict the number of viewers for a specific movie or TV show and make informed investment decisions.

Profiles Re-invented (2012):

In 2012, Netflix reinvented user profiles, allowing each member of a household to have their own profile. This further enhanced personalization by tailoring recommendations to individual viewers' tastes and preferences.

Language and Geography as Predictors (2015):

In 2015, Netflix conducted a demographics test and discovered that language and geography were not effective predictors of a member's movie preferences. Instead, they found that the most efficient way to seed a member's taste profile was to ask for a few TV shows or movies they loved. This finding highlighted the importance of personalization and individual preferences over general demographics.

The Shift from Stars to Thumbs (2016-2017):

In 2016, Netflix conducted an A/B test of their five-star rating system against a simpler thumbs up/down system. Surprisingly, the thumbs system collected twice as many ratings, indicating that simplicity often leads to higher user engagement. Following this test, Netflix decided to phase out the star ratings and introduced the "percentage match" system, which indicated how much a viewer would enjoy a movie, regardless of its quality.

The Evolution of Personalized Movie Art (2018):

In 2018, Netflix introduced personalized movie art, further tailoring the user experience by showcasing artwork that aligns with individual preferences. This added a visual element to the personalization efforts, enhancing the overall user interface and engagement.

The Long-Term Vision of Personalization (2021):

Looking ahead to the future, Netflix envisions a time when personalization becomes seamless and automatic. Their long-term vision involves eliminating the "Play Something" button and personalized merchandising systems. Instead, Netflix aims to automatically play the one movie that perfectly matches a viewer's mood and preferences at any given moment.

The Importance of Mastering the Basics:

While Netflix's journey in personalization is undoubtedly impressive, it is essential to remember the importance of mastering the basics. Scott H Young, in his article "You're Never Too Good for the Basics," emphasizes that advanced knowledge is built upon a solid foundation of fundamental skills. Just as most math is arithmetic, running a successful business relies on keeping revenues above costs, and good writing stems from clear ideas and clean sentences.

Young suggests three actionable pieces of advice for returning to the basics:

• 1. Change your environment: By altering your surroundings, you can create an environment that encourages a focus on the basics. Removing distractions and setting up a conducive space can help you prioritize fundamental skills.

• 2. Change your goals: Setting different standards for what you want to achieve can shift your actions towards mastering the basics. By redefining success and focusing on the core elements, you are more likely to excel in your chosen field.

• 3. Reflect and analyze: Take the time to examine your work after the fact. Analyzing mistakes and learning from them when you're not in the midst of making them can help you identify areas for improvement and strengthen your grasp on the basics.

Conclusion:

Netflix's journey in personalization showcases the power of leveraging data and algorithms to enhance the user experience. From the Netflix Prize to the Movie Genome Project, Netflix has constantly strived to deliver tailored recommendations and improve member retention. However, amidst the advancements, it is crucial to remember the significance of mastering the basics. By focusing on fundamental skills and returning to the core elements of any field, we can lay a strong foundation for growth and success. So, whether you're navigating the world of personalization or pursuing any other endeavor, never underestimate the power of the basics.