How to try out the latest experimental Netflix features. Netflix is obsessed with testing; the company tests every new feature before rolling it out widely. Here’s how it works and how you can opt-in. Netflix might not roll out features quite as frequently as something like Google Maps, but the company does push plenty of new features in Netflix every now and then (remember Netflix games?).
If you’re someone who loves to experience new features before they are available globally, chances are you’d love to try out Netflix’s experimental features. That’s where Netflix’s “Test Participation” program comes in. So, here’s how to try out Netflix beta features.
Everything You Should Know About Experimental Netflix Features
Before launching a new feature like the Play Something button on Netflix, the company rolls out the experiment to limited beta testers. Apart from that, Netflix heavily uses experimentation to decide on button placements, UI, UX, movie art, and more. Let’s see how you can enable the Test Participation feature to get these exciting experiments before everyone else.
How to Opt-In to Netflix Tests – experimental Netflix features
If you want to ensure you’re constantly experiencing the advanced version of Netflix, you need to opt in to receive tests and previews. By default, everyone is included in this, but here’s how to check that you didn’t opt out previously:
- From the Netflix website, hover over your profile picture in the top-right.
- Click Account.
- Next to Settings, click Test participation.
- Turn to Include me in tests and previews on and click Done.
It’s important to note that while opting out of this test participation program excludes you from seeing new trial features, it doesn’t mean that you won’t be exposed to A/B testing of existing features—more on that later.
Why Does Netflix Experiment and How Does It Work?
Netflix tests everything: registration, playback, recommendations, search… you name it, it’s tested. The reason for this is that Netflix wants to check its assumptions. It doesn’t matter how hard a Netflix employee pushes for an idea—data inform decisions, not opinion. Otherwise, a change could fail drastically because it was based on a hunch.
The company does this through A/B testing. At its core, A/B testing is a way of comparing two versions of something to see which is the most successful. The measure of success isn’t always the same; it depends on the change. The experiment might aim to see which version gets more people to register, or discover new Netflix shows, or stay watching for as long as possible.
Netflix isn’t just testing two versions, though. It has such an expansive user base, not only in terms of raw numbers but also in demographics and behavior. It means that Netflix can separate its users into many experimental groups, trialing ever-so-slightly tweaked versions to see which is truly optimal.
As detailed on the Netflix Technology Blog, Netflix assigns its users to these groups through batch and real-time allocation. The batch assigns a fixed set of members to an experiment who are known to meet the trial’s criteria. Real-time is more flexible, shuffling users in and out of tests as they interact more with the platform.
What Features Has Netflix Tested?
Netflix is always testing changes and new features. Some of these never make the light of day, while others are now beloved components of the platform. Examples of past Netflix experiments include:
- Changing the size of the tiles on the homepage to see which encouraged users to watch.
- Changing the tone of the call-to-action button on the homepage to see which encouraged users to click through to sign up.
- Introducing collections of content curated by Netflix’s creatives, rather than an algorithm, to see if it encouraged users to watch something outside their usual recommendations.
- Charging subscribers who share their Netflix account outside their household, to see if revenue grew through existing customers.
- Introducing a button that displays something psuedo-randomly for someone to watch (based on their watch history and recommendations) to see if it increased watch time and decreased time spent scrolling.