How to use the double thumbs up feature on Netflix
Want to show Netflix that you REALLY like a show or movie? Here’s how.
Previously, when you had an opinion about something on Netflix, you could only give it a thumbs up or down or tell anyone who’ll listen. But now, the streaming platform has added an extra choice.
Clicking the new double thumbs rating tells Netflix that you “Love this!” That will train your recommendation algorithm, so you see even better matches.
Netflix spent a year testing the new feature to see if users preferred two thumbs up or the universal icon of a heart.
The two thumbs up won, possibly because of movie critics Siskel and Ebert, who used “Two Thumbs Up” as their trademarked top mark.
The feature is available on desktops, smart TVs, Android, and iOS. Let’s discuss how to use double thumbs up on Netflix.
Where to find Netflix’s double thumbs up button
Netflix’s double thumbs are easy to locate and generally hang around the Play button on most devices. The new “Love this!” rating icon appears alongside the classic “I like it” and “Not for me” options.
Here’s where to find Netflix’s double thumbs up on desktop, mobile, and TV
Regardless of your device, here’s where to locate the button that helps shape Netflix’s algorithm:
Desktop: Either hover over the Rating button for a movie/series on the Home screen or on the More info panel.
Mobile: Open the More info panel for a movie/series and tap Rate.
TV: Open the More info panel for a movie/series, and all available thumbs will appear above the Play button.
And there you have it. A quick guide to understanding where to find the newest rating system on Netflix.
Netflix should add more thumbs
The addition of the double-thumbs-up button should help the streaming platform offer more relevant recommendations to its users. In the interest of fairness, the streamer should add a double-thumbs-down option.
That would give a better indicator of which shows Netflix should cancel.
The only feature we don’t want back is user reviews. Netflix’s personalized recommendation algorithm should be trained by every individual user, not influenced by others.
Have any thoughts on this? Let us know down below in the comments or carry the discussion over to our Twitter or Facebook.
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