Double Thumbs Up for Better Netflix Recommendations

How effective will the new Two Thumbs Up feature be for Netflix?

Advait Lad
Product Coalition

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Photo by Thibault Penin on Unsplash

Netflix’s Recommendation Engine (NRE) has had a huge part to play in the success of the OTT giant. It is highly accurate and relevant, so much so that about 80% of Netflix’s viewer activity is driven by personalized recommendations from the engine. Reports estimate that NRE saves the company north of $1 billion every year.

A large contribution to NRE’s high performance is from the data collected when users interact with the platform — when they watch, like, or dislike the content. The latest addition to user engagement options for the users is ‘Two Thumbs Up’. The Two Thumbs Up feature is an additional way for the users to let the platform know that they are like what they see. It is different from the already existing thumbs up feature in that thumbs up indicates that users like the content but double thumbs up would suggest that the users love the content.

Double Thumbs-up Feature by Netflix

The idea behind this button is that the previous thumbs up and thumbs down buttons helped Netflix understand what the users liked and disliked. These data points were used to recommend content to the users. But studies suggest that users' feelings about content can go beyond simply liking or disliking. So with the introduction of this new two thumbs up button, users will now possibly be able to further fine-tune their recommendations on the platform. For instance, if the users like a show, say Stranger Things. NRE can now show you shows and films with similar cast or by the same creators of Stranger Things.

Although, I am curious as to why Netflix would want to add something like this over a star rating system — something they’ve already tried in the past. The Vice President for Product, Todd Yelin mentioned that the rating system was removed because it feels “very yesterday”. Additionally, Christine Doig-Cardet, Director of Product Innovation at Netflix explained in a blog post -

“Providing an additional way to tell us when you’re really into something means a profile with recommendations that better reflect what you enjoy.”

She also mentioned that -

“We’ve been hearing from members that it’s important for them to distinguish [between] shows they liked and the shows that they really loved — and that distinction was important to them.”

This would not be the first time Netflix has made a change after listening to what users wanted. Recently, Netflix add a feature that gave users the ability to remove titles for the “Continue Watching” section.

Christine introduced the feature as a button that will be placed alongside the thumbs up and thumbs down buttons. But, an important thing to note is that while double thumbs up would carry an additional weightage over the previously present thumbs up button, it does not mean that it has double the weightage.

How can Netflix measure the success of this new feature?

  1. Tracking the number of hits on the button: This would be the key metric that Netflix would want to track to see if the people are actually using this feature.
  2. People comments on social platforms: Twitter is usually a good place to gauge people's opinions on anything new that happens in the world. People are usually vocal with their tweets and studying those tweets can be a good way to judge if the users are liking this feature. Linkedin is another platform that can be a good option to get insights into how the users are feeling about this feature.
Photo by Prateek Katyal on Unsplash

This new Two Thumbs Up feature is the first update Netflix has had in five years to the rating system and the first for this year. It would be interesting to see if Netflix ramps up and introduces additional personalization features that would help users further personalize their content library on the platform.

Netflix Design Team Netflix Technology Blog

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Data Product Manager @ KPMG | A product enthusiast who loves to talk about features, user workflows and strategies that drive people towards products.