The Problem With Netflix's Algorithm — And How to Fix It

Netflix's recommendation algorithm is designed to maximize one thing: watch time. Not quality, not satisfaction, not whether you'll remember the movie tomorrow. Here's why that's a problem.

Optimized for Engagement, Not Quality

Netflix's algorithm learns what keeps you watching. That sounds good in theory, but it means the algorithm favors easily digestible content over challenging, rewarding films. A mediocre thriller you'll half-watch is more "valuable" to Netflix than a brilliant drama you'll pause to think about.

The Hidden Gems Problem

Netflix has thousands of movies. But their algorithm surfaces the same few hundred titles over and over. High-quality films with lower viewership numbers get buried because they don't generate enough "engagement signals."

Here are some movies currently on Netflix with GoodScore 80+ that the algorithm probably never showed you:

The Fix

Instead of trusting a single platform's algorithm, use a composite rating that draws from multiple sources. GoodScore combines IMDb, RT, Metacritic, and TMDB — so popularity alone can't inflate a movie's ranking. Add emotional profiles on top of that, and you get recommendations based on what's actually good for your mood, not what Netflix wants you to binge.