1/13/2023 0 Comments Thortspace review![]() I’m actually rather fond of the rating system. However, ratings help users to make rational decision-making. Thumbs up/thumbs down would more likely be a good solution if you are looking to increase user engagement, and to give your users a more personalised experience. It’s worth noting that every product is different, and this simpler rating system might not work in all cases. Users usually rated videos they really love or absolutely hated, thus creating the same, good old J-shaped curve. In 2009, Youtube made the same shift as Netflix for its video rating. The music-streaming platform, Spotify, also uses a thumbs up/thumbs down model for its radio service, that helps personalise better (more personalized) content for its users. Netflix is not the first tech giant to choose this direction. On the one hand, the new rating system annoyed some users, and created a lot of frustration but on the other hand, the streaming giant has reported that it saw a 200% increase in users leaving ratings, and now has new match percentages (up to 100%) to more accurately predict what users are more likely to watch. Netflix introduced thumbs up/thumbs down feature Therefore, it’s hard, visually, to evaluate, or make use of these ratings when they are all almost all the same. Put simply: generally average scores of ratings clump together between 4.5 to 4.7. The end result is that this creates a J-shaped curve of biased ratings ( In economics, the ‘J curve’ is the time path of a country’s trade balance following a devaluation or depreciation of its currency, under a certain set of assumptions according to Wikipedia). And this is a systematic problem with many online ratings - they tend to over-represent the most extreme views. You see, I tend to rate the products I bought, or the services I used, only when they exceeded my expectations, or when I really had a bad experience. Having said that, I myself am part of the problem with ratings. I find, though, that I can’t just blindly trust them. The J Curve - Achilles’ heel of Biased RatingsĪs a Product Designer, I try hard to evaluate the products and services I’m working on and ratings are one of my main ways of doing this. To be honest, most of the time, it’s way better just to ask a local person for advice. For example, I never rely on the TripAdvisor recommended top places for a simple reason - when I’m showing friends or guests around my home city, Vilnius, Lithuania, and I want to find a good place to eat, none of my favourites features in the top 10 list that shows up. And we tend to trust some ratings more than others, or at least I do. You want a nice place to stay on your vacation, so you check the reviews of the Airbnb apartment you just found. For instance, you order Uber ride: you rate your driver after your trip, and driver rates you, too! You’re looking for a movie to watch, so you check a movie’s ratings on IMDb or Rotten Tomatoes. ![]() However, rating systems are entirely subjective and can, therefore, be inaccurate because they’re not based on data, more on feelings and emotions. The very idea of a sharing economy depends on mutual trust, and ratings are a huge part of that. Watch this funny short video about 5-star ratings from Saturday Night Live
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