Averages (even with the post's approach) still have the problem of not being "honest" in the game theory sense. For example, if something is rated 4 stars with 100 reviews, a reviewer who believes its true rating should be 3 stars is motivated to give it 1 star because that will move the average rating closer to his desired outcome. A look at rating distributions shows that this is in fact how many people behave. Med…
I wonder if a system that assigned weights to each individual user's rating based on that user's rating history could help there - if a user always rates products with 5-stars, then another 5-star rating shouldn't have nearly as much weight as one coming from a user that gives a fairly balanced range of ratings. I'm not sure if that would actually work better in practice, but it's at least an interesting idea.
Then I realized that it would just incentivise bots to add 1-star reviews to random products once their creators figure out this mechanism.
Sometimes these problems make me sad, it could all be so nice and easy if it weren't for these bad actors.