Show HN: I built a Rotten Tomatoes-style platform for durable products

I've found a huge problem with products is that their quality changes over time. So, a product may be named the same but the SKU changes or the products from a couple of years back were much better made for whatever reason while the company has gutted them and continues to sell on reputation. I've wondered if there's a way to track product changes (user reported maybe?) between revisions of products on a wide scale. Can you convert the "years owned" to a purchase date somewhere? Are you tracking SKUs?

How will you handle fake reviews?

What I honestly dislike, however, is to see all the google tracking going on there... is that really necessary?

I like this idea and a lot of similar information sharing sites but I find in today's environment, anything successful will be targeted by misinformation and gamed which makes it difficult to determine if the information was provided in an uninfluenfed manner from the product creator/retailer/etc. who have obvious conflicted goals.

The best efforts seem to be information sites that are successful enough to gather enough data to represent something accurately from a user base but not so successful it becomes a target for corporate advertising and marketing groups. Reddit communities still provides some of this but have become a target for advertising as well and also are more difficult to extract useful information from.

Amazon has "verified purchase" which is still gamed using other techniques. I've found the best model is still Consumer Reports for fair product assessments but they only speculate on durability since it would be incredibly difficult for their product assessment model (new products rolling out frequently, modified/re-released/etc and limited staff/personal time to keep up with).

I theorized that reviewers would have their own scale, both in median (maybe they only give 4s and 5s), as well as range (a lot of people only give 1s and 5, losing all the resolution of the middle). My solution was to continuously keep each reviewer's ratings normalized both to the centerpoint (each review would have a delta added to it to re-center) as well as to standard deviation (each review would be scaled so that their overall stdev would be 1.0). The result is that everyone would look like a nice normal curve around 3.0.

This has a nice side effect of diluting ratings spam, too. If somebody spams 5s, they wind up being just average 3s. Even if they spam 1s and 5s, they're at least normalized to a lower spread.