This is awesome! I regularly encounter the same problem. Particularly when shopping for electronics, where there is a clear metric that counts (say, USD/Watt hour for batteries). But how often had I wished something like this existed for other items as well. Say, toothpaste. What do I care about the brand? I care about the abrasivity factor (RDA), and the amount of flouride. Or sweaters. I don't care that it looks like wool, or that other people use it as replacement for wool. Instead, I want something that's 100 % wool, and no acrylics. Or think supplements. I don't care about fancy pictures of healthy people. I want to know what's in the capsule, where it was source, and how much of it I get per USD.

I get that a site like yours cannot solve all of that. You can only extract the info that's already there. And parsing such data for different categories of products is a major league hassle.

I once built a tool that did this for used cars. And it would allow you to plot all available listings that matched your filters in a price/milage scatter graph. To make the outliers really visible.

Can you share how you solved the parsing problem in your implementation? Is it just regexes, or are you employing NLP span categorization techniques?