At least customers get paid for giving them that information (in the form of the discount that the price-matcher gives). I've done it, too, at Fry's when I needed some hard disks and a laptop on short notice. Saved about $100 in one trip (they were expensive hard disks), just by pulling up Amazon and pointing at the price for the service rep.

Competition is good.

I can't believe so few people know about this. Fry's and Best Buy both price match reputable online retailers ("Sold by Amazon" or whatever they say when Amazon is the retailer and distributor) and I just get all of my hardware like that. For the cost of gas, I get it instantly and can instantly return DOAs instead of waiting for RMA or Amazon returns. In the case of lower cost products like USB cables, which have been the target of counterfeiters and fraud on Amazon, it prevents damage to other devices because the physical retailers are generally more careful about sourcing.

Even if the store didn't price match, you can get the price match from using a credit card that has a good price protection (like Discover) and submitting a claim (very easy in my experience).

Not really. He bought the product from someone else. If Amazon didn't need the money and just wanted the analytics, it would have undercut the physical store. The value of the analytics would be in the sale to another company to market to this person, but they fulfilled their need for the product when Amazon acquired the information. So it didn't benefit Amazon and by the time they could have sold it to a third-party, it was useless.

Simply by looking at a product will build a user profile. It's not about making this sale, but maybe about the next 100 sales.

Sure, but money isn't quantum physics. If he doesn't spend any money on Amazon or any other online retailer, how are they monetizing his time on the site?

They see he likes products x y and z. Another 20 customers like products x and y, so nudge them towards buying product z

No, what they see is that he looked at x, y and z and didn't buy anything. Why would it nudge the next guy towards z? "Other people who did not convert also did not convert after seeing THIS!"?

Ok so my example was obviously too simplified

Users a b and c all at some point search for information on products x y and z. Many users, many products.

User d comes along and has previously looked at product z and is now searching for product y. It's now worth putting product x in the "you may also be interested in" segment. It might land a sale, it might not. That data can then be added to the pool to decide if they should show product x to people who search similar products

Why bother at all if they didn't purchase? You don't know why they didn't purchase. Maybe they were shopping around, maybe they were price matching, maybe they just don't have the cash right now.

It's machine learning, not if statements.

Adding a bunch of non-converting user behavior to your machine learning model won't help you or anyone else make a single sale. Best Buy got the sale. They got all the meaningful analytics along with it.

All you got from this person is that they looked at two products. Maybe those two products are related, but maybe they aren't. Adding this to your model is just adding noise to the "people who liked this also liked" references, and Amazon surely already has better qualified data for that (i.e. actual conversions).

They're already pretty good at determining that without scanning items in a store.