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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).




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