Amazon's recommendation system generates about 35% of the company's revenue by analyzing what you browse and buy. The algorithm connects unrelated products, like shirts and kitchen items, to suggest things you didn't know you wanted.
They famously generated 35% of their revenue through their personalized recommendation system, showing products based on browsing history, purchase behavior, and even what similar customers have bought. What's your take on this? Bad bold or brilliant? I
think it's super smart in the sense of, you know, they're doing all different kinds of analysis at Amazon all the time, but, like, some of that where you're connecting completely disparate data points and then all of a sudden surfacing something that is actually related to people who buy these things, like maybe all these people that buy these shirts actually also buy this thing for their kitchen. And you would never really connect that normally, like, as a human. But when you're looking at the data patterns and you start to see this overlap, I think it really unlocks a lot of revenue potential that is, is really smart and really strategic. And for me, as a customer, like, I would much rather have you show me something that I want to buy versus showing me something that's like, categorically appropriate. It saves me time, it saves me searching. And the more you learn my behaviors and my. My shopping patterns, like, I'm happy to find new products even if they feel completely unrelated, unrelated to the last thing that I purchased from you. So I'm a fan of it.
