There are lots of reasons why it makes sense for Amazon to recommend additional products for its users to purchase. It’s in their best interest to sell as many products as possible, obviously. That’s the most obvious reason.
Moreover, Amazon is sitting on an incredible database that includes not just what people actually buy, but what they browse and reject prior to checking out. This data set gives Amazon the power to make very specific recommendations that often align with what users are actually likely to buy (I can attest to this, having made far too many impulse purchases on the site).
But there is another reason, from a motivational design perspective, why Amazon’s strategy of recommending additional products is a smart way to keep users hooked on the site. These recommendations support relatedness. Self-determination theory posits that relatedness is one of three fundamental human needs that are precursors to motivation. Simply put, relatedness is the sense of connection to other people. Amazon’s recommendations support this sense in at least two ways:
The recommendations show that Amazon knows who you are and what you like. I’ve found Amazon’s product recommendations for me are generally pretty good. It’s not all rocket science. You don’t need to be a genius to realize that I order a lot of cleaning supplies and home goods (necessary evil since I don’t have a car to port these larger items home from a physical store). It’s also pretty easy to figure out what types of books I tend to buy (lots of murder mystery in the fiction realm, and lately, books about happiness and well-being in non-fiction). And I own cats but not dogs, so while kitty litter is a good bet, puppy chow is not.
This wouldn’t blow my mind so much if I’d gone on an Amazon shopping spree for my kitchen, but I didn’t. I’ve accumulated my red kitchen stuff over a decade from a variety of stores and from wedding gifts. I’m sure I’ve picked up a few items from Amazon, but that’s not the main source of my kitchen goods. And yet they know not to recommend a blue spatula to me.
The upshot of this is that when I see the products Amazon recommends for me, I have a sense that the company understands me as a person. They know what types of items will get me excited. Are they 100% right? Absolutely not, but they get a heck of a lot closer than any other retailer, and it helps motivate my continued purchases by creating a sense of a personal relationship with me.
The recommendations also show how you’re connected to other Amazon consumers. Amazon draws its recommendations from data that shows what other consumers who looked at and bought the same items you’re browsing eventually did. They’re able to extrapolate from the behavior of these other shoppers to make predictions about what you might do.
This screen shot is a fairly humorous example of how this works. I clicked on a link for a lobster costume, because, well, I saw a link for a lobster costume and I click on that sort of thing. Now Amazon has some interesting recommendations for other unique items I might want to browse based on other lobster costume aficionados’ tastes (please note, I did not purchase the lobster costume).
The “customers like you” functionality is a subtle way for Amazon to tell its consumers that they are not alone; that they are part of a group of like-minded others who also browse lobster costumes and yodeling plastic pickles. Human beings hate to feel isolated, and are drawn to these reminders that we’re connected to others.
How crafty is Amazon? It’s interesting to think about whether the folks at Amazon are deliberately using principles of motivational design to engage their users with relatedness. I suspect that, at least initially, their recommendations were more a straightforward attempt to expose users to appealing products. Deliberate or not, the way Amazon has implemented recommendations is particularly effective at creating a psychological sense of both being recognized as an individual, and being connected to other.
What other sites or companies do you think do a good job supporting their consumers’ relatedness?