How Amazon Uses AI to Help Build Their E-Commerce Empire and How You Can Apply That To Your E-Commerce Business
AI (artificial intelligence) is a branch of computer science that is dedicated to making mathematical models that can simulate intelligence.
For example, the Bellman equation is a simple yet powerful equation that allows for reinforcement learning to occur in machines.
There are many other methods of simulating intelligence such as supervised learning, unsupervised learning, genetic algorithms, etc. The point is that there are many ways for a machine to learn and Amazon has taken full advantage of this technology to amplify their e-commerce business.
In this short article, I will go over the ways Amazon uses AI in their e-commerce business and also give you the reasoning behind why they used AI in that particular way. Below is also a video I made on this exact topic.
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Application #1: Figuring Out Trends in the Marketplace
Imagine having the amount of products Amazon has in your store. First of all, you’d need a lot of Walmart supercenters to hold all of those products. Second of all, how do you know which products are trending for a certain user group so you can start to place them correctly in your store?
That’s where AI can start to come into handy.
Imagine sitting in front of the door of your gigantic Walmart supercenter. Whenever someone walks in, you ask them a whole bunch of questions to get to know who they are and you have cameras setup all over the store to monitor which products a particular person is looking at and what they’re interested in.
You’re gathering a lot of data about users and what kind of products they like to shop for.
You then use this data to figure out if a new person walks into your store and starts to look at tennis rackets, then they’re most likely to want tennis balls, tennis shoes, maybe some Federer hats. You’re starting to understand the trends that are occuring for each and every consumer that walks into the store.
Now imagine that each and every potential customer that walks into your Walmart supercenter gets to see their own version of your store. Now whenever a person who previously has expressed interest in tennis items, you can start to move all of the related tennis items to the front of the store so it’s easy for them to get what they want.
This is essentially what Amazon is doing on a massive scale. They are recording each and every search query you make. They know where you’re from. Additionally, if you’re a Prime member, they can potentially even look into what movies and shows you watch and see if there’s some correlation in what content you consume and which products you like.
Their AI algorithms learn what type of person you are and then categorize you into a certain group and show you more of the products that other people in the same category have bought.
In technical terms, they are using clustering and classification algorithms to understand which groups are present on their website and then classify you into a particular group.
This plays into consistency bias. If you are looking for tennis items and someone comes up to you and tries to sell you pizza, unless you got super hungry while shopping, you’re not going to want that pizza because it’s not consistent with what you are looking for.
So now how do you apply this to your own e-commerce business? Well, you can start off with simple A/B tests to figure out which products do better with the visitors you are gaining on your website. This will help you understand your target audience better and you can also start to give them more of what they want.
Application #2: Upselling
Upselling is a term in marketing that basically means that if someone has just bought a product from your business, you try to sell them another thing which is usually priced higher than the product that they just bought.
Again, imagine having as many products as Amazon in your store. When someone goes to the checkout line, how do you know which products to offer them based on what they are about to buy?
This is where AI can help you understand what products are similar to the one that a customer is about to buy.
It’s the equivalent of training all your checkout employees to know exactly which products a customer will be interested in if they are buying a particular product and then having your employees attempt to sell the customer on more related items.
With how many transactions occur on Amazon daily, they can get a lot of data on which products are related to the one you are about to buy and then try to present you with bundles.
By increasing the amount of upselling that occurs on their site, they can start to sell more products and this allows them to outbid the competition in advertising as well.
Upselling relies on two very key psychological biases that Amazon is taking full advantage of. The first is reward bias. When you click that buy button, you get a spike of dopamine because you are about to get a new item in the mail which is going to solve a particular problem that you have. The second is commitment bias/sunk-cost bias. Humans will continue to do something just because they have already completed a portion of it. So if you’ve already spent some money, you’re likely to spend some more.
How can you apply this to your own e-commerce store? If you’re using Shopify, there’s a specific plugin by Beeketing that allows you to do almost the same thing as Amazon. It’s a recommendation engine that allows your website to learn if a particular product is about to be checked out, then they are most likely to also buy another related product and then display it right before they are about to checkout.
Application #3: Testing Copy
Certain words appeal more to certain people and make them action. How do you which words to use for a certain set of people? AI can help you crack this puzzle as well.
If you allow for Amazon to send you emails then you will start to see how this can become effective.
Which email subject line will grab your attention? Which particular text should they use to compel you to take action and click the buy button? Which layout of email should they use?
All of these questions can be answered with some experimenting by the AI algorithm. It will first classify the person it is about to send a test email to, then it will pick a certain version of the email to send, then send it. It will then observe and learn based on the results which subject lines capture attention, which specific text compels you to take action and which layout of the email it should use to most likely achieve the desired outcome.
It’s like you know what to say, to who to say it to, and when to say it.
They also use this tactic to send you notifications on your phone (if you have allowed for notifications on the Amazon app) at the time you are most likely going to click on it and shop based on your user profile.
So how can you apply this to your e-commerce business? Well, we all have text on our websites and we don’t necessarily know if that text is compelling visitors to take an action or actually just driving them away. This is where A/B testing can come into handy.
By using a platform like Optimizely, you can learn which text or layout does better to drive a certain action. However, Optimizely is somewhat expensive if you are just starting out and that’s why I’m creating a barebones version of what they offer and price it much cheaper. If you are interested in the beta, email me at firstname.lastname@example.org or click this link (coming soon).
Amazon has been absolutely crushing the e-commerce game which allowed them to propel their business to become evaluated at over $1,000,000,000,000, the second business to join the four-comma club.
As one of mentors says, would you rather learn basketball from the random stranger who’s at the park every weekend or Michael Jordan. Same thing.
Learn from Amazon and what they are doing and apply those same principles to your e-commerce business. You don’t have to reinvent the wheel.
If you have more questions about how you can use AI in your business, feel free to reach out to me. It’s @sunnychopper on pretty much every social media platform.