How Amazon Optimizes For Conversions: 8 Tricks You Never Knew!

Amazon's aggresive growth is the part I find the most interesting and probably also the most shocking 😱.

The story of Amazon’s product recommendations

Jeff Bezos woke up one morning in 2015, drank his coffee, and thought about how he could earn even more money 💡. The day before, he’d just been to a meeting with the shareholders of Wholefoods. He was considering buying them but wasn’t satisfied with that only. So instead, he wanted to make Amazon even more profitable 💪.

Amazon.com has always been an e-commerce site, and that has been its primary focus since its birth. Therefore, Jeff spent a lot of money on Google and invested a lot of effort into gaining and maintaining a high ranking of Amazon.

How could he satisfy his shareholders without increasing his marketing budget?

Hmmm...

💡 "How about I try to do something that makes my customers buy even more? I pay for them to visit Amazon anyway, so this might make it a bit more cost-effective.”

This is how the new era of Amazon began 🌟. He asked his developers to start working on a project that we now know as “Product Recommendations." But what are product recommendations, and how does Amazon use them?

Amazon has been using product recommendations since 2015. The recommendations were incorporated in every aspect of the Amazon platform. So much so that the only place you don’t see them is the search results and stores (where sellers with a trademarked brand get an entire page for their company to sell products).

Amazon has gone from no product recommendations to never missing an opportunity to show product recommendations. In this post, we’ll walk you through the 8 secret ways in which Amazon uses product recommendations to effectively boost sales and achieve tremendous business growth.

1. Recommended for you, xxx.

When you visit Amazon and log into your account, you can go to the header banner (beneath the search bar) and find "XXXX's Amazon." When you click on this, you’ll be able to see a page as displayed in the example below.  

Amazon recommends products that they think you’ll be most tempted to buy. Besides, this is also where Amazon "gets to know you." They collect data from the clicks you do on this page, to either confirm or deny whether their algorithm has “guessed” correctly in the first place. After clicking around and shopping on Amazon for years, I realize that this’s probably the part of the site where you should not go onto… Because you might not be able to afford it 😂!

2. Frequently bought together

This banner can be found on almost every product page. Amazon collects and analyzes enough data to tell you which products should be bought together. As you might have noticed, this dynamic banner is also optimized for UX (user experience). You can purchase two items in only one step by simply clicking on the button "add both to cart." More importantly, these product recommendations are smart and good 👍! As the example below shows, it makes perfect sense to buy a “Rumble Roller” together with a “Spiky Massage Ball."

As a cross-selling tactic, this is how Amazon succeeded in increasing AOV (average order value) through recommending and selling complementary products.

3. Recently viewed items and featured recommendations

This recommendation is based on the products that you’ve recently looked at. Below is an example of what Amazon recommends to me after I browsed around their site and viewed at several massage balls:

Although we don’t have full access to Amazon’s algorithms, we can still clearly see what these recommended products have in common: they belong to the same category, “sport & fitness equipment.” Doing so allows Amazon to suggest products that tend to the most relevant to your buying interests.

4. Your browsing history

Imagine this: after looking at various e-readers for days, a customer finally made up their mind and decided on which brand and model to buy. What will be the most effective way to help this customer find the product they’ve already looked at and now are interested in making a purchase?

Let them look at their browsing history 👀!

As it’s a daunting task to find something that you’ve viewed on Chrome or Safari because the browsing history is mostly page titles and URLs with NO pictures 😔. The example above exhibits Amazon’s solution in this situation.

5. Items related to those you’ve viewed

When you’re searching for a product but didn’t end up buying it or simply didn’t find the right one, Amazon will display similar, alternative items for you to choose from:

6. Hey! There’s a newer version of this item now.

Why bother buying an older version of a product? Especially in categories like electronics, almost everyone wants to buy the newest item, not the previous versions. For example, who would want to have a phone with only one camera when all the newly released phones have three or even more?!

The data can clearly tell the answer. For instance, if you look up monthly search volumes for a new item and then for an item that has already been for sale for over a year, you will usually find that search volumes for newly released products are 2-3x bigger than for products that are no longer the most recent. In line with this thinking 💡, Amazon presents you a newer version of Kindle as a recommendation when you’re looking at the product page of an older version:

This only strengthens the advantage of Amazon’s Choice by letting customers know - before they place a purchase - whether this is the newest version or not.

7. Items based on products you’ve purchased before

You just bought a new kindle? Great! Now you probably need a cover, so it doesn't break if you drop it. And Amazon has already thought of this for you 😉:

Like the previous trick of presenting complementary items simultaneously when a customer is shopping, another great cross-selling opportunity is to recommend them after purchasing. After using the Kindle for a while, you've probably realized that you would like to buy a cover to protect it.

8. Best-selling products in X-category

In the e-commerce universe, social proof works. While comparing products, consumers tend to choose the trendy, best-selling ones, as they trust other buyers' choices. For instance, you’re visiting a webshop. It's selling an item that has been going off shelves like crazy within the last 24 hours, and sales are 100x higher than the rest of the products in the same category. You’ll probably be more inclined to buy this product than the other product that has only been sold once within the last few days.

Amazon also knows about it, so they select and recommend the best-selling products in the category for you:

If you want to learn more about the benefits of using AI-powered personalized product recommendations, 👉 check out our new article on how to reduce bounce rates and increase AOV by optimizing the product pages of your e-commerce site.

The 8 tricks concerning product recommendations mentioned above are probably one of the most powerful lessons you can learn about Amazon's e-commerce success 🏆. So now, are you excited to try out these fantastic product recommendations?

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