What Are “Also Boughts”? Can They Help You Sell More Books?

You may have heard authors and other publishing professionals talk about the Amazon algorithm and how it impacts their books. In this article, we break down what an algorithm is, how the Amazon algorithm works and how it impacts you as an author. Before we begin: Don’t be intimidated by the terms you see. Everyone can understand how this works. And, as an author who is aiming to sell more books on Amazon, it is important that you understand what’s going on behind the scenes.

The Personalization of Online Shopping

In today’s world of online shopping and e-commerce, a lot has changed in how retailers are able to sell products to their customers. In a physical store, every customer sees the same thing – the same displays, the same products on the shelves, the same signage. Because every customer sees the same thing, the owner of a physical store tries to appeal to the average customer. She tries to display the products that the majority of customers will like and she runs promotions that will appeal to the majority of customers. This is why when you walk into a Barnes & Noble, you will see displays packed with books by James Patterson and other best selling authors. James Patterson appeals to the majority of mystery readers so it’s a good bet for the bookseller whose goal is to sell as many books as possible.

Online stores give store owners the ability to personalize the experience for every single customer. Personalization means each customer sees different products, different promotions, and different displays. The largest online store in the United States is Amazon.com. Amazon has gotten very good at personalizing the shopping experience for every customer that visits the website.

• Traditional Retail = Everyone sees the same products
• Online Retail = Every user sees different products that are more relevant to them
• Amazon is very very very good at Online Retail

The Algorithm and Also Boughts

Let’s start with some definitions:

Data is information, plain and simple.

An Algorithm, in this case, is a computerized process that takes in information (data) and spits out conclusions based on patterns in that information.

Amazon has lots of data on its customers. It knows what they browse, what they buy, what they review, and what they return. Amazon makes money when you purchase more things from them, so their goal is to recommend products that you are most likely to purchase. They figure this out by taking all of the data they have on all of their customers and building an artificial intelligence that can determine what you are most likely to buy based on your past actions. Many people refer to this artificial intelligence as the “Amazon algorithm”. The part of the Amazon algorithm that has the greatest effect on buyers and sellers on Amazon is the part that leverages item-to-item collaborative filtering (people who buy x also buy y)

Data about people buying stuff + Pattern recognition written by smart people = Amazon Algorithm

Examples:

• People who buy baby formula also buy Diapers
• People who buy a bathing suit also buy suntan lotion
• People who bought Jurrasic Park by Michael Crighton also bought Ready Player One by Ernest Cline

You see this play out all over the Amazon website in the Also Bought items that appear on every product page on Amazon. The Amazon algorithm has determined these Also Boughts by looking at the data associated with each person and each purchase on Amazon. In doing so, the algorithm has noticed that a high percentage of time people who bought Baby Formula also bought Diapers. Someone who bought baby formula may also have bought a notepad but when the algorithm looked at the data in aggregate it determined that there was a high correlation between Baby Formula and Diapers but a low correlation between Baby Formula and notepads.

This logic holds true for all products on Amazon, including books!
According to Chris Fox, “it’s becoming conventional wisdom that smart authors want to see books very similar to their own in that area.” If you see similar titles to your own in your Also Boughts it means that the algorithm understands what your book is about and who is most likely to purchase it. Additionally, if books similar to yours are showing up in your Also Bought section, then there is a good chance that your book is showing up in these similar books’ Also Bought section. This is how Amazon is helping you get in front of new readers who are the most likely to buy your book.  The Also Bought listing is the place where Amazon is marketing and selling your book for you. It’s incredibly valuable placement because, at that moment, the shopper is considering buying a book in your genre, and although they first landed on a title that isn’t yours, there is a chance they will purchase your book in addition to (or instead of) that original title. Amazon also frequently sends emails to its customers with book recommendations based on these Also Bought listings.

Let’s look at an example:

In visiting the product page for Mark Dawson’s latest novel, Blackout, we can scroll down to the section titled “Customers who bought this item also bought” to see the Also Boughts for this book. Blackout is an action-packed thriller. The first page of Mark’s Also Boughts are other books by Mark Dawson. This tells us that fans of Mark Dawson are the most likely people to purchase another Mark Dawson book. It tells us Mark has an avid fan base that is likely purchasing all the books that he puts out. If we scroll over to see additional Also Boughts, we start to see books that are not authored by Mark. These books have similar looking covers to Blackout and are also action-based thrillers. We can see that Amazon understands what type of book Blackout is, and knows who is likely to purchase it: readers who like action thrillers.

 

Also Boughts and Your Book

So how do you make sure your book appears in the right Also Boughts and in Amazon’s marketing emails? Amazon can only recommend your book once the algorithm has enough data points to know who to recommend your book to. When your book is newly published, Amazon does not know very much about who is going to like it. Yes, you have input keywords and genres to give the algorithm a general idea, but the algorithm is waiting for sales and downloads to determine who your target reader is. Once the algorithm has determined a profile for your target reader, it will start including your book in the Also Boughts and recommendation emails. A mistake many authors make is that they get their first sales from friends and family. This is fine if you write science fiction and all the members of your friend and family pool are avid science fiction fans. But if they’re not, you are confusing the algorithm by giving it faulty information about who your target reader is.

Think about Friends and Family from the algorithm’s point of view:
Let’s say the Algorithm is watching your new book, which is classified as science fiction.

1. Then a sale comes in from your mom (who usually purchases mysteries)
2. A sale comes in from your dad (who usually purchases biographies)
3. A sale comes in from your aunt (who usually purchases romance)
4. and so on

The algorithm is going to have a hard time figuring out who the target readers are since there is no common purchase history or preference among the customers who account for your initial sales.

Now, let’s think about your target readers from the Algorithms Point of View:
They love the genre you write in and have purchased items on Amazon that indicate that. When your target reader discovers your book the algorithm sees this activity:

1. A purchase from Dave (who usually purchases space exploration sci-fi)
2. A purchase from Janet (who has purchased The Martian by Andy Weir, the movie adaptation, and a related t-shirt)
3. A purchase from Bob (who usually purchases mystery but listens to sci-fi audiobooks)
4. and so on

With enough data points, the algorithm will figure out that the common thread among these customers who liked your book, is that they like science fiction. Once it has this common thread, the algorithm can start recommending your book in the Also Bought section below relevant products that your fans (and people like them) have purchased in the past and are browsing in the present. You want to make sure your Also Boughts are tightly aligned with your specific genre so your book is targeted toward the right kind of reader.

To determine your current Also Boughts you can simply go to your book on Amazon in incognito mode in your browser and scroll down to take a look. There is a nifty tool out here called Yasiv that will visualize your Also Boughts for you. Check out David Gaughran’s post on how to use Yasiv, it’s a gem.

How to Optimize your Also Boughts

Now that we know what the algorithm is and how it works, how do you get your target readers to purchase your book so that you can feed the most relevant data points to the algorithm? Or how do you fix your Also Boughts if they are ugly. Here are the steps:

Step 1: Identify your sub-genre

To get Also Boughts to work for you, you want your book to be featured in the Also Boughts of books similar to yours. So the first step is to identify your genre so you can identify the other books and authors in your genre. Defining your genre broadly, as Mystery/Thriller or Romance, for example, is not good enough. You need to identify the specific sub-genre within your main genre.

For example:

• Culinary cozy mystery
• Psychological thriller
• Step-dad steamy romance

To get a sense of the sub-genress that are out there, go to the Amazon Best Seller charts and navigate into your genre and then navigate deeper into the sub-genres available. Here is an example of us navigating into the Psychological Thriller sub-genre:

Our click path was Mystery, Thriller & Suspense –> Suspense –> Psychological

It’s worth clicking on many of the genres and sub-genres so you can feel certain you have picked the best sub-genre for your book.

Step 2: Evaluate your Cover

Once you have identified your sub-genre, take a hard look your book cover and compare it to the book covers populating the bestseller list for your genre. You want your book cover to look like it belongs with those books if it was featured on the bestseller list with them. If your book cover looks markedly different, take the time to redesign it so it fits your sub-genre. You are facing an uphill battle if your cover does not fit your genre and the next steps will not work if your cover does not appeal to your target reader.

Step 3: Make a List of Books and Authors for your Also Boughts

Once you are comfortable that your book cover is appropriate, go back to the bestseller list and make a list of the authors and books that are most like yours. For this exercise don’t confine yourself to just the bestseller list. As you click on books like yours, also look at the books populating their Also Boughts and click on those, and so on. Eventually, you should have a list of 50+ books and/or authors where you’d like your book featured in the Also Boughts.

Step 4: Populate your Also Boughts with Books Like Yours

Now that you know what your specific sub-genre is and which books are like yours, it’s time give Amazon the data it needs to include your book in the appropriate Also Boughts. There are two effective ways to do this and we recommend both:

The first tactic is to use book promotion services to send hundreds of your target readers to purchase or download your book.
To get this right you will want to make sure that the promotional site that you’re using has narrow genre definitions (sweet romance is separated from steamy romance; mystery is separate from cozy mystery; science fiction is separate from fantasy). That will ensure that readers within your sub-genre are the ones feeding the algorithm. The lower your price when you run a promotion, the more readers will engage with your book, and the more data you will feed the algorithm. Offering your book for free upon release can be especially effective since it allows you to feed the algorithm hundreds to thousands of data points in 24 hours. Running a discounted promotion at 99c is effective, but not as effective as a free promotion since fewer readers will download your book. The benefit to running a book promotion is that it is quick and easy to set up and once it’s set up your work is done. Many of our customers use our book promotion services (Freebooksy, Bargain Booksy, Red Feather Romance, NewInBooks) to feed the algorithm. Reedsy’s directory of promotion services is also a great resource.

Book promotion services allow you to get in front of your target readers in a specific sub-genre, however, you cannot target a specific author or book with book promotion services. Which brings us to the second tactic.

The second tactic is to run Amazon Ads targeting the authors and books on the list you made in Step 3.
When running ads you will want to choose the Sponsored Products option as that allows you to target specific keywords, authors, and books. We recommend that you first set up an Automatic Targeting campaign at a low daily budget. Next, you will set up Manual Targeting campaigns for each of the books and authors you identified on your list. This means you will likely have more than 30 campaigns running if you choose to target everyone on your list. The benefit to Amazon Ads is that you can specifically target authors and books. Running Amazon Ads can be time-consuming as you have to monitor your ads on a daily basis and it can take time for you to see results as ads may take time to get impressions and clicks. But once those ads start rolling you are feeding the Algorithm on a daily basis.

Both these tactics will help you get your book in front of the right readers. When these readers browse and purchase your book they are feeding the algorithm useful, actionable information.

A Note on ARCs

Some authors cultivate a pool of beta readers and super fans by joining the conversation in Facebook groups, Goodreads groups and other reader forums where their target readers hang out. Once they’ve established a rapport they ask these readers to join their beta readers group or mailing list. It is important to remember that providing an ARC to your beta readers will not help your Also Boughts as the transaction is not happening on Amazon and Amazon, therefore, will not be able to link that reader and that reader’s data to your book. If you want your beta readers or mailing list readers to help cultivate your Also Boughts these readers must download or purchase the book on Amazon. An easy way to facilitate that is to run a free or discount day and tell your readers to go and purchase the book then. This will feed the algorithm valuable data points AND it will improve your Amazon sales rank.

Wrap Up

Whew. It’s a lot of information, I know!  Here’s the bite-size summary:

• Online stores like to recommend products to shoppers in order to get them to buy more things. In order to recommend the right kind of products to their shoppers, many online stores utilize an algorithm that analyzes the behavior of their customers and figures out what they are most likely to buy.
• On Amazon, this algorithm recommends products in a variety of places, most notably the Also Bought section on every product page. When you’re selling a product, in your case a book, on Amazon, there are things that you can do to give the algorithm useful information about your book, which will allow it to recommend it in the right places, to the right people.
• The more useful the information that you feed the algorithm, the more it will promote your book in the Also Boughts. Running book promotions and setting up Amazon ads are two effective ways to feed the algorithm a lot of information at once.
• As an author, you need to understand which sub-genre your book fits in to and it is your job to make sure your cover appropriately reflects that sub-genre. If your book or cover is mismatched to its sub-genre, the tactics outlined above will not work.
• Your ARC readers and super fans can only help feed the algorithm if the transaction occurs on Amazon.

 

Footnote on Amazon’s Patent

Back in 2001 Amazon was granted a patent on its collaborative recommendation service. The patent describes the recommendation service as “A recommendation service is a computer-implemented service that recommends items from a database of items. The recommendations are customized to particular users based on information known about the users. One common application for recommendation services involves recommending products to online customers. For example, online merchants commonly provide services for recommending products (books, compact discs, videos, etc.) to customers based on profiles that have been developed for such customers. Recommendation services are also common for recommending Web sites, articles, and other types of informational content to users. “