Crafting effective keywords to add to a book's metadata, could be one of the highest return marketing activities to increase online sales potential. This post examines why keywords are so important, and how they affect discovery on Amazon.
Let's break the logic down:
• Amazon is the biggest bookseller in the world.
• Around two thirds of online book sales are made through Amazon.
• Search is how most customers find products on Amazon.
• Keywords directly influence a book's visibility in Amazon's product search.
In Amazon's own words (link requires a seller central login):
Search is the primary way that customers use to locate products on Amazon. Customers search by entering keywords, which are matched against the search terms you enter for a product. Well-chosen search terms increase a product's visibility and sales. The number of views for a product detail page can increase significantly by adding just one additional search term—if it's a relevant and compelling term.
We differentiate between keywords derived from web page text (Google, Bing, etc.) and keywords added to a book's metadata for consumption by a book retailer (Amazon, Barnes & Noble). Web search engines crawl web pages to derive keywords and concepts, to help users find information. Book product search engines consume book metadata (which includes keywords), provided by the publisher or author, and help customers find books to purchase.
As Google's executive chairman, Eric Schmidt lamented:
People don’t think of Amazon as search, but if you are looking for something to buy, you are more often than not looking for it on Amazon.
Why can't the machines just figure it all out?
So why the difference between a web and a book (product) search engine? Why can't Amazon read a book's text to figure out what to index, just like Google crawls a web page? There are two core reasons for this:
1. Human classification beats machine classification, when done properly. People are better at describing books, in terms other people relate to, than machines. The technology exists to understand the topical content of a book (we know, we've built it), but for a product search engine, it's more effective for Amazon to put the burden of describing a book in keywords, onto the author or publisher. The author/publisher, in turn, has a strong incentive to increase their book's discoverability in search.
2. It's easier for Amazon to do. Pretend you're a technical superstar tasked with building a search engine for millions of books. What solution do you think would be easier to build? One where you had to index 5-20 human curated keywords that describe each book, or one where you had to index tens (or hundreds) of thousands of words per book to find out what it's about? Leveraging an incentivised crowd to manually add descriptive terms in a structured format, is a much smarter and technically simpler solution.
Isn't it a search engine, not a discovery engine?
It has been said that search is not discovery, but this perspective doesn't consider the complex task search engine's undertake to discern user intent (we've talked about the different user intents when searching before). Let's look at the distinction between book discovery and book search (within the context of a search engine), and how different elements of metadata support different user intents:
Searching for a specific book or title supports a customer who has 'discovered' a book through another channel, and is simply visiting a book retailer to purchase the book. In this case, the user intent is obvious, and the implementation is a basic, nuts and bolts 'search' engine. As a publisher or author, you really don't have much to do to optimize for this use case. Your book title and author (contributor) name is specified in the metadata. The engine performs a simple match for these fields to a customer's search query. This is why there is no need to include book title and author name in your keywords.
Book discovery, in the context of a 'search' engine supports many cases of different user intent, where a customer isn't searching for a specific book. The engine helps the customer discover books that satisfy their query. For example, customers might use a book search engine to discover:
• a new book to read in their favorite genre ('contemporary romance new releases')
• a book to learn about a trending topic ('books about the islamic state')
• a book to solve a problem ('back pain')
The metadata that directly influences book discovery on Amazon search are keywords.
Cases exist where subtitles and category names impact discovery, but keywords are designed for, and have a direct relation to book discovery. Other discovery mechanisms also exist, of course, such as bestseller lists and item-to-item similarity recommendations, but these are often outside of the control of an author/publisher.
Codifying how customers think about books
Amazon categories are influenced by the way customers naturally group books together, and how they express these categorizations when searching for books. Book categories are continually refined to adapt to shifts in customers' tastes and collective interests. Books are categorized by manually curated metadata (BISAC or Browse Node - Amazon's equivalent of a category), as well as by analyzing a book's keywords. Many categories need a book to be associated with certain keywords, in order for it to qualify for the category. Analyzing the Science, Fiction and Fantasy category requirements we'll see keywords such as: angels, demons, dragons, vampire, aliens, horror and magic. These are all broad, book discovery terms that are designed to satisfy users looking to find books by search terms other than title and author.
There is a clear link between how customers mentally label and group books, and how they express their intent when trying to find books. Amazon attempts to replicate this organization via it's search engine and associated categorical data. By using the language and terms customers actively use to search for books, it can more accurately answer book queries at scale.
The bulk of the complexity of a successful book search engine, lies not in basic title/author matching, but in deciphering a user's intent when broad terms are used for discovery. Helping a customer find and purchase a book when they're unsure of exactly what they're looking for, is big business.
After all, the 'search experience team' believe it's about "finding, not searching".
Do readers even discover new books through search?
Unless you have access to internal search query and purchase data from a major online retailer, it's not possible to make an absolute assertion one way or the other. So let's consider some visible signals:
The industry believes so
The BISG has created a working group dedicated purely to defining best practices for keywords in book metadata. These keywords (in almost all cases) are curated by a person, to be stored with the rest of the book's metadata, and used by retailers (such as Amazon and Barnes & Noble) to help consumers find books. These are not the keywords that web search engines, such as Google, extract from the content of book descriptions on product pages.
This working group has published a guide for publishers to use when defining keywords, which is available for download (via free registration). A summary, that doesn't require registration, is also available.
The group comprises members from all the publishing service provider heavyweights (Ingram, Bowker, etc.), all big five publishers (plus many others), Library of Congress, Barnes & Noble and also Amazon.
Most large publishers have also allocated in-house resources (of varying expertise) specifically to curating keywords for their books.
Amazon has invested heavily in Search and Sales Business Intelligence
Access to this data is only available to a small number of organizations that sell a lot online, through a product called Amazon Retail Analytics (ARA). It's goal is to help vendors optimize their product listings to sell more, largely through data optimization for search. Here's a screenshot.
ARA provides publishers with data on how often keywords are searched for (volume), click through rates and conversion rates. It has it's limits, but is far more information than most smaller publishers and independent authors have access to.
When considering the investment and focus the publishing industry has dedicated to keywords, which are created for the sole purpose of helping consumers find books - it's challenging to dismiss the vital role they perform in selling books online.
A sales panacea?
Will the perfect keywords alone magically whisk a book to the bestsellers list? No. The fundamentals need to be executed well, which results in a quality, professional product with market demand. Quality can't be faked over the long term, and short term hacks won't lead to sustainable ongoing sales.
Effective keywords increase a book's chance of being located by the right customer, and help augment success achieved through other marketing channels. While keywords can increase a book's exposure, whether a customer discovers a quality book or not, will ultimately be represented by unit sales and reviews.
We've analyzed how keywords work and why they're important - which is to help sell more books in the marketplace where most books are sold. The industry acknowledges the importance of this correlation, as evidenced by its focus and investment in keyword standardization and dedication of resources (at publisher and retailer level). Yet most authors and publishers don't create effective keywords for their books or update them very often. Compared to the effort and resources involved in publishing a title, a well-implemented keyword strategy can be one of the highest ROI marketing activities for a book. In many cases, this represents a strong, currently missed, opportunity for increased book discovery.