So you've found the perfect keywords for a book, how do you know if they're effective? Off-page keywords aren't visible to potential customers, so assessing whether they'll work or not takes a completely different approach to assessing visible metadata (title, description, etc.) about a book. The purpose of a keyword is to help a search engine return a book to a customer in a set of search results, in response to a search query. If a keyword doesn't achieve this one task, then it is of no value to you. It doesn't matter how beautifully descriptive or categorically accurate a keyword is, if it doesn't help your book show up in search, then it is worthless. Public data, such as categories or subtitles are dual purpose - they can improve your book's search presence and also help to convince a searcher to buy your book.
With an understanding of an off-page keyword's purpose - how do measure it's effectiveness on Amazon search? Amazon doesn’t share much data in the way of search metrics and even the data in Amazon's Retail Analytics (ARA) is pretty limited. But it’s still possible to measure whether a book has poor or good search visibility by analyzing public data. The most rudimentary method is to type every keyword into search, and see if the book appears, or ranks, in the search results. If it doesn’t show up in the results, then it has no visibility for that search query and it's effectiveness is nil. It’s pretty simple.
If a book does show up for the keyword, where does it rank? By rank, we mean the position it holds in the search results. Is it number one? Number 5? Does it show up on the first page, second page? Search rank can have a huge impact on conversion. Customers are significantly more likely to click on the first few results of a search query, than further down the page. Techniques such as Discount Cumulative Gain to measure search quality are predicated on this assumption.
Beyond simple one-to-one keyword to search query testing, to get a true appreciation of a keyword’s impact, you also need to test for derived keyword combinations. As an example take these three key phrases: “ya romance”, “contemporary romance” and “thriller”. These keywords will also match to the search queries: “ya contemporary romance”, “romance thriller”, “contemporary romance thriller” and so forth. Books are also matched against search queries that only partially match keywords. Using the same example, the book might also match “romance suspense” and “ya paranormal romance” even if “suspense” and “paranormal” weren’t specified as keywords for the book. To truly figure out how well a book ranks in search, requires figuring out all of these combinations, then running searches for each of them.
Once you find a match for your book, you then need to calculate how valuable the search query is, as they’re not all equal. Ranking in the top 5 for “romance” will generate more traffic for a book than ranking in the top 5 for “cozy beach romance set in florida”. The latter search query is more specific and while it receives lower search volume, it may have higher conversion potential. Long-tail searches are more granular, specific and easier to rank for, and are likely to generate better leads. Publishers almost never include them.
On Amazon, the majority of customer searches are long-tail - in fact a large percentage of searches have only been seen a couple of times or less. A significant percentage of these search queries on Amazon each month, have never been previously observed.
With the knowledge above, it's quite easy, albeit time consuming, to measure the effectiveness of a keyword for a book on Amazon (or any other search engine for that matter).