To What Extent Should Publishers Update Their Keywords?

Choosing the right keywords and phrases helps maximise both generative (GEO) and search engine optimisation (SEO)

By Ella Clapton

For years, trade publishers have understood the role metadata plays in discoverability, and we’ll return to the question of quality shortly. But its impact extends far beyond Google rankings or visibility within algorithmic and AI-driven search.

Metadata plays a critical role in helping retailers such as Amazon and Bookshop.org correctly list, categorise, and recommend books. Their discovery and recommendation engines depend on accurate, well-structured data to bring titles to the forefront in the correct context.

Ultimately, success depends on how readers search and describe what they are looking for and how effectively their request matches relevant publisher metadata producing relevant search results, leads to our websites, retailers and marketing channels.

In this article, we unpack ‘Long tail phrases vs. Short tail keywords’, how to find the phrases your readers will be searching with, and how it fits into the wider metadata discoverability discussions each publisher has every year.

Long Tail Keywords are Essential for Conversion

Long tail searches are now more focused on finding an informational response. Phrases provide relevance and are necessary to enable readers to find the books that they’re looking for and that will genuinely interest them, thereby increasing sales conversions.

Long tail phrases are usually something like: “List me the best cosy crime novels with older female detectives”

Or, the popular choice at the moment, is searching using comparisons: “I love authors such as Ian Rankin and John Conolly find me stories/authors that are similar”

Amazon and Google are starting to use long phrases to pick up reader intent and produce more relevance in their responses.

So, where does this leave us in choosing the best keywords/phrases for maximum discoverability? Does this tip the balance towards long tail keywords vs short tail keywords?

Well, not exactly…

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Short Tail Phrases Help with Ranking and Confirmation

Short tail keywords remain essential. Remember Algorithms use short tail key words for classification, AI platforms use them as anchors and retailers will use them to help with categorisation — Historical Fiction, W11 Memoir & Romantic Fantasy, for example.

If you focus only on long tail search you risk poor categorisation and weak retailer placement. If you only focus on short tail keywords your conversion rates will be significantly reduced. A balance needs to be struck between long tail phrases that drive initial discoverability — how do readers find you versus how your books are ranked and classified.

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Fast Fixes, Quick Wins

Book publishers have very limited time and resources to spend a huge amount of time on this. One way to approach this would be to start with your short tail keywords and BISAC codes. For example — Historical Fiction.

Then come up with a few long tail expansions. Rule of thumb: choose a phrase that readers would likely use to search if they know the topic but not the title.

‘Historical novel about women in wartime France’

Add your keywords to your ONIX, focusing on:

Title and Subtitle — try and add in a phrase into this section if space allows it.

Main Book Description — try and add in 3 keyword phrases per 100 words — without making it forced.

Categories — when you add your primary BISAC/THEMA codes make sure you add a sub category for enhanced discoverability.

We have listed below 3 simple tips to help work out searchable phrases:

Auto Complete — start to type into search bars in Amazon, for example, or other retailer platforms and see what comes up with the auto complete function. This is an effective way to see what readers are searching for.
Reader Communities and Forums — Choose best selling books and check how readers describe them in the various recommendation forums, for example: Goodreads groups, Book clubs, Facebook communities. The language used is indicative of what they are looking for. These are usually phrases you won’t find under standard genre categorisation.
ChatGPT to help speed up the process — ChatGPT can help find relevant phrases to add to my metadata. Simply upload a short synopsis or some of your ONIX and ask it to help you. Like: “What would a reader type into Google or Amazon if they wanted this book?” Or, “Give me 20 long-tail search phrases a reader might use to find this novel.”

What Academic & University Presses Need to Know

This is broadly the same as for trade publishing. Layered metadata is required so that all bases are covered. Ensure the traditional vocabulary — keywords — as well as up to date BISAC codes are added to your ONIX. The library supply chains, retailers and wholesaler classification are dependent upon short tail keywords. When it comes to semantic discoverability in AI, Google and institutional search — long tail phrases will be needed too. Most presses don’t focus on BOTH aspects which are extremely necessary to be successful.

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USEFUL TIPS

In your ONIX under “subject” Best practice for short tail keywords usually recommends 3 primary subject codes (BISAC) — making sure the first code is the most specific. French Architecture not Architecture for example. Ideally add up to 5 codes to your primary format. Books are often about more than one topic so breadth here is important. However, be honest and don’t add in topics that are briefly referenced in the book as readers will be disappointed to find half a chapter on the one topic they were researching!! If you are stuck, ask yourself where would a librarian expect to find this book?
Long-tail keywords are most effective when they are added to the “keywords” field in your ONIX. Here you can add nuance which will be picked up by Google, AI (generative engines) and other institutional search platforms improving discoverability. An example here of adding nuance would be ‘civilian political influence on British military strategy during World War II’ rather than ‘war, Britain, politics, WWII’. It would also be advisable to add long tail phrases into the main description “TextContent”. Libraries, retailers, search engines and AI algorithms scour the description too. For academic titles, you might consider phrases that reference ‘research, methodology and/or scholarly contribution’. Even chapter headings make excellent long tail phrases. Chat GPT, as mentioned above, can help not only produce long tail phrases by reviewing the ONIX, it can also help pick out phrases most frequently searched for by readers but also review your ONIX to look to filter out duplication and remove copy that is too heavily focussed on marketing.

So, ultimately…

Publishers now need to think in terms of:

a) Book content and how this relates to structural metadata - keywords, BISAC, format.

b) Reader search; intent, questions they might ask (using the tips above).

c) Use AI to help them take turn the content into suitable questions to reflect reader intent.

d) Look at bestseller’s metadata in their product detail pages on their publisher website and other reader platforms. Although it isn’t always the same as ONIX metadata it is usually very similar.

There is no single formula for weaving in long tail phrases but weaving them in is the right approach.

Sources

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