Choosing your seven KDP backend keywords is a decision that most authors make in five minutes under the pressure of the upload process — and then never revisit. This article gives you a systematic process for making that decision well, with time to think and research before you publish. For the full keyword context, see our complete guide to Amazon KDP keyword research.
The Selection Process Overview
Choosing your seven keywords is not a single decision — it is the end point of a process. That process has three phases:
- Research: Generate a pool of candidate keyword phrases through Amazon autocomplete, competitor analysis, and reader language research. Aim for at least 20–30 candidate phrases before you start selecting.
- Filter: Reduce your pool using three criteria — relevance, specificity, and competition — until you have around ten strong contenders.
- Select and balance: Choose seven from your ten contenders, ensuring your final set covers different aspects of your book’s searchability rather than seven variations of the same phrase.
The entire process should take 30–60 minutes for a new book. This is time well spent — keyword choices made in five minutes at the publishing interface tend to be generic, unconsidered, and significantly less effective than choices made through a deliberate research process.
Building Your Research Pool
Your research pool is the collection of candidate keyword phrases you will eventually filter down to seven. Build it through multiple research methods:
Amazon autocomplete (primary method): Type genre-relevant phrases into Amazon’s search bar and note every autocomplete suggestion that accurately describes your book. Work through variants — “cosy mystery,” “cosy mysteries,” “cozy mystery,” “cozy mysteries” — and note suggestions from each. See our dedicated guide on using Amazon autocomplete for keyword research for the full methodology.
Bestseller description analysis: Read the descriptions of the top 10 books in your specific subcategory. Note the specific language they use to describe their books — these phrases are genre conventions that readers recognise and search for.
Review mining: If comparable books have reviews, read the five-star reviews. Note how enthusiastic readers describe the book to others — “perfect for fans of…” “if you love… you’ll love this” — the language of enthusiastic recommendation is often the language of keyword-worthy search terms.
Keyword research tools: Tools like Publisher Rocket or KDP Rank Fuel by Vappingo can generate large pools of candidate keywords from your book details. KDP Rank Fuel generates 100 targeted keyword ideas in a single run, giving you a substantial research pool without manual autocomplete work.
Filter 1: Relevance
Remove every phrase from your pool that does not accurately describe your book. This sounds obvious, but authors frequently include keywords that are adjacent to their genre without being accurate to their specific book.
Test: if a reader searched for this phrase and found your book, would they be satisfied? If they searched “cosy mystery with cats” and your book has no cats, that keyword is misleading and will generate returns and negative reviews. Remove it.
Accuracy matters not just ethically but algorithmically. Amazon’s algorithm tracks the conversion rate and return rate of books that appear for specific keyword searches. A book that appears for a keyword phrase but fails to satisfy the readers who find it through that phrase will gradually lose ranking for that term — and the damage to your overall algorithmic standing can be significant.
Filter 2: Specificity
From your relevance-filtered pool, prioritise specific multi-word phrases over generic short ones. Apply this test to each candidate: how many books on Amazon could this phrase accurately describe?
- “Mystery” — millions of books. Remove.
- “Cosy mystery” — tens of thousands. Borderline — keep only if you have nothing more specific.
- “Cosy mystery English village” — hundreds. Strong candidate.
- “Amateur sleuth cosy mystery retired librarian village” — dozens. Excellent candidate.
The more specific the phrase, the more targeted the readers it attracts, the more realistic your ranking opportunity, and the higher your likely conversion rate from that phrase. Specificity is almost always better than breadth for a book without established sales history.
Filter 3: Competition
Search each candidate phrase on Amazon and look at the search results. How many books appear? What is the sales rank of the top-ranking books? Are those books established bestsellers with thousands of reviews?
A phrase where the top results are books with BSR (Best Seller Rank) numbers in the thousands and review counts in the hundreds is a competitive phrase that will be hard to rank for without established sales momentum. A phrase where the top results are books with BSR in the tens of thousands and review counts in the dozens is a phrase where a new book with good metadata can realistically compete.
You do not need to win every keyword — you need to rank meaningfully for some of them. A mix of phrases across competition levels is more sustainable than targeting only the most competitive phrases in your genre.
Balancing Your Final Seven
Once you have ten or so strong candidates, your final selection should balance coverage across different search intents:
- At least one highly specific long-tail phrase that accurately nails your exact niche
- At least one setting or period descriptor if that is relevant to your genre
- At least one character type or protagonist descriptor
- At least one mood or tone phrase
- At least one phrase that captures a secondary audience or variant search pattern
Seven phrases that are all slight variations of the same term (“cosy mystery,” “cozy mystery,” “cosy mysteries,” “cosy mystery novel”) provide far less coverage than seven phrases that approach your book’s searchability from different angles. Variety in the search intents you target is as important as the quality of individual phrases.
Choosing Keywords for Fiction
Fiction keyword selection should prioritise:
- Subgenre specificity first — the most precise description of your fiction subgenre
- Setting and period — where and when matters enormously in reader search behaviour
- Tropes (especially for romance) — readers actively search by trope; include your key tropes
- Protagonist type — amateur sleuth, ex-special forces, reluctant witch — character types drive significant search volume in genre fiction
- Mood — “heartwarming,” “dark,” “funny” — mood qualifiers attract readers whose expectation matches your book
For genre-specific guidance, see our dedicated articles on KDP keywords for fiction and KDP keywords for non-fiction.
Choosing Keywords for Non-Fiction
Non-fiction keyword selection should prioritise:
- Problem-based phrases — the specific problem your book solves, in reader language
- Methodology phrases — the approach or system you use, if readers search for it
- Audience identifiers — who specifically this is for (ADHD adults, first-time investors, freelance designers)
- Outcome phrases — what the reader achieves by reading your book
- Subject-specific terminology — the precise vocabulary of your niche that informed readers use
When to Revisit Your Choices
Your initial seven keywords are a starting hypothesis. Revisit them after three to six months based on the data available to you: your Amazon Advertising search term reports (if you are running ads) reveal which keyword phrases are actually generating impressions and conversions; changes in your category’s competitive landscape may open new keyword opportunities; reader reviews often reveal how actual readers describe your book, which can inform better keyword choices.
For the full update methodology, see our article on when to update your KDP keywords.
The research pool generation and filtering process above takes time when done manually. KDP Rank Fuel by Vappingo generates 100 targeted keyword ideas from your book details in a single input — giving you a substantial, research-backed pool to filter from rather than a blank page to fill under pressure at the publishing interface.
Before any keyword brings a reader to your book, your manuscript needs to be in its best possible condition. Manuscript proofreading for self-published authors from Vappingo ensures the content those readers find is error-free and worth the positive reviews that strengthen your keyword rankings over time.
