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Metadata Worksheet — Non-Fiction

Non-Fiction Example & 7-Step Optimisation Framework

Lesson 10 of 10 · 3 min · Updated 3 September 2026

Non-fiction fails differently from fiction. Fiction metadata usually fails by being vague; non-fiction metadata usually fails by promising an outcome any book in the category could promise.

Here is the same business and productivity title before and after.

Before and after

Before — poor metadata

Title
Getting Things Done Better
Subtitle
A Guide to Productivity
Categories
Business & Money › Business Culture › General; Self-Help › Personal Transformation
Keywords
productivity, getting things done, business, success, goals, motivation
Description
Are you tired of being unproductive? Do you want to get more done in less time? This book will teach you the secrets of highly productive people.

What is wrong

Generic title · vague promises anyone could make · broad, unrankable categories · overused single-word keywords

After — optimised metadata

Title
The 4-Hour Workweek Myth
Subtitle
Why Most Productivity Advice Fails and the 3-System Solution That Actually Works
Categories
Business & Money › Skills › Time Management; Business › Entrepreneurship
Keywords
time management system, productivity for entrepreneurs, deep work, focus techniques, small business efficiency
Description
The productivity industry sold you a lie. After analysing 200+ successful entrepreneurs, productivity consultant Marcus Chen discovered that 89% of popular productivity advice makes you less efficient. The solution: three interconnected systems designed for business owners, not corporate employees.

Why it works

Contrarian hook · a specific research claim · targeted categories · phrase-based keywords · a clear outcome promise

The 7-Step Optimisation Framework

Run this on your own book, in order. Each step feeds the next, and step 7 is assembly — do not start there.

Optimise your own metadata

  1. 1

    Audience Promise Analysis

    Who exactly is this for, and what do they type into a search box?

    • Your target reader, and their single biggest problem
    • The words they use to describe it — not the words you use
    • Competing books they have already bought
  2. 2

    Comparable Titles Research

    • Five to ten successful books in your category
    • For each: category rank, review count, price
    • Note specifically what works in their metadata
  3. 3

    Category Target Selection

    • Primary and secondary categories where the top 100 is realistically reachable
    • Check the current #100 book's review count — that is the bar you must clear
  4. 4

    Keyword Phrase Development

    • Two or three primary terms plus four or five long-tail phrases
    • Build them from Amazon autocomplete and competitor analysis
    • Validate every phrase before committing to it
  5. 5

    Blurb Hook Development

    • Fiction: protagonist → inciting incident → conflict → stakes
    • Non-fiction: contrarian claim → credibility → problem → solution → outcomes
  6. 6

    Title and Subtitle Optimisation

    • Test three to five title options
    • The subtitle must add keywords and clarify the benefit
    • Check for existing conflicts on Amazon before committing
  7. 7

    Final Metadata Assembly

    • Compile every element
    • Run it through the Priority Stack: cover → blurb → title → categories → keywords
    • Enter it on the platform, then schedule a 30-day review

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