Methodology

How we score your book

100 points across 5 categories. Same rubric for every book. No mystery — here's exactly what we look at and how we weight it.

Keyword Alignment

20 pts

Visual Competitiveness

20 pts

Keyword Alignment

20 points

Do the words readers actually type into Amazon and Google show up in your title, subtitle, and description — early and naturally?

What we look at

Title and subtitle phrasing
First 2–3 lines of the description
Whether terms are vague, clever, or buried

Scoring notes

0–7 weak
8–14 moderate
15–20 strong

Positioning Clarity

20 points

Within 5 seconds, is it obvious what the book is, who it's for, and why a reader should pick it over the next one in the carousel?

What we look at

Stated audience and use case
Differentiation from comparable titles
How the value is framed

Scoring notes

0–7 unclear
8–14 somewhat clear
15–20 clear & compelling

Conversion Strength

20 points

Once a reader lands on the page, does it convert? Broken into three sub-scores.

What we look at

Description Quality (0–8) — hook, value, skimmability
A+ Content (0–6) — present? Does it reinforce, not repeat?
Review Signal (0–6) — volume, rating, what reviews actually say

Scoring notes

We don't over-penalize new books with few reviews
No generic 'get more reviews' advice

AI Visibility

20 points

When ChatGPT, Claude, Gemini, and Amazon's AI search recommend books, does yours have a chance? Four 5-point sub-areas.

What we look at

Query Match Coverage — would it match natural questions?
Topic Labeling — is the topic plainly named?
Audience & Use Case Clarity — who, when, why
Structured Information — is it parseable, signal-rich?

Scoring notes

Includes an AI Recommendation Test: we simulate a real query and report Likely / Maybe / Unlikely with reasoning

Visual Competitiveness

20 points

How does your cover hold up at thumbnail size in a crowded carousel? Four 5-point sub-areas.

What we look at

Thumbnail readability
Category signal — does it look like its genre?
Standout factor in a row of competitors
Value communication at a glance

Scoring notes

If we can't see your cover clearly we score cautiously and say so

What data we look at

Only what's publicly visible on your Amazon listing — the same things any reader sees.

Title and subtitle
Book description and bullet points
A+ Content (if present)
Cover image
Review count, average rating, recent review themes
Category and published status

How we use AI (and what we don't use it for)

We do use AI to:

· Read your listing the way a reader would
· Apply the rubric above consistently to every book
· Simulate AI search queries against your listing
· Generate plain-language draft recommendations you can review and adapt

We don't:

· Train any model on your book or your data
· Sell, share, or resell your email or listing
· Promise ranking boosts or algorithm tricks — that isn't what this tool does
· Invent facts about your book; missing data is flagged

The rubric is the same for every book. AI is the reader — the scoring criteria are fixed and human-designed.

What we recommend you actually change

We only score books with a live Amazon listing. Once your book is published, Amazon locks the title and subtitle — they can't be edited.

So we focus our recommendations on the levers you can actually pull: description rewrites, backend keywords, A+ Content, category placement, and cover messaging tweaks.

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