Scoring System

53 weighted criteria across 5 pillars determine your AEO Site Rank. Learn how effective weights, confidence, and page-fleet scoring combine into the final score.

Deterministic scoring engine

AEORank powers every AEO Content AI audit. Review the engine overview and methodology: Docs

Overview

Your AEO Site Rank (0 - 100) measures how well AI engines can discover, parse, and cite your website. The score is deterministic: every point traces to a specific check, and the same crawl state produces the same result.

The current model is not a single raw weighted average anymore. AEORank calculates a base criterion score, applies a topic-coherence gate when needed, then blends that base score with a page-fleet score based on the types and quality of sampled pages.

Scoring Flow

Each of the 53 criteria is scored 0 - 10 individually, but the final score is assembled in stages. Raw criterion weights are adjusted for heuristic confidence and overlap between closely related criteria, normalized inside each pillar, then aggregated into a base score.

formula

effective_weight = normalize_within_pillar(
  raw_weight * criterion_confidence * cluster_adjustment
)

base_score = sum(pillar_score * pillar_target_weight)
if topic_coherence < 6:
  base_score = min(base_score, 35 + topic_coherence * 5)

content_fleet = weighted_page_score(sampled_pages)
overall_score = blend(base_score, content_fleet, page_fleet_weight)
overall_confidence = blend(base_confidence, sample_representativeness)

Normalization and overlap control

Closely related criteria do not all get full raw weight at once. AEORank dampens overlap in three clusters: the question-answer system, freshness signals, and provenance/trust signals. The pillar targets still remain fixed at 45/25/16/9/5.

Site Aggregation

After the base score is calculated, AEORank scores the sampled page fleet. Page reviews are classified by helpful page type such as homepage, editorial, product, category, catalog, support, reference, and landing. The model then blends the base score with the weighted page-fleet score.

This is why audits now return split headline scores. Foundation emphasizes technical foundation, AI discovery, and trust infrastructure. Content Fleet reflects the sampled page mix and content quality. A site can have strong foundation but weak page templates, and the audit will show that gap explicitly.

Prevalence beats isolated examples

Several content criteria now score by coverage across eligible pages instead of presence anywhere on the site. That includes Q&A format, query-answer alignment, citation-ready writing, and evidence packaging.

Five Pillars

The 53 criteria fall into five pillars with fixed target weights. Answer Readiness is normalized to 45% of the final model, Content Structure to 25%, Trust & Authority to 16%, Technical Foundation to 9%, and AI Discovery to 5%.

Answer Readiness12 criteria

“Is your content worth citing?”

Normalized to 45% of the model. Determines whether AI engines have substantive, original, citation-ready material worth referencing, including first-hand evidence and duplicate-content resistance.

Content Structure10 criteria

“Can machines extract and cite your content?”

Normalized to 25% of the model. Covers answer density, Q&A patterns, FAQ, tables, definitions, and entity disambiguation.

Trust & Authority11 criteria

“Do AI engines trust your content?”

Normalized to 16% of the model. Covers entity authority, internal linking, freshness, visible dates, schema, authorship, and methodology trust signals.

Technical Foundation11 criteria

“Is the markup AI-friendly?”

Normalized to 9% of the model. Covers semantic HTML, clean crawlable markup, extraction friction, image context, and schema depth.

AI Discovery9 criteria

“Can AI crawlers find you?”

Normalized to 5% of the model. Covers cannibalization avoidance, llms.txt, robots.txt, publishing velocity, licensing, sitemaps, canonicals, and RSS feeds.

All 53 criteria

Every criterion has a fixed effective weight that determines how much it contributes to the base score. The table below shows the current effective weights after confidence weighting, overlap damping, and pillar normalization. Values are rounded for readability.

#	Criterion	Pillar	Weight
Answer Readiness - Is your content worth citing?
1	Topical Authority	Answer Readiness	7%
2	Original Research & Data	Answer Readiness	7%
3	Content Depth	Answer Readiness	6%
4	Fact & Data Density	Answer Readiness	5%
5	Citation-Ready Writing	Answer Readiness	3%
6	Answer-First Placement	Answer Readiness	2%
7	Evidence Packaging	Answer Readiness	2%
8	Helpful Purpose Alignment	Answer Readiness	2%
9	First-Hand Experience Signals	Answer Readiness	2%
10	Answer Capsule Pattern	Answer Readiness	2%
11	Duplicate Content Blocks	Answer Readiness	4%
12	Cross-Page Duplicate Content	Answer Readiness	3%
Content Structure - Can machines extract and cite your content?
13	Direct Answer Density	Content Structure	3%
14	Q&A Content Format	Content Structure	3%
15	Query-Answer Alignment	Content Structure	3%
16	FAQ Section	Content Structure	2%
17	Tables & Lists	Content Structure	3%
18	Definition Patterns	Content Structure	1%
19	Entity Disambiguation	Content Structure	2%
20	Entity Density	Content Structure	4%
21	Sentence Atomicity	Content Structure	2%
22	Titles & Meta Descriptions	Content Structure	2%
Trust & Authority - Do AI engines trust your content?
23	Entity & Brand Authority	Trust & Authority	3%
24	Internal Linking	Trust & Authority	2%
25	Content Freshness	Trust & Authority	2%
26	Schema Markup	Trust & Authority	1%
27	Author & Expert Schema	Trust & Authority	1%
28	Creator Transparency	Trust & Authority	1%
29	Methodology Transparency	Trust & Authority	1%
30	Owned Data Density	Trust & Authority	2%
31	Visible Date Signal	Trust & Authority	1%
32	AI Disclosure	Trust & Authority	1%
33	Citation Density	Trust & Authority	1%
Technical Foundation - Is the markup AI-friendly?
34	Semantic HTML	Technical Foundation	1%
35	Clean HTML	Technical Foundation	1%
36	Extraction Friction	Technical Foundation	1%
37	Image Context for AI	Technical Foundation	1%
38	Schema Coverage	Technical Foundation	0%
39	Speakable Schema	Technical Foundation	0%
40	Indexability	Technical Foundation	2%
41	Layout Stability	Technical Foundation	1%
42	Page Speed: Server Response	Technical Foundation	0%
43	Page Speed: Load Blockers	Technical Foundation	1%
44	Page Speed: Page Size	Technical Foundation	1%
AI Discovery - Can AI crawlers find you?
45	Content Cannibalization	AI Discovery	1%
46	llms.txt File	AI Discovery	0%
47	robots.txt for AI	AI Discovery	1%
48	Publishing Velocity	AI Discovery	1%
49	Content Licensing	AI Discovery	1%
50	Canonical URLs	AI Discovery	0%
51	Sitemap Completeness	AI Discovery	1%
52	RSS/Atom Feed	AI Discovery	0%
53	Multi-Language SEO	AI Discovery	0%

Effective weights are rounded

The engine normalizes pillar weights exactly, but the public table rounds criterion weights to whole percentages. That means the displayed total may land slightly above or below 100%.

Score Ranges

Your overall score maps to one of six tiers. These labels appear on audit reports and in the API response.

Range	Label	Meaning
86 - 100	Excellent	AI engines actively cite your content
71 - 85	Good	Solid foundation with room for improvement
56 - 70	Average	Missing key optimization opportunities
41 - 55	Below Average	Significant gaps in AI visibility
26 - 40	Poor	Major structural issues limiting visibility
0 - 25	Critical	Fundamental problems preventing AI discovery

HTTPS Factor

Criterion #4 (Clean, Crawlable HTML) includes HTTPS availability. Sites without HTTPS are capped at 3/10 on this criterion, resulting in an approximate 3 - 4 point overall penalty. The audit checks HTTPS first and falls back to HTTP for all subsequent checks.

No HTTPS = guaranteed penalty

Even if your HTML is perfectly clean, lacking HTTPS caps criterion #4 at 3/10. This is one of the easiest points to recover - install an SSL certificate and gain 3 - 4 points immediately.

Benchmark Comparison

Your score is compared against peers in your sector and category. The API returns sector averages, and the web dashboard shows “Above Average”, “Average”, or “Below Average” badges based on a +/- 5 point threshold from the sector mean.

For example, if the average score in “Developer Tools > Cloud Infrastructure” is 62, a score of 68 or higher earns “Above Average”, 57 or lower shows “Below Average”, and anything in between is “Average”.

View the full benchmark data across all sectors and categories at /benchmarks.