AEO
Answer Engine Readiness Scorecard
AI-driven search doesn't reward design — it rewards structure. Score your site against the Answer Engine Readiness Scorecard and find out exactly where you stand.
dimensions
framework
criteria
The rules of search visibility just changed
Answer engines don't surface your best-looking page. They surface your most machine-readable one. For enterprise teams, that gap creates real business risk.
Sections get extracted out of context
AI search doesn't always use a full page as written. It may pull a single section or short passage — and vague structure gets misread or misattributed.
Structural drift spreads across thousands of pages
As teams update templates and publish new content, heading levels get skipped, landmarks disappear, and consistency breaks down silently at scale.
One-off copy rewrites don't fix the real problem
Answer engine readiness is a template and governance issue — not a content issue. The fix has to happen at the structural level to stick.
Your totals
Score each criterion 0–2 · 0 = missing/broken · 1 = present but inconsistent · 2 = strong and consistent
Multiply score by the Weight · Total ÷ 2 = Score out of 100
Machine-Readable Structure
| Criterion | What good looks like | Wt | Score |
|---|---|---|---|
| Single, descriptive H1 | One clear H1 that matches page intent; no duplicates | 4 | |
| Logical heading hierarchy | H2/H3 used in order; no skipping levels; headings summarize sections | 6 | |
| Semantic landmarks | Proper use of header/nav/main/aside/footer or ARIA landmarks | 5 | |
| Structured lists and steps | Procedures are real <ol>/<ul> (not styled paragraphs) | 5 | |
| Real tables | Data uses <table> and headers (<th>) where appropriate | 4 | |
| Definition block pattern | A short definition/answer near top, marked by a heading and paragraph/list | 6 |
Why it matters: Answer engines often extract content in sections rather than as whole pages. A clear hierarchy makes it easier to interpret section boundaries — weak structure increases the risk of misreading or misattribution.
| Section total | Total section score based on the above criteria | Section score |
Extractability and Page Anatomy
| Criterion | What good looks like | Wt | Score |
|---|---|---|---|
| Answer-first summary | 40–80 word direct answer (TL;DR) appears at the top | 6 | |
| Clear section intent | Each section answers a sub-question (FAQ-like, but not junk) | 4 | |
| Scannable formatting | Short paragraphs; meaningful subheads; bullets for attributes/benefits | 4 | |
| Stable content zone | Main content isn't buried under carousels/accordions; minimal layout noise | 3 | |
| Consistent template anatomy | Same page type (product, policy, help) uses same structure sitewide | 3 |
Why it matters: Answer engines work better with pages that surface key information early and present it in clean, predictable content regions. Noisy or inconsistent layouts make reliable parsing harder at scale.
| Section total | Total section score based on the above criteria | Section score |
Entity and Relationship Clarity
| Criterion | What good looks like | Wt | Score |
|---|---|---|---|
| Entity-first naming | People/organization/product names are explicit (not we/it/this) | 5 | |
| Disambiguation | Acronyms expanded; regions/versions specified (e.g., WCAG 2.2, EU, 2026) | 4 | |
| Relationship signaling | Use X vs. Y, requirements, steps, components, and limits explicitly | 3 | |
| Unique page focus | Page has one primary job, not a wide variety of loosely related topics | 3 |
Why it matters: Answer engines are more likely to select and summarize content accurately when the main entities, terms, and relationships are explicit. Ambiguity around names, versions, or scope increases the chance of weak or incorrect retrieval.
| Section total | Total section score based on the above criteria | Section score |
Structured Data and Supported Markup
| Criterion | What good looks like | Wt | Score |
|---|---|---|---|
| Relevant schema present | Appropriate schema for page type: Organization, Article, FAQPage (when valid), Product, HowTo, etc. | 6 | |
| Schema validity | Valid JSON-LD; matches visible content; no spam markup | 4 | |
| Authorship and dates | Clear datePublished, dateModified, and author where appropriate | 3 | |
| Canonical entity pages | Strong about pages for brand/products to anchor entity understanding | 2 |
Why it matters: Structured data can help clarify page type and key attributes in a machine-readable format — treat it as supporting markup, not a primary lever. Use valid, relevant schema that aligns with visible content.
| Section total | Total section score based on the above criteria | Section score |
Trust, Citability, and Governance
| Criterion | What good looks like | Wt | Score |
|---|---|---|---|
| Claim support | Statistics/claims have a nearby source link or reference | 5 | |
| Freshness signals | Last updated reflects real maintenance; outdated content is reduced/redirected | 4 | |
| Author/reviewer clarity | Named owner; credentials where relevant (regulated industries especially) | 4 | |
| Internal citation hygiene | Key pages link to the definitive source page (no orphan near-duplicates) | 4 | |
| Indexability basics | Not blocked by robots/noindex; correct canonicals; clean URL | 3 |
Why it matters: Content is more usable as an answer source when claims are supported, ownership is clear, and maintenance signals are trustworthy. These cues don’t guarantee visibility. But they do make content easier to verify, attribute, and align with current information.
| Section total | Total section score based on the above criteria | Section score |
Overall score
| Final score | Total score across all sections | Overall score |
What your score means
85–100
Answer-Engine Ready
Strong structural clarity and low ambiguity. Focus on maintaining consistency across templates.
70–84
Competitive but Inconsistent
Generally usable, but structural gaps increase the risk of weak or inconsistent retrieval.
50–69
Discoverable but Not Reliable
May be crawlable, but weaknesses in structure and governance make it a poor answer source.
< 50
High Readiness Risk
The page may still rank, but it won't be interpreted or reused reliably in AI-driven search.
85–100
Scale and defend
Diagnostic: Readiness is strong. The risk at this tier isn't current quality—it's future drift and competitive displacement. Templates are good now, but sites evolve, teams turn over, and answer engine behavior shifts.
General guidance: Institutionalize the standard. Document what “readiness” looks like for each template type, build it into content workflows as a baseline expectation, and shift monitoring attention toward competitive share of voice rather than internal quality scores.
Siteimprove angle: This is where the platform's value is less about catching problems and more about maintaining position—tracking mention rate and citation rate across answer engines, watching for structural drift before it affects performance, and giving content teams a shared readiness dashboard that keeps the standard visible without requiring manual audits.
70–84
Governance and consistency
Diagnostic: The content is generally usable. The structural quality is there, but it isn't reliable across the full site. Individual pages score well; the template or team behavior doesn't hold at scale. This is a maintenance problem, not a design problem.
General guidance: Focus shifts from building to protecting. The work here is preventing drift—making sure that good structure doesn't erode as teams publish, update, and hand off content. That means clear template documentation, publishing workflow checks, and defined ownership for high-value page types.
Siteimprove angle: AEO visibility monitoring becomes the right tool at this tier. Teams should be tracking whether their well-structured pages are actually being cited and surfaced in answer engines—and using that signal to identify which remaining gaps matter most. The question shifts from “Are we structurally sound?” to “Are we being selected as an answer source, and where are we still losing to competitors?”
50–69
Systematic remediation
Diagnostic: The building blocks are there but inconsistently applied. Some pages do it right; others don't. The structural intent exists but hasn't been enforced. This is the most common enterprise bucket.
General guidance: You don't need to redesign—you need to standardize. Identify which criteria are consistently scored 1, meaning present but weak, versus 0, meaning missing, and treat each one as a template-level fix rather than a page-level fix. Prioritize heading structure and answer-first summaries first; they have the highest impact-to-effort ratio.
Siteimprove angle: This is a content governance and monitoring problem. Teams need visibility into which page types are drifting and which criteria are failing at scale—not a spreadsheet audit they do once. Siteimprove can surface structural inconsistencies across templates continuously, so remediation becomes a managed backlog rather than a one-time sprint.
Below 50
Structural rebuild
Diagnostic: The problem is foundational. Structure is either absent or inconsistent at the template level, which means no amount of content editing will fix it. You're building on a bad scaffold.
General guidance: Stop optimizing individual pages and go upstream. Audit your shared templates first—heading hierarchy, semantic landmarks, and content zone definition. Until the template is right, every page it generates inherits the same problems.
Siteimprove angle: This is where accessibility and SEO auditing overlap directly. The same structural issues that score poorly on the readiness scorecard—skipped heading levels, missing landmarks, and styled paragraphs masquerading as lists—are also flagged in accessibility checks. Teams in this bucket can use Siteimprove's technical auditing to get a site-wide inventory of structural failures before they begin remediation work, so they're fixing patterns rather than individual pages.
5 Fast Wins to Improve Readiness Today
- 1 Enforce one H1 and clean H2/H3 on templates — the single highest structural ROI change you can make.
- 2 Add a 40–80 word definition/answer block at the top of every high-intent page.
-
3
Convert faux formatting into real semantics: proper
<ol>,<ul>, and<table>elements. -
4
Make sure
dateModifiedreflects actual content edits — not superficial page touches. - 5 Validate schema markup matches visible content and remove any junk FAQ markup.