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sinai.com
WINTER 2020

sinai.com

Moderate AI visibility with 26 of 48 criteria passing. Biggest gap: llms.txt file.

51/100
F
Citation Avg
Coherence gate active - score capped at 60
Answer Readiness
~40% weight
6/10
Content Structure
~25% weight
5/10
Trust & Authority
~15% weight
6/10
Technical Foundation
~10% weight
5/10
AI Discovery
~10% weight
5/10

Verdict

Below-average AEO readiness at 51/100 - multiple areas need attention. Key strengths include Canonical URL Strategy, Schema Coverage & Depth, and Internationalization Signals. Priority gaps: llms.txt File, RSS/Atom Feed, and Speakable Schema. Topic coherence is moderate at 5/10, capping the score at 60. Tighter topical focus would lift this ceiling.

#4846of 13363
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How to Improve

Current
51/100
Projected
81/100
40Total Fixes
10Quick Wins
~82hEst. Effort
Quick Wins
Create /llms.txt fileConfigure robots.txt for AI crawlersImplement semantic HTML5 elementsAdd structured tables and listsAdd ai.txt and content licensingImprove query-answer alignmentAdd visible date signalsFocus blog content on core expertiseMake content creators clearly visibleImprove citation-ready writing quality
Create /llms.txt file
critical|low
Add llms-full.txt with extended content
medium|low
Configure robots.txt for AI crawlers
high|trivial
Fix HTML structure and meta tags
low|low
Create complete sitemap.xml
medium|low
Reduce render-blocking resources
medium|low
Improve server response efficiency
low|low
Reduce document weight
low|low

Top Opportunities10

Ensure blog content consistently covers your core expertise areas rather than scattering across unrelated topics. AI engines build authority models - a site about "Medicare coverage" that also publishes about humidifiers and groceries dilutes its topical authority.

Sections within pages contain identical or near-identical text. LLMs may flag this as low-quality or thin content, reducing citation authority. Rewrite duplicate blocks with unique angles.

Include "our analysis", "our data", "our testing" phrases backed by original research or proprietary data. 52.2% of AI-cited posts contain owned data signals.

Create a dedicated FAQ page with FAQPage schema markup. Cover common questions about your products, services, and industry to become a direct answer source for AI engines.

The same paragraphs appear on multiple pages. AI engines may only index one version and ignore the rest. Rewrite shared content so each page offers a unique perspective.

Write concise, standalone answer paragraphs (2-3 sentences) immediately after question headings. These "snippet-ready" paragraphs are ideal for AI engine citations.

Use HTML tables for comparison data and ordered/unordered lists for features, steps, and specifications. Structured data formats are directly extractable by AI engines for answers.

Ensure every question-format heading (H2/H3) is followed by a direct answer paragraph. This pattern is ideal for AI engine snippet extraction.

Write self-contained definition sentences and single-claim statements that AI engines can quote directly. Avoid pronouns like "this" or "that" at the start of answer paragraphs.

Define the primary entity in the first 500 characters, use consistent terminology (same term 70%+), and add "unlike X" signals to help AI engines distinguish your topics.

Fix It With AI44

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Site Pages

www.sinai.com/post/marginal-cost-of-abatement-understandi...F35
SINAI | Marginal Abatement Cost Curve - Basics
www.sinai.com/post/how-to-address-scope-3-emissions-in-th...F35
SINAI | Scope 3 in Mining: how to cut value chain emissions
www.sinai.com/success-stories/our-customersF35
Our Customers | Helping Organizations Decarbonize
www.sinai.com/solutions/brazil-cvmF34
Brazil CVM Compliance | ESG Reporting Software & Sustainability Platform
www.sinai.com/pt/industries/industry-food-beverage-agricu...D41
SINAI | Plataforma de Descarbonização e Sustentabilidade Empresarial
www.sinai.com/solutions/supply-chainF39
Scope 3 Emissions Software | Supply Chain Decarbonization Platform

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