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metaplane.dev
WINTER 2020

metaplane.dev

Moderate AI visibility with 23 of 48 criteria passing. Biggest gap: llms.txt file.

52/100
1 since v1
F
Citation Avg
Answer Readiness
~40% weight
7/10
Content Structure
~25% weight
5/10
Trust & Authority
~15% weight
3/10
Technical Foundation
~10% weight
5/10
AI Discovery
~10% weight
4/10

Verdict

Below-average AEO readiness at 52/100 - multiple areas need attention. Key strengths include Fact & Data Density, Canonical URL Strategy, and Cross-Page Duplicate Content. Priority gaps: llms.txt File, Schema.org Structured Data, and Comprehensive FAQ Section.

#4159of 13363
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How to Improve

Current
52/100
Projected
80/100
43Total Fixes
10Quick Wins
~91hEst. Effort
Quick Wins
Create /llms.txt fileAdd question-based headingsConfigure robots.txt for AI crawlersAdd structured tables and listsAdd ai.txt and content licensingImprove query-answer alignmentAdd visible date signalsImprove citation-ready writing qualityPackage evidence for AI enginesReduce extraction friction
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
Add internationalization signals
critical|medium
Reduce document weight
medium|low
Improve server response efficiency
medium|low
Reduce render-blocking resources
low|low

Top Opportunities10

Publish original research, statistics, case studies, or proprietary data that AI engines can cite. Unique data points make your content a primary source rather than a derivative one.

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.

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.

Add question-based headings (H2/H3) throughout your content. Use "What is...", "How does...", "Why should..." patterns that match how users query AI assistants.

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

Add Organization schema with consistent name, address, phone (NAP). Include sameAs links to social profiles and authoritative directories to strengthen entity recognition.

Include dateModified schema, visible last-updated dates, and time elements on content pages. Fresh content signals help AI engines prioritize your pages over stale alternatives.

Place a concise 40-80 word answer block in the first 300 words of each page. Avoid throat-clearing openers like "In this article..." and lead with the answer.

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.

Fix It With AI44

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Site Pages

www.metaplane.dev/blogD41
Data observability & data quality blog | Metaplane
www.metaplane.dev/customers/appcuesD42
How Appcues reduced data quality issues by 77% using Metaplane, Snowflake, and dbt | Metaplane
www.metaplane.dev/blog/great-expectations-and-metaplaneD44
Great Expectations and Metaplane | Metaplane
www.metaplane.dev/resourcesF37
Resource Library | Metaplane
www.metaplane.dev/blog/5-things-to-know-about-microsoft-f...D42
5 Things to Know About Microsoft Fabric | Metaplane
www.metaplane.dev/how-to-monitor/row-count-in-snowflakeF37
How to Monitor Table Row Count in Snowflake
www.metaplane.dev/how-to-monitor/uniqueness-in-sqlserverF37
How to Monitor Column Uniqueness in SQL Server
www.metaplane.dev/how-to-monitor/mean-in-databricksF37
How to Monitor Column Mean in Databricks
www.metaplane.dev/how-to-monitor/max-in-databricksF37
How to Monitor Column Max in Databricks
www.metaplane.dev/data-observability/data-regression-testsF38
Data Observability: Data Regression Tests | Metaplane
Changes since v1Last audited 52 days ago
51
52
+1
View full comparison →
Add Original Data & Case StudiesBuild Comprehensive FAQ SectionAdd Direct Answer ParagraphsAdd Structured Tables & ListsRestructure Content as Q&AImprove Question-Answer AlignmentStrengthen Entity Authority (NAP)Add Content Freshness SignalsAdd Answer-First PlacementImprove Citation-Ready Writing

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