AI Visibility Scorecard
simonhessner.de · Education
At 2.47/10, Simon's blog is near-invisible in AI search today. Most AI engines will not name it when asked about its category. The weakest signals are Structured Data, E-E-A-T Signals and Backlinks. That is fixable, and the signals below show where to start.
AI engines read this profile 6 times
Meta AI · Claude
Top 50% in Education for AI visibility
19
AI Naming Predictability
iRarely named · 19/100
Education average 14
Top 20% of Education
See what's behind this score →2.47
-
Network Authority
iNot connected yet
0 relationships on record. Businesses in Education average 4. Claim your page and Engagemii is your first.
See what's behind this score →5
6
from our crawl and measurement
Simon's blog is a business whose own site puts it this way: "It covers many topics of the LLM lifecycle in three weeks of videos, labs and quizzes." To AI engines like ChatGPT and Perplexity, though, it is barely visible: it scores 2.47 out of 10.
Our crawl found a sitemap, a readable heading structure, substantial page content. It also found the gaps that keep answer engines guessing: structured data describing the business, an llms.txt file.
Strong · Good · Fair · Weak
Structured Data
Weak
Organization / LocalBusiness JSON-LD that AI can read.
Content Structure
Strong
Clear headings and answer-style content.
Entity Clarity
Fair
How clearly your brand identity reads to AI.
E-E-A-T Signals
Experience, Expertise, Authority, Trust
Weak
Experience, Expertise, Authority, Trust markers.
Technical AEO
Fair
robots.txt, llms.txt, and AI-bot crawl access.
AI Discoverability
Fair
Sitemaps and entity links AI can follow.
How the web signals your brand to AI
Backlinks
Weak
No inbound links found yet.
Domain Authority
Weak
Little domain authority yet.
Reference Presence
-
Not yet measured.
News & Press
Weak
No press coverage found yet.
Community
Weak
No community discussion yet.
Social Mentions
Weak
No social discussion found yet.
Your AEO score measures whether AI search engines (ChatGPT, Claude, Perplexity, Gemini) can read your site and name it in answers. At 2.47/10, Simon's blog is near-invisible to AI engines today. That is fixable, and the signals above are where to start.
Why are precision, recall and F1 score equal when using micro averaging in a multi-class problem?
July 19, 2018June 12, 2019 Simon 15 Comments In a recent project I was wondering why I get the exact same value for precision, recall and the F1 score when using scikit-learn’s metrics. The project is about a simple classification problem where the input is mapped to exactly \(1\) of \(n\) classes.
ChatGPT doesn't crawl the web like Google does. When someone asks Claude about the best project management tools, the model isn't searching your website in real-time. It's pulling from training data that stopped months or years ago.
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Scored by Engagemii on November 9, 2026. Methodology: engagemii.com/aeo/methodology
Source URL: https://engagemii.com/aeo/brands/simonhessner-de
Cite this score: Engagemii (2026). "AEO Score for Simon's blog." Retrieved from https://engagemii.com/aeo/brands/simonhessner-de
Licensed under CC BY 4.0. You may reuse this data with attribution: a visible link to engagemii.com.
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