The AEO gap widget
Six sample queries a real prospective student might type into an AI engine. The columns below are an illustrative manual estimate, not a measured probe. They show the shape of the gap that the Option A run would confirm with real data.
| Sample query | SFU AI-cited today? | Who gets cited instead | Opportunity |
|---|---|---|---|
| psychotherapy degree Vienna | Unclear, likely No | Rankings sites, established public unis | High |
| study psychology Austria in English | Likely No | Aggregator rankings, larger universities | High |
| medical school Vienna private | Unclear | Public medical universities, directories | High |
| psychotherapy science masters Europe | Likely No | Course aggregators, mixed EU institutions | High |
| best private university Austria | Unclear | Rankings and "best of" listicle sites | Med |
| Sigmund Freud University reviews | Partial | Review aggregators, forums | Med |
Illustrative manual estimate only. "Likely No" and "Unclear" are honest first-pass reads, not measured citation results. The full 4-platform probe replaces every cell with a real, dated answer.
Why SFU is invisible
The same six signals from the technical read, viewed through the AI-citation lens. Short version: AI engines cannot cite what they cannot cleanly understand and extract.
Schema
Thin structured data means AI cannot reliably parse programs into citable facts.
Citations
Program-level citation density is likely under-built, so AI lacks corroboration to cite SFU.
Entity / KG
An incomplete knowledge-graph entity means AI may not map queries to SFU at all.
Citable copy
Prose-heavy pages are not answer-shaped, so AI quotes a cleaner source instead.
Consistency
Entity drift across six campuses weakens the trust signal AI relies on.
E-E-A-T
Real strength here. Faculty credentials and accreditation are an asset to surface, not a gap to fill.
Day 30 / 60 / 90 citation targets
What "getting cited" looks like as a staged target. These are direction-setting targets for a first engagement, not guarantees. AI citation is probabilistic, and we frame it as increased likelihood of citation, never a ranked position.
| Window | Target | Focus |
|---|---|---|
| Day 30 | Foundation laid | Course schema live, top program pages restructured to be answer-shaped, Wikidata entity opened. |
| Day 60 | First citation movement | FAQ answer content per flagship program, faculty entity pages, third-party citation building underway. |
| Day 90 | Measurable AEO presence | Re-probe the same query set across all four platforms and show increased likelihood of citation on the priority queries. |
The 5-move plan to flip citations
| # | Move | What it flips |
|---|---|---|
| 1 | Entity build (Wikidata + knowledge graph) | Lets AI place SFU and its programs accurately against the query. |
| 2 | Citable program pages | Turns each program into extractable, quote-ready facts. |
| 3 | Schema (Course + Organization + FAQ) | Makes the structure machine-readable and citation-eligible. |
| 4 | Third-party citations | Builds the corroboration AI needs before it will cite a source. |
| 5 | FAQ / answer content | Provides the direct question-and-answer blocks AI engines quote verbatim. |