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Academy

GEO Foundations — Certification Course

A short self-paced course covering how generative engines choose brands, how visibility is measured, and how to run a first audit end to end. Finishes with an assessment and a CiteRank certificate.

CiteRank AI Research·10 July 2026·Course · 3h 10mIllustrative data
AcademyCertificationFundamentals

Key takeaways

  • —You finish able to scope and run a defensible AI visibility audit, not just describe one.
  • —Every metric taught is published with its formula, so nothing in the course depends on a black box.
  • —The certificate is tied to a method version and expires, because the method changes.
Course outline
Level
Foundation — no prior GEO experience needed
Duration
3h 10m across 6 modules
Format
Self-paced · written lessons, worked examples and a practical exercise

  1. 01 How generative engines pick brands

    30 min

    Retrieval, synthesis and recommendation: what actually happens between a prompt and a named brand across the eight tracked engines.

  2. 02 The prompt is the unit of analysis

    35 min

    Why keywords stopped predicting answer inclusion, and how to design a stratified prompt corpus for your category.

  3. 03 Measurement and the metric suite

    35 min

    Visibility Score, Recommendation Share, Citation Score and Entity Health — definitions, formulas and what each one cannot tell you.

  4. 04 Entity hygiene

    30 min

    Auditing names, locations, people and products, and sequencing entity fixes before content work.

  5. 05 Running your first audit

    35 min

    A guided walkthrough: scope the corpus, run the replay, read the report, pick the first three actions.

  6. 06 Reporting to stakeholders

    25 min

    Turning a visibility report into an executive narrative without overstating what modelled data can prove.

Assessment — 25-question assessment plus one submitted audit scope. Pass mark 80%. Two retakes included.

CiteRank AI Academy
CiteRank Certified — GEO Foundations
Awarded to Your Name on completion
Prompt corpus designAI visibility measurementEntity auditingAudit reporting
Credential ID · CR-GEOF-2026-XXXXXXValid 24 months, tied to the method version taught
Sample certificate — illustrative preview of the credential issued on completion. Names and credential IDs shown are placeholders.

Who this is for

Marketing leads, SEO practitioners and agency strategists who need to answer 'how does AI see our brand' with a method they can defend in a meeting.

What you need beforehand

No prior GEO experience. Familiarity with basic search or analytics reporting helps but is not required.

Frequently asked

Is the course free?

Foundations is included with any CiteRank workspace, and the outline above is public so you can evaluate it first.

Is the certificate verifiable?

Each certificate carries a credential ID in the format shown. Verification is planned as part of the Academy rollout — the sample certificate on this page is illustrative.

Methodology, limitations and disclosure

Every CiteRank study states who produced it, what it measured and where it stops being reliable. The full scoring model is documented on the methodology page.

Author
CiteRank AI Research
Author role
CiteRank AI Research team — measurement, prompt-corpus design and scoring
Review
Internal editorial review by the CiteRank AI Research team. No external or academic peer review was conducted.
Published
10 Jul 2026
Last updated
10 Jul 2026
AI engines
Not engine-specific
Model versions
Specific model build identifiers are not disclosed by every vendor and are therefore not claimed here.
Industry scope
Professional Services
Geographic scope
Global
Language scope
English
Sample size
Not disclosed for this entry
Conflicts of interest
CiteRank AI publishes this research and sells an AI visibility platform. No third party funded, commissioned or reviewed this entry.
Data availability
Underlying raw data is not published. Method and scoring are documented on the Methodology page.

Limitations

  • Figures in this entry are modelled and clearly labelled illustrative. They demonstrate structure and method; they are not observed client results.
  • AI engines are non-deterministic: an identical prompt can return a different answer on replay, so every figure is a sampled estimate rather than a fixed value.
  • Engine vendors change retrieval and ranking behaviour without notice. Findings describe the sampling window stated above, not a permanent state.
  • Results describe the prompt corpus that was designed for this study. A different corpus for the same brand can produce a materially different picture.
  • This entry does not disclose a sample size, so its figures should not be treated as statistically representative.

Suggested citation

CiteRank AI Research (2026). GEO Foundations — Certification Course. CiteRank AI. https://www.citerank.in/research/academy-geo-foundations

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