Methodology version 1.0

AI SEO Course Study Methodology

What qualifies as an AI SEO course?

A program qualifies for the study when its public curriculum contains substantive training relating to AI search optimization, generative engine optimization, answer engine optimization, LLM visibility or AI-driven search. A general SEO course is not classified as an AI SEO course merely because it teaches students how to use ChatGPT for content creation. Programs sold under the AI SEO label that turn out to teach AI-assisted conventional SEO are kept and flagged, because a buyer searching for the label will meet them.

What data is collected?

For every AI SEO course, the study attempts to record: course name, provider, instructor, price, price model, format, experience level, GEO coverage, AEO coverage, LLM citation training, entity SEO, AI visibility measurement, traditional SEO, link and mention training, whether ChatGPT is named, community access, live support, update model, certificate, module count, status, last verification date and primary source.

How are AI SEO courses checked?

The current provider-controlled page is the preferred source for provider-controlled information. Where possible, each record is checked against:

1. The official course page.
2. The published curriculum or syllabus.
3. Current pricing or checkout information.
4. Provider documentation.
5. Relevant independent sources when clarification is required.

Every mutable record receives a verification date. Where two official pages disagree, the record says so and names the page used for the headline figure.

How are claims classified?

Provider-stated the course provider published the information.
Observed AI SEO Course Study independently observed the information.
Calculated the value was derived from sourced data.
Unverified current evidence could not confirm the claim either way.
Study finding the conclusion was derived from the dataset.

How are study findings calculated?

Aggregate findings are calculated only from records containing the required verified field. For example, the percentage of AI SEO courses teaching LLM citation optimization is calculated as:

verified courses explicitly teaching LLM citation optimization ÷ eligible verified courses × 100

The denominator and verification date are published alongside the result. Medians are reported separately for monthly memberships and one-time purchases. Unverified values never count as No.

How are AI SEO courses ranked?

Where a comparison or grouping is published, the criteria and source data are disclosed. AI SEO Course Study does not treat marketing claims, popularity or price alone as evidence that one course is superior, and does not publish a single-number score.

How often is the study updated?

Course pricing, curricula and availability can change rapidly. Records are rechecked when new information becomes available and material changes are recorded in the update log. The dataset version increments with each recheck.

Corrections

Incorrect information can be submitted with a public supporting source to research@aiseocourse.study. Verified factual corrections are incorporated into the dataset and dated. Providers may submit curriculum pages that were not public at the time of checking; the record is then updated with the new date.

Limitations

The study reads public pages, not course content behind a paywall. A program can teach a subject without naming it on its sales page; the study records what the page says, and the record's evidence field paraphrases the wording relied on. Prices are US dollar headline figures on the day checked and exclude tax, discounts and regional pricing. The dataset is a census of programs the study found, not a random sample, so percentages describe the tracked set rather than every AI SEO course in existence. Prices and curricula for the AI SEO course study are rechecked on a rolling basis.