01
See
Build a repeatable prompt set and establish where the brand appears, disappears or is misrepresented.
Methodology
Observe carefully. Change deliberately. Verify honestly.
GEO is not a single technical switch. AIARF uses a repeatable research loop that connects answer observations to the public evidence available about a brand.
Important limitation
No outside provider can guarantee inclusion, ranking or citations in a generative answer. AIARF measures observable change and improves the information environment around a brand.
02
Explain
Trace the sources, entities and content patterns that are most likely shaping the observed answers.
03
Act
Prioritize specific changes across owned pages, structured facts and third-party evidence.
04
Verify
Re-run the same questions over time and record what changed, without promising deterministic rankings.
Research controls
A baseline only matters if it can be repeated.
The following controls keep the output useful without pretending that probabilistic systems behave like fixed search results.
Prompt control
Use stable, documented questions grouped by buyer journey and category intent.
Time control
Timestamp every capture because answer systems, indexes and interfaces change.
Platform control
Report each engine separately instead of merging different retrieval behaviors.
Evidence control
Separate direct observation from inference and retain the source trail.
What the machine layer contains
The same facts, in formats agents can parse.
Human pages and machine-readable files share the same claims. There is no hidden second story and no content served only to crawlers.
- Semantic server-rendered HTML
- Schema.org structured data
- llms.txt and Markdown summary
- Robots and XML sitemap
- Canonical page metadata
- Public change-ready research notes