1 min read
Rather than citing someone else’s numbers, it’s more useful to have a repeatable method for running your own AI search visibility case study.
A simple methodology
- Pick a small set of representative queries in your topic area
- Check whether your content is cited across major AI assistants, and note the exact wording used
- Make one specific change — e.g., adding a clear definition section or updating structured data
- Re-check the same queries after a reasonable interval and record what changed
Why this matters
A documented before/after process gives you evidence specific to your own content, rather than relying on generic industry claims. See AI SEO. More in Research & Data.
Related Reading
Related in Research & Data:
- Designing an Internal Linking Experiment
- How to Run a Schema Markup Case Study
- Designing a Core Web Vitals Experiment
- Designing a GEO Experiment
- AI Search vs. Traditional SEO: How to Compare Them Fairly
Supporting reading from related clusters:
Cornerstone guide: SEO Audit