Use case 01
Measure AI visibility
Build a repeatable view of brand mentions and citations across named AI services without turning sampled observations into universal rankings.
Use cases
Start with the decision, not the software.
AI SEO use cases work best when the question, evidence, and human decision are clear before a tool enters the process. These seven guides cover visibility, citations, prompts, crawlability, content, referral traffic, and reporting. Each one separates what can be observed from what cannot be promised.
Seven workflows
Choose the job you need to do
Each guide gives you three steps, a human decision point, suitable tool categories, and a clear evidence boundary.
Use case 02
Find citations and source influence
Identify cited pages and recurring source domains, then use them as research evidence rather than a shortcut to guaranteed inclusion.
Use case 03
Research prompts
Build a useful prompt set from real customer language, then version and test it without inventing universal AI-query volume.
Use case 04
Audit AI crawlability
Check whether named AI crawlers can reach and interpret representative site pages while keeping readiness separate from visibility.
Use case 05
Optimize content for AI search
Make pages clearer, better supported, and easier to extract while avoiding keyword stuffing and promises of guaranteed AI citations.
Use case 06
Track AI referral traffic
Identify attributable visits from AI services and report their behavior without relabeling unknown traffic or zero-click exposure.
Use case 07
Build SEO and AI-search reports
Report technical readiness, sampled AI observations, search performance, referrals, and outcomes as separate evidence layers.
What these guides do not promise
A workflow can make research more consistent and decisions easier to audit. It cannot guarantee rankings, inclusion in an AI answer, citations, referral traffic, or revenue. Start with the guide, then browse the source-checked tool inventory.