Category Definition for AI Visibility
Category Definition gives teams defining the market language an audit should test a controlled input for AI visibility measurement instead of relying on ad hoc prompts or screenshots.
Open the playbookPlanning library
Plan an Evidence-Led AI Visibility Program
Build the inputs, evidence standards, review stages, actions, and retests behind a defensible AI visibility program.
Choose the page that matches the decision
A durable program starts before the first model run: define the market, questions, competitors, measurement contract, review rules, and decision cadence.
10 distinct workflows
Buyer Question Research for AI Visibility
Buyer Question Research gives teams building a commercially meaningful prompt portfolio a controlled input for AI visibility measurement instead of relying on ad hoc prompts or screenshots.
Open the playbookCompetitor Set Design for AI Visibility
Competitor Set Design gives teams choosing which vendors to compare in an audit a controlled input for AI visibility measurement instead of relying on ad hoc prompts or screenshots.
Open the playbookPrompt Portfolio Design for AI Visibility
Prompt Portfolio Design gives teams turning buyer intent into a stable measurement set a controlled input for AI visibility measurement instead of relying on ad hoc prompts or screenshots.
Open the playbookMeasurement Baseline for AI Visibility
Measurement Baseline gives teams establishing the first defensible AI visibility benchmark a controlled input for AI visibility measurement instead of relying on ad hoc prompts or screenshots.
Open the playbookEvidence Review for AI Visibility
Evidence Review gives analysts and reviewers validating AI visibility findings a controlled input for AI visibility measurement instead of relying on ad hoc prompts or screenshots.
Open the playbookAction Prioritization for AI Visibility
Action Prioritization gives teams converting observed gaps into a focused backlog a controlled input for AI visibility measurement instead of relying on ad hoc prompts or screenshots.
Open the playbookRetest Planning for AI Visibility
Retest Planning gives teams evaluating whether an AI visibility change had the intended effect a controlled input for AI visibility measurement instead of relying on ad hoc prompts or screenshots.
Open the playbookReporting Cadence for AI Visibility
Reporting Cadence gives teams choosing how often to collect and review AI visibility evidence a controlled input for AI visibility measurement instead of relying on ad hoc prompts or screenshots.
Open the playbookMarket Segmentation for AI Visibility
Market Segmentation gives teams separating AI visibility results by buyer, geography, and use case a controlled input for AI visibility measurement instead of relying on ad hoc prompts or screenshots.
Open the playbookMeasurement before optimization
Read the methodology Keep every recommendation tied to evidence.
Use the methodology and audit template to define scope, record answers, review exceptions, and plan a comparable retest.