Most tool comparisons stop at a feature checklist. The real question is whether a platform helps your team make better content, citation, and authority decisions. The seven criteria below are the questions to ask before you pick a tool.
Read the criteria, then run an audit before you decide.
Each criterion below is phrased as a question. Use them when you talk to any AI visibility vendor, including us. If a tool cannot answer cleanly, it probably will not help your team prioritize the right next move.
Does the tool measure AI visibility inside generated answers, or only traditional search rankings?
Does the tool also surface the SERP sources, related questions, and citation candidates that may be shaping the AI answer?
Does the tool actually run prompts across multiple AI engines in parallel, with token and cost capture per call?
Can you see why a query is scored a quick win, a competitive gap, or an authority play — or is the score a black box?
Does the tool segment queries into actionable buckets — quick win, competitive gap, authority play, monitor, ignore — or only show flat numbers?
Does each visibility gap map to a next step across content, citation, authority, accuracy, or monitoring?
Does the tool give you predictable usage and cost — with metering on external calls, plan-based queue priority, and idempotency on runs?
AI visibility is still an emerging category. The platforms that will actually help your team are the ones that measure what AI engines do, explain how they score it, and turn it into prioritized actions — not the ones with the longest feature list.
Run an AI visibility audit first. Then bring the seven criteria above to every vendor conversation you have — including ours.