Visibility Baseline

Extended definition

A Visibility Baseline establishes your starting point across all relevant AI engines and query sets before optimization initiatives begin. This comprehensive measurement captures: citation share by topic and engine, answer share percentages, entity recognition accuracy, citation positioning (lead vs mid vs tail slots), and competitive comparisons. The baseline serves as the control group for measuring improvement and provides data-driven prioritization for where to focus efforts. Without a rigorous baseline, you can't prove ROI or know which initiatives actually moved metrics.

Why this matters for AI search visibility

You can't optimize what you don't measure. A proper baseline transforms AI visibility from guesswork into engineering: clear starting metrics, measurable progress, and provable ROI. For executives and boards, baselines provide the 'before' snapshot that makes 'after' results credible. Baselines also reveal surprising gaps—topics where you expected visibility but have none, or engines where competitors dominate despite your market position. These insights redirect strategy before wasting resources on assumptions.

Practical examples

• A baseline audit reveals 4% citation share despite 28% market share, quantifying a 24-point visibility gap worth immediate investment
• Baseline measurement shows zero visibility in Perplexity despite strong ChatGPT presence, identifying a critical blind spot
• Six months post-baseline, a company demonstrates 327% citation growth and uses the data to justify doubling visibility budget