Visibility should be measured before it's optimized.
Most businesses have some idea how they appear on Google. Far fewer know what happens when a customer asks an AI assistant who they should hire. Local Visibility IQ measures both.
Measure
We run a set of commercially relevant customer questions — the kind a real prospect would ask — across ChatGPT, Google AI Mode, Gemini and Perplexity, and pair that with a review of traditional search performance.
Diagnose
We look at who's appearing instead of you, and investigate the websites, citations, profiles, reviews and authority sources associated with those results. We separate what we observed from what we think may explain it.
Prioritize
We don't hand clients a fifty-item checklist. We identify the highest-value opportunities based on impact, evidence and effort, so the work that gets done first is the work most justified by the evidence.
Improve
For managed clients, we implement the prioritized improvements directly — website changes, local-search fundamentals, citation and entity work, and content where it's warranted.
Retest
We repeat the measurement on a regular cadence and track how AI visibility, organic search performance and competitive position change over time.
Seven diagnostic areas.
Each study looks across the same seven areas, at a level appropriate to the business. We don't expose a proprietary scoring formula — the value is in the judgment applied to what we find, not a black-box number.
- Entity clarity — how clearly a business is identified as itself across the web.
- Website relevance — whether the site actually answers the questions customers are asking.
- Local-search foundation — the basics: profiles, categories, service areas, consistency.
- Authority and citations — the sources that repeatedly get referenced alongside a business.
- Reputation — reviews and the signals that come with them.
- Technical discoverability — whether search engines and AI crawlers can actually read and understand the site.
- Conversion and measurement — what happens after someone finds you, and whether we can track it.
Observation vs. explanation.
We separate what we observed from what we think may explain it.
An AI platform recommending a competitor is an observation. Why it's happening is a hypothesis, and we treat it as one until the evidence supports something stronger. That distinction shapes every report we write.
Ready to see where you stand?
We'll walk through what a Visibility Snapshot would look like for your market.