AI Visibility for Local Businesses

Local-intent prompts are already the norm

People have carried the same “near me” and “in [city]” habit they built with Google search over to AI assistants, because the assistant now gives a direct recommendation instead of a results page to click through. Typical local-intent prompts look like:

• Best-of: “best dentist in Leipzig”, “top-rated moving company in Phoenix”
• Comparison: “X vs Y near me, which is better for [need]”
• How-to with local intent: “how do I find a reliable roofer in [city]”
• Pricing: “how much does a plumber charge for a callout in [region]”

TAMGIO treats “local” as one of five prompt-intent categories — alongside best-of, comparison, how-to, and pricing — when a project's 30-40 tracked prompts are written or AI-generated for approval, so a business can see, intent by intent, whether it shows up.

Why it matters even in small or regional markets

A national “best CRM software” prompt might have to compete against dozens of established brands for a single mention. A “best plumber in [mid-size city]” prompt usually has a realistic pool of only a handful of businesses an AI answer can name. That changes the math:

• The competitive set is smaller. One AI mention in a local prompt carries proportionally more weight than one mention in a saturated national category.
• The funnel compresses to one paragraph. When an AI assistant names two or three businesses instead of listing ten links, being one of those names functions like a direct referral — and being absent hands that referral to a competitor.
• The signals AI models draw on differ from classic map-pack ranking factors. Grounded answers (Perplexity Sonar, Gemini grounded search, OpenAI web_search) pull from live web content and citations, not purely from directory-listing signals, so a business's own content, reviews, and web presence all feed into whether it gets named.
• Google AI Overviews behaves differently again. It's SERP-embedded and deterministic per search, and it doesn't always appear for a given query — a “no_surface” result means the AI Overview simply wasn't shown, which is not the same as the brand being left out of it.

How TAMGIO measures local AI visibility

TAMGIO tracks a domain across four surfaces — OpenAI web_search (gpt-4.1-mini), Perplexity Sonar, Gemini grounded search, and Google AI Overviews via SerpAPI — and reports the same four core metrics for any prompt set, local or otherwise: Mention Rate, Share of Voice, Citation Rate, and Prompt Coverage. Because AI answers are non-deterministic, every metric is an N-sample proxy rather than a single-shot check, and only grounding-verified answers count toward the numbers; errors and no-surface results are shown openly, never hidden.

Every metric carries a dashed underline — opening it reveals the raw API response, the citations, and the timestamp behind that number, so a business can see exactly which answer produced which result instead of trusting a black-box score.

For a business that wants a first read before committing to ongoing tracking, Audit Mode runs a one-time scan (10–12 prompts × 3 LLM engines × N=2 + Google AI Overviews) and produces an audit report. See the TAMGIO homepage for how the full measurement approach works.

Pricing