What Is a Good AI Visibility Score?

A good local AI appearance rate is 37.3 percent or higher. That is the top-quartile line in the Cheers panel, 28 days ending September 2, 2026, 119 home-services organizations, aggregate only. The median is 27.4 percent, and 47.4 percent marks the top decile.

Last verified: September 2, 2026.

My benchmark is:

• Below 15.1 percent: bottom quartile. The business is absent from most tracked buying prompts.
• Around 27.4 percent: median. The business appears in fewer than a third of tracked answers.
• 37.3 percent or higher: good. This is top-quartile performance in the panel.
• 47.4 percent or higher: top decile. The business appears in nearly half of tracked answers.

The panel mean is 27.0 percent and the mean citation rate is 22.0 percent. Every organization in the panel tracks roughly 31 buying prompts, the window is the 28 days ending September 2, 2026, and the only figures I publish are aggregates: no single organization's results are broken out, and the panel is home services, so a dentist or a law firm should not read these bands as their own. The full cuts are in AI visibility statistics, the sampling rules in the methodology, and the AI visibility benchmark report explains the underlying recommendation gap.

One brand, four different scores

The same 119 organizations score differently depending on which engine you ask. Median appearance by engine, same window: Google AI Overviews and AI Mode 31.8 percent, Gemini 25.6 percent, Perplexity 23.9 percent, ChatGPT 21.6 percent. Citation rates diverge harder than that. The panel mean citation rate is 34.3 percent on Perplexity and 12.4 percent on Gemini, so a brand can be named often on one surface and almost never used as a source on another.

Prompt shape moves the number too. Price and cost questions returned a 37.9 percent pooled appearance rate across the panel; "best near me" and named-place prompts returned 22.8 percent. If a vendor quotes you one score, ask which engines and which prompt shapes are behind it before you compare it with anything.

When ChatGPT did name a panel organization, the mean mention position was 2.87. Third on the list is a different commercial outcome from first, and an appearance rate on its own will not show you that.

Use appearance rate before a blended score

Vendors calculate AI visibility in different ways, and they say so in their own documentation. BrightLocal describes its visibility score like this:

It combines how often you're mentioned, where you appear in answers, how positively you're described, and how strongly you're recommended to a score out of 100.

Local Falcon scopes its metric far more tightly:

Share of AI Voice (SAIV) is a metric that shows how visible your brand is within AI-generated search results for a specific query and area.

One is a blended index out of 100 across platforms. The other is a per-query, per-area share. Both are useful inside their own tool. Neither converts into the other, and a vendor quoting "your AI visibility score went up 12 points" has told you nothing you can audit.

I start with appearance rate: the share of tracked answer runs in which the business appears. It is plain enough to audit from the saved responses. Citation rate answers a separate question: how often the business or its site is cited as a source.

A score without location detail misleads

Suppose a parent brand has a healthy aggregate because a few mature branches appear often. That number can hide a new acquisition whose name, page, Business Profile, reviews, and citations still disagree.

The correct operating view breaks the score down by location, buyer prompt, engine, competitor, and cited source. A plumbing branch can perform well for drain cleaning and disappear for water-heater replacement. An HVAC branch can appear in Gemini and miss in ChatGPT. The average does not tell the owner which problem to fix.

The location-level audit guide shows how to store those dimensions. The source comparison explains why one engine cannot stand in for the rest.

How to use the percentile bands

Treat the panel bands as an operating benchmark, not a promise. If a branch is below 15.1 percent, inspect whether the prompts match real services and whether the public facts are correct before starting content work. If it is near the median, compare lost prompts with the competitors and sources that appear instead. If it is above 37.3 percent, protect the working source coverage and look for weak service lines rather than chasing the aggregate.

Re-run the same prompt set on a consistent cadence. Changing the engines, markets, or questions changes the denominator and breaks the trend.

You can establish a current baseline with the AI Visibility Grader. For a multi-location program, keep the branch-level detail even when leadership receives one rollup.

Sources

Every link below was opened and checked on September 2, 2026.

• Cheers panel, 28 days ending September 2, 2026. 119 home-services organizations, aggregate only, about 31 tracked buying prompts per organization. Supports the appearance-rate mean, the percentile bands, the per-engine medians, the prompt-shape rates, and the citation-rate means. Figures pulled September 3, 2026. Methodology.
• What does each Local AI Visibility metric mean?. BrightLocal Help Center. Definitions of visibility score, mention rate, share of voice, and average position.
• Local Consumer Review Survey 2026. BrightLocal, February 2026. Consumer-side adoption context for why the appearance rate matters.
• How to use Share of AI Voice. Local Falcon Knowledge Base. The per-query, per-area definition.
• Optimizing your website for generative AI features on Google Search. Google Search Central, last updated July 2026. What Google says eligibility for AI surfaces depends on.

Dylan Allen-Arnegard is the CEO and Co-Founder of Cheers. I help multi-location service brands get recommended by AI search and Google, with results tracked by location, employee, and competitor.