Your competitors have a higher AI visibility score than you when AI assistants mention, recommend, or cite them more often for the questions your buyers ask. To find those rivals, run the same category prompts across ChatGPT, Gemini, and Perplexity, record who appears, and weigh not just how often each brand shows up but where, how it's described, and which sources back it.
We build blog content at Grid13 that gets brands cited in AI answers, so we watch these scores move week to week. Here's how the score actually works, why some competitors sit above you, and a method you can repeat this week without buying anything.
What an AI Visibility Score Measures — And What It Ignores
An AI visibility score compresses one messy question into a single number: when someone asks an AI system about your market, how present is your brand in the answer? Most tools express it on a 0-100 scale. According to Rankfender, 67% of B2B buyers now use AI for product research, which is why this number stopped being a novelty and became a KPI teams report on.
The trap is treating the score as pure frequency. Being named ten times as "one option among many" is worth less than being named once as "the tool we'd recommend." A serious AI visibility score weighs several things at once:
- Position — first sentence of the answer versus a footnote link.
- Sentiment — described as trusted, or described with a caveat.
- Source quality — cited from a respected third party, or from your own homepage.
- Recommendation language — "best for" and "we suggest" versus a flat mention.
- Prompt importance — visibility on a high-intent buying prompt outranks visibility on trivia.
Where the score lands has real weight. Presenc.ai puts the cross-industry median at 49 out of 100, with SaaS and technology leading at a median of 63 and construction and real estate trailing at 31. If you're a SaaS brand scoring 40, you're below your own field's median — that context matters more than the raw digit.
Why Do Some Competitors Rank Higher in AI Answers?
When we audit a client against rivals, the gap almost never comes down to one thing. It's a stack of advantages the AI model has quietly absorbed.
The most common reason is third-party coverage. AI models trust what other credible sites say about a brand more than what the brand says about itself. A competitor with independent reviews, comparison articles, and press mentions gives the model more corroborating evidence to lean on. That's compounding, too: LLM Research Lab found the top three brands in any category now capture 68% of all AI-generated mentions, up from 54% in Q3 2025. The leaders are pulling away.
The second reason is structural. Foglift reports that brands with comprehensive JSON-LD markup score 23 points higher on average than those without, regardless of industry. Clear schema, clean headings, and direct answers make your content machine-readable — a competitor who did that work is easier for the model to quote.
The third is simple absence. Botify found that 62% of brands are invisible on at least one major AI platform. If your rival shows up on Perplexity and you don't, they win that surface by default — you're not being outranked there, you're not in the room.
A Method You Can Repeat This Week (No Budget Required)
You don't need to subscribe to anything to see where you stand. Here's the process we run before we ever touch a tool:
- Write 10 to 15 real buyer prompts. Not "what is [category]" — write the questions a customer actually types: "best [product] for a 20-person team," "[competitor] alternatives," "is [your brand] any good." Prompt quality decides everything downstream.
- Run each prompt in ChatGPT, Gemini, and Perplexity. Use a fresh chat each time so past context doesn't skew results. Perplexity is the most useful for this because it shows its cited sources openly.
- Log every brand named, and how. A spreadsheet with columns for platform, prompt, brands mentioned, position, sentiment, and cited source. This becomes your homemade AI visibility score.
- For free automated checks, layer on the vendor tools. Semrush's AI Visibility Checker and Ahrefs' AI Visibility Checker both run without payment and return a score plus a mention breakdown. Treat their numbers as directional, not gospel — each vendor measures differently.
- Repeat across models on purpose. Profound measured a median 8-point visibility gap between a brand's best and worst-performing Google model across 15,155 configurations tracked daily in May 2026. One platform can flatter you while another buries you.
What not to do: don't run one prompt in one model, screenshot a flattering answer, and call it a benchmark. AI answers vary by session, region, and phrasing. A single lucky result tells you nothing you can act on.
How Do You Read the Score Against Your Rivals?
Once you have the data, resist the urge to build a leaderboard and stop there. The point of an AI visibility score is to expose fixable gaps, not to hand you a trophy or a wound.
Read it by platform first. If a competitor beats you on Perplexity but you're even on ChatGPT, the problem is source-based — Perplexity leans hard on cited web pages, so you likely lack the third-party references it pulls from. Read it by prompt next. Losing on "best [category]" prompts hurts more than losing on a niche edge case, because those are the prompts near a buying decision.
Then read the language. A competitor who appears less often than you but gets described as "the most reliable" is winning the part that converts. Frequency without warmth is hollow. This matters more as trust shifts — Frac.tl reports consumer trust in AI search dropped from 82% to 54% in a year, so how a brand is framed increasingly carries the recommendation.
How to Close the Gap on a Higher-Scoring Competitor
Every gap in the audit maps to one of four moves. That's the practical payoff of the score.
- Content: If rivals appear on prompts you don't, publish direct, well-structured answers to those exact questions. Lead with the answer, use clear headings, and add an FAQ section AI models can lift verbatim.
- Public relations: If a competitor's edge is third-party coverage, earn mentions on the sites your buyers and the models already trust. This is the slowest lever and usually the decisive one.
- Reputation: If sentiment lags, address the reviews and comparison pages shaping how you're described. Models echo the consensus they find.
- Technical: Add JSON-LD schema, fix crawlability, and make your pages machine-scannable. Given Foglift's 23-point schema finding, this is often the fastest measurable win.
None of this is guesswork once you've done the audit. The score points at the weakest lever, and you pull it.
Frequently Asked Questions
What is a good AI visibility score?
It depends entirely on your industry. The median across all sectors is 49 out of 100, but SaaS and technology brands need a median near 63 to be average in their field, while construction and real estate sits around 31. Compare against your own sector, not the global number.
Why does my competitor show up in AI answers when I don't?
Usually because they have more independent coverage, cleaner structured data, or a presence on a platform you've ignored. Botify found 62% of brands are invisible on at least one major AI platform, so the gap is often simple absence rather than being actively beaten.
Can I check my AI visibility score for free?
Yes. Semrush and Ahrefs both offer free AI Visibility Checkers that return a score and mention breakdown, and you can run buyer prompts manually in ChatGPT, Gemini, and Perplexity yourself. Use the free tools as directional signals, since each vendor calculates the score its own way.
How often should I recheck the score?
Monthly is enough for most brands, more often if you're actively publishing to close a gap. AI answers shift constantly — Profound tracked a median 8-point swing between a brand's best and worst Google model in a single month, so one snapshot isn't a trend.
Does frequency alone determine the score?
No, and treating it that way is a mistake. Position in the answer, sentiment, the quality of the cited source, recommendation language, and how important the prompt is all shape the real value. One warm "we'd recommend" beats ten neutral mentions.
Turn the Score Into a Roadmap
A higher-scoring competitor isn't a verdict — it's a map of what to fix. Once you know which prompts, platforms, and sources they own, you know exactly where to publish, earn coverage, and clean up your markup. That's the whole point of measuring: not the ranking, the roadmap. With Gartner forecasting that AI-powered search will influence over 40% of B2B technology purchases by 2027, closing the gap now is cheaper than closing it later.
Grid13 builds the structured, citable blog content that moves an AI visibility score — the direct answers, schema, and FAQ formats AI models actually quote. See how Grid13 turns one keyword into content AI search cites.