The Discovery Gap: Why AI Knows Your Brand But Won't Recommend It

AI knows who you are. It just does not recommend you.

Across 1,423 companies, average overall AI visibility is 0.615. Average category visibility is 0.092. The Discovery Gap (overall minus category) averages 0.515. And 97% of companies (1,378 of 1,423) are lower in category visibility than brand visibility. That is the headline.

Brand visibility is awareness. Category visibility is consideration. Most companies are losing at the consideration stage, which means they are recognized but not recommended when users ask "best X" or "X vs Y." If you want AI traffic, this is the bottleneck.

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The Discovery Gap, by the Numbers

Here is the full picture for the companies with category data:

Metric	Value
Reports with category data	1,423
Overall visibility average	0.615
Category visibility average	0.092
Average gap	0.515
Companies with lower category visibility	1,378
Companies with equal or higher category visibility	45

The gap is not a small edge case. It is the default state for almost everyone. AI can identify your brand when asked directly, but it does not surface you when users describe the category without a brand name.

This is why many teams feel like they are "known" but not "recommended." It is not a ranking problem. It is a discovery problem.

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Platform Breakdown: Where the Gap Is Worst

The gap shows up on every platform, but not equally.

Platform	Overall Avg	Category Avg	Gap
ChatGPT	0.703	0.099	0.604
Claude	0.643	0.061	0.583
Gemini	0.498	0.117	0.380

ChatGPT has the widest gap. Gemini is the least severe but still large. This matters because a platform-first strategy will not save you. Even the "best" platform in this dataset leaves a 0.380 gap between awareness and recommendation.

If your team only tracks brand prompts, you will miss the true problem. Brand prompts tell you whether AI knows you. Category prompts tell you whether AI recommends you. Those are not the same.

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The Discovery Gap Is a Funnel Problem

Think about the AI visibility funnel in two steps:

• Awareness: The model recognizes your brand when someone asks about you directly.
• Consideration: The model surfaces your brand in unbranded category prompts like "best AI sales tools."

Most teams are strong on awareness and weak on consideration. The data says this is normal, but it is also costly. The users who ask unbranded category questions are the buyers who are actively choosing. If you do not appear there, you are not in the decision set.

This also explains why traditional SEO wins do not always translate into AI recommendations. You can have a clean site, strong brand, and decent authority, and still be invisible in category prompts because you have not built the content and references that make you a recommended option.

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What the Gap Looks Like in Practice

Two anonymized examples from the dataset show the pattern clearly:

Example	Overall Visibility	Category Visibility	Gap
Company A	0.75	0.20	0.55
Company B	0.98	0.93	0.05

Company A is the "known but not recommended" archetype. It posts 69% on ChatGPT and Claude and 88% on Gemini overall, but category visibility is 0% on ChatGPT and Claude and 60% on Gemini. The average drops to 0.20. This is a brand that AI recognizes but does not promote in category discovery.

Company B is what closing the gap looks like. It sits near 1.0 overall and 0.93 in category visibility. That balance means the brand appears consistently in both brand and category prompts. It is not just known. It is recommended.

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Why Category Visibility Is Harder

Category prompts are competitive by default. When a user asks for "best X," the model has to choose a short list. That is a harder problem than answering "what is Company Y." It is also where AI models rely heavily on comparative evidence: side-by-side reviews, lists, and third-party sources that signal which options are credible.

This is why category visibility is the real test. It is the moment where the model decides which brands deserve to be in the answer. The Princeton GEO study found that adding citations, quotes, and statistics increases AI visibility by 30-40% (KDD 2024). Those cues help with both awareness and recommendation, but they matter most when a model is deciding which brands to elevate in a competitive answer.

If you want to close the gap, you need to show the model that your brand is a category leader, not just a known entity.

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What Category Visibility Actually Measures

Category visibility is a proxy for recommendation. It answers a simple question: do you show up when your brand is not named? That is the moment where AI acts like a buyer. It compares, filters, and selects a short list.

If you only look at brand prompts, you will feel good and still lose the deal. Category prompts are where the shortlist forms. That is why the gap exists. It is not that AI does not know you. It is that AI does not have enough comparative evidence to elevate you.

Here are the query types that define category visibility:

• "Best [category] tools"
• "[category] alternatives"
• "[category] for [use case]"
• "[category] vs [category]"

If your content strategy does not target these prompts directly, you are not competing in the recommendation layer.

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Common Failure Modes That Keep You Invisible

Most teams share the same blind spots:

1. No category framing. Your site talks about features, not the category you compete in. The model cannot place you.
2. Branded content only. Your blog posts answer brand questions but never unbranded category questions.
3. No comparison evidence. You do not publish "vs" or "best" content, and third-party sources do not list you.
4. Inconsistent language. Your category name changes across pages, listings, and profiles. The model cannot map you cleanly.

Fixing these is not complex, but it is deliberate. Category visibility is earned by repetition, clarity, and third-party confirmation. If you want recommendation visibility, you need a public paper trail that says "we belong in this category."

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The Path from "Known" to "Recommended"

There is a simple pattern in how brands close the gap:

1. They own category content. They publish pages that answer the category question directly, without burying the answer.
2. They show up in comparisons. Their brand appears in "vs" and "best" content both on their site and on third-party sites.
3. They use consistent category language. The model sees the same category framing across their site, listings, and references.

This is not about gaming AI. It is about giving the model enough evidence to choose you when the user does not name a brand. If your content only speaks to brand prompts, you will stay visible only in brand prompts.

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What Actually Closes the Gap (Actionable)

Here is the short list of moves that reliably lift category visibility:

1) Build a real category page

A category page is not a product page. It is a clear answer to "best X" with criteria, comparisons, and tradeoffs. Keep it factual. Make it scannable. Use a short summary at the top and deeper sections below. This is the page the model looks for when the user asks category questions.

If you want a baseline structure, start with generative engine optimization and make sure the page uses clear headers, definitions, and a category taxonomy that matches how buyers speak.

2) Publish comparison content that is not fluffy

Comparison content is the bridge between awareness and recommendation. It lets the model see how your product performs against alternatives. Publish two types:

• "Best X" lists that include your brand with clear criteria
• "X vs Y" pages that define differences and who should choose each

This is where AI pulls from when users ask "best" and "vs" prompts. If you are not present in these surfaces, you will not be recommended.

3) Seed third-party comparisons

Category visibility is not just on your site. Models look to third-party sources for confirmation. If your brand is missing from review platforms, directories, and analyst writeups, you will not win category prompts.

The fastest lift often comes from getting listed and reviewed on credible surfaces. These are not just SEO links. They are the sources AI models trust when choosing recommendations.

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Make the Funnel Visible (Measure the Gap)

Most teams track brand visibility but not category visibility. That hides the real problem. You need both.

A simple way to track progress:

• Brand prompts: "What is [Company]?"
• Category prompts: "Best [category] tools"

Measure both and track the gap over time. If your overall visibility rises but category visibility stays flat, you are only building awareness. If category visibility rises, you are moving into recommendation territory.

Loamly makes this split visible in one report. If you want your current gap, start with the free AI visibility check, then track changes over time with AI website traffic analytics.

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A Practical 30-Day Plan

If you want to close the gap fast, run this plan:

Week 1: Category clarity
Create or rewrite one category page. Start with the one that maps to your highest-intent buyers. Use clear headers, criteria, and a summary that answers the category question directly.

Week 2: Comparison content
Publish one "best X" list and one "X vs Y" page. Keep it factual and specific. AI models reward clarity and evidence, not adjectives.

Week 3: Third-party coverage
Secure 2-3 third-party references that list you in the category. Review sites, directories, and industry blogs count more than press releases.

Week 4: Measurement
Re-run brand and category prompts. Track the gap. If category visibility does not move, adjust the comparison content first. That is the most responsive lever.

This is not a silver bullet. It is a repeatable system. The brands that close the gap are the ones who treat category visibility as a core KPI, not a side effect.

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FAQ

Is the Discovery Gap real for most companies?
Yes. In this dataset, 97% of companies with category data have lower category visibility than brand visibility.

What is a good target for category visibility?
Aim to bring category visibility within 0.25 of your overall visibility. That is a realistic first milestone and indicates you are moving into consideration.

Why is ChatGPT the worst gap?
ChatGPT has the largest average difference between overall and category visibility (0.604). It recognizes many brands when asked directly but recommends fewer brands in unbranded prompts.

How long does it take to close the gap?
You can move the needle in 4-6 weeks if you publish category and comparison content and secure a few third-party mentions. Sustainable gains come from consistency.

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Check Your Discovery Gap

If you want to see your brand vs category visibility, run a free report at loamly.ai/check.