The question we kept hearing

Over the past four months, we've run AI Visibility Audits on 400+ B2B brands. In almost every conversation after the audit, the same question comes up:

"How did you choose that prompt? What's your methodology?"

But there's a deeper question underneath: "How do you know which prompts matter? How does ChatGPT actually decide which brand to recommend?"

The honest answer was: we've been observing the patterns, but we haven't systematized them.

Until now.

We've spent the last six weeks analysing the 400 audit results we've collected and looking for patterns in which brands get recommended and why. The data is clear. LLMs use five decision patterns, and they're learnable.

Pattern 1: The "authority cluster" effect

When an AI model generates an answer about vendors in a category, it doesn't evaluate brands independently. It evaluates clusters.

Here's what we mean:

We asked ChatGPT, Claude, Perplexity, and Gemini the same question: "What's the best project management tool for distributed engineering teams?"

ChatGPT recommended: Linear, Jira, Asana, Monday.com, Notion (5 tools)

Claude recommended: Linear, Jira, Asana, Notion, Plane (5 tools)

Perplexity recommended: Linear, Asana, Jira, Coda, Monday.com (5 tools)

Google AI Overviews recommended: Asana, Monday.com, Jira, Linear (4 tools)

Notice: Linear, Asana, and Jira appear in almost all of them. These three form an "authority cluster" — the set of brands the models are trained to think of first.

Notion appears in 3 of 4. Monday.com appears in 3 of 4. They're in the secondary cluster.

Plane appears in 1 of 4. Coda appears in 1 of 4. They're in the "alternative" cluster.

Why?

Because across AI training data (Reddit, G2, industry blogs, news coverage, podcasts), these three names appear together most frequently. When people discuss project management tools, they discuss Linear, Jira, and Asana together so often that the models learn to associate them.

The implication: Getting into the authority cluster is not about being the "best" product. It's about being mentioned alongside the other authority players consistently.

If your brand is mentioned 100 times but always alone or with random other brands, you're not in the cluster. If a smaller brand is mentioned 20 times but always alongside the category leaders, they're in the cluster.

How do you break into the cluster? Be mentioned in the same articles, reviews, and discussions as the authority players.

• Request comparisons with the category leader ("us vs Linear")
• Get listed on multi-vendor comparison pages
• Participate in the same industry conversations as the leaders
• Get analyst reports that compare you to the leaders

• Show up in Reddit threads where the leaders are being discussed

   

Pattern 2: The "source credibility hierarchy"

Different sources carry different weight in an LLM's training data.

We analysed 100 audits and tracked: which sources most frequently led to a brand being mentioned in the AI-generated answers?

Here's the hierarchy we found (from highest influence to lowest):

Tier 1 (Highest influence):

• G2 reviews and ratings
• Capterra reviews and ratings
• Reddit discussions (especially r/webdev, r/productmanagement, category-specific subs)
• Major news outlets covering the vendor
• Analyst reports (Gartner, Forrester, etc.)

Tier 2 (Medium influence):

• Industry blogs and publications
• Podcast mentions
• YouTube videos and tutorials
• Twitter/X discussions (especially from credible accounts)
• Case studies and customer stories on third-party platforms

Tier 3 (Lower influence):

• The vendor's own website and blog
• Email marketing mentions
• Social media posts from the vendor
• Vendor-controlled press releases

Tier 4 (Lowest influence):

• Directory listings (capturetheworld.com, softwarebear.com, listicles)
• Paid reviews or sponsored content
• Mentions in comment sections

Why the hierarchy?

LLMs are trained to recognize credibility signals. A mention on G2 is credible because G2 is a third-party review platform with reputation on the line. A mention on your own website is self-promotional and weighted lower.

A Reddit comment is credible because it's peer-to-peer advice, unfiltered. An email marketing mention is filtered advertising.

The implication: If you want to influence how AI models describe your brand, focus on Tier 1 sources first.

Get on G2 and Capterra. Get mentioned on Reddit in authentic conversations (not spam). Aim for news coverage and analyst briefings. Podcast guest spots. Industry publication features.

One mention on G2 is worth more than 50 mentions on your own website.

Pattern 3: The "semantic consistency" filter

Here's where it gets interesting.

We audited a brand that had excellent coverage — 40+ mentions across G2, Reddit, industry blogs, and news articles.

But their AI Visibility Score was below average.

Why?

We read through the mentions. Here's what we found:

• On G2, they're described as "the most flexible project management solution"
• On Reddit, they're described as "good for startups that don't need complexity"
• On industry blogs, they're described as "the enterprise project management tool"
• On their own website, they're described as "the all-in-one collaboration platform"

Four completely different positioning messages.

When an LLM reads these 40 mentions, it doesn't know which one is the truth. So it doesn't confidently include them in recommendations. The inconsistency creates noise.

Compare that to a competitor with fewer mentions (only 20) but perfect consistency:

• Every source describes them the same way
• The positioning is unambiguous
• The LLM learns a clear, consistent description

That competitor's AI Visibility Score is higher despite fewer total mentions.

This is huge.

It means consistency of positioning across platforms matters more than the total volume of mentions.

The implication: Before you spend time chasing more press coverage or reviews, fix your positioning message across the platforms you're already on.

Audit every place your brand is mentioned in the past 6 months. Are you described the same way everywhere? If not, that's your first fix.

Go to G2. Go to your company website. Go to your LinkedIn. Go to industry articles about you. Make sure the one-sentence pitch is the same everywhere.

Pattern 4: The "competitive co-occurrence" signal

We looked at 50 brands that score high in AI Visibility. Almost all of them had one thing in common: they appear in content alongside their direct competitors.

This happens in a few ways:

• Comparison articles ("X vs Y vs Z")
• Multi-vendor review lists ("Best 5 tools for [use case]")
• G2, Capterra, and TrustRadius reviews (where you're implicitly compared)
• Analyst reports that benchmark multiple vendors
• Reddit threads asking "X or Y?"

Brands that appear in these "competitive comparison contexts" get a boost.

Why?

Because when an LLM is generating an answer about vendors in a category, it's learned from contexts where multiple vendors are discussed together. If your brand rarely appears in comparison contexts, the model doesn't learn to include you when comparing options.

We audited a brand that had 30 mentions across the web but almost none of them were in comparison contexts. Their score was 24/100.

We audited a competitor with 20 mentions, but 15 of them were in comparison articles and G2 reviews. Their score was 68/100.

The implication: Get into comparison content.

• Request to be added to comparison articles
• Ensure you're on G2, Capterra, TrustRadius (these are comparison engines)
• Participate in "tools I recommend" discussions on Reddit
• Get included in analyst reports that benchmark your space
• Aim for "best tools for X" roundup articles

Comparison content is where category learning happens for LLMs.

Pattern 5: The "recency boost"

The last pattern is the most time-sensitive.

LLMs have training cutoff dates. ChatGPT's knowledge cutoff is April 2024. Gemini's is April 2024. Claude's is early 2024.

But the training data isn't evenly distributed across time. Recent data (within the last 12 months of the cutoff) gets slightly more weight than older data.

This means: if you were recently mentioned in a major publication, podcast, or review platform, that mention carries more weight than a mention from 3 years ago.

We see this in the data: brands that have had recent press coverage, recent podcast appearances, or recent reviews get visibility boosts in the next generation of models.

The implication: Consistency + recency = visibility.

Don't do one big PR push and then disappear. Aim for consistent, ongoing mentions across the key platforms. Two mentions per quarter in high-credibility sources beats one big mention per year.

The meta pattern: Credibility compounds

If you zoom out, all five patterns point to one thing: credibility is cumulative.

The brands with the highest AI Visibility Scores aren't necessarily the ones with the most features or the best products. They're the ones who are:

1. Mentioned alongside category leaders (authority cluster effect)
2. Mentioned on credible third-party platforms (source hierarchy)
3. Described consistently across those platforms (semantic consistency)
4. Included in comparison conversations (competitive co-occurrence)
5. Mentioned recently and regularly (recency boost)

Each of these compounds. Do one, you see a small lift. Do three, you see a meaningful lift. Do all five, you become a category-defining brand in AI outputs.

The 90-day playbook: From invisible to visible

If your brand is currently invisible in AI search (scoring below 30/100), here's what to do:

Weeks 1–2: Get on the platform.
If you're not on G2 and Capterra, that's your baseline. Do it this week. Niche review platforms in your category matter too.

Weeks 2–4: Ensure positioning consistency.
Go to G2, your website, your LinkedIn, and the last three mentions of your brand on Google. Are they saying the same thing about you? If not, align them.

Weeks 3–8: Get into comparison contexts.
Request to be added to comparison articles in your space. Participate in relevant Reddit communities. Participate in analyst processes. Aim for 2–3 "you mentioned alongside the leader" moments.

Weeks 5–12: Drive regular mentions.
Podcast guest spots, industry publication features, G2 case studies, thought leadership content. Aim for one mention per platform per month.

By week 12, if you've done this right, your AI Visibility Score should move 15–30 points.

The unfair advantage

Here's what's wild: most of your competitors don't understand any of this yet.

They're still chasing Google rankings while ignoring the fact that ChatGPT is already your second-biggest discovery channel for research-stage buyers.

They're not measuring it. They're not optimizing for it. They're not even aware it's happening.

But the brands that do understand this pattern — the ones that optimize for these five signals — are seeing outsized visibility in the models that are defining how buyers discover vendors in 2026.

The window for a competitive advantage is open right now.

The brands that move first have a two-year head start before everyone else wakes up.