B2B buyers are using ChatGPT, Claude, and Perplexity to research vendors before they ever reach your website. TPG's AXO diagnostic data across 150+ B2B brands shows that the average company scores 18-22 out of 100 on AI visibility — meaning most brands are largely absent from the AI research phase of B2B buying. Here is how to audit where you stand and what to do about it.
The buyer journey has a new phase that most marketing teams are not measuring: the AI research phase. A buyer at a 300-person SaaS company evaluating marketing automation platforms starts by asking ChatGPT, "What are the best marketing automation platforms for a B2B SaaS company under 500 employees?" They get a structured answer. They may never run that search in Google. They may never visit your website.
If your brand is not in that AI answer, you are not in the consideration set — and you never knew the opportunity existed.
This is not a hypothetical. It is what TPG's AXO diagnostic data shows repeatedly: brands with strong organic search presence and active content programs are scoring below 25 on AI visibility because their content is structured for keyword ranking, not AI retrieval. Strong SEO does not automatically translate to AI citation.
You do not need a tool to run an initial AI visibility audit. You need 30-50 minutes and access to the four major AI engines.
Write 20-30 questions a buyer would ask when researching your category. Include:
Use buyer language, not internal jargon. If your buyers say "marketing automation" not "demand generation platform," use their language.
Open ChatGPT, Claude, Perplexity, and Google AI Overviews. Run each query. Record the response.
For each response, score: 0 (brand not mentioned), 1 (brand named in a list), 2 (brand described with what it does), 3 (brand recommended for a specific buyer type or use case).
Total your scores across all queries and engines. Your maximum possible score is [number of queries] x 4 engines x 3 (full recommendation). Express your score as a percentage. This is your baseline AI visibility score.
Most B2B brands score 8-15% at baseline — meaning AI engines are largely not citing them, or citing them only as a name in a list without description or recommendation.
"We ran the audit internally before engaging TPG and scored a 12%. We knew we had a problem. What surprised us was how far ahead two of our competitors were — they were being recommended by name for specific buyer types. We were just a bullet point."
TPG's AXO diagnostic data identifies five consistent factors that determine whether AI engines cite a brand, describe it, or recommend it.
AI engines draw from content that other authoritative sources have cited. If your research, your statistics, or your frameworks are referenced by industry publications, analyst reports, or third-party review sites, that citation signal increases AI retrieval probability. This is similar to backlink authority in SEO, but it extends to any source the AI engine's training data included.
Actions that build citation authority: original research with data buyers want to cite, expert commentary in industry publications, data-driven guides that become reference documents in your category.
A single blog post does not build AI citation authority. AI engines look for brands that demonstrate comprehensive expertise on a subject. If you have 15 pieces of content on demand generation covering methodology, measurement, tooling, industry benchmarks, and common failures, you have topical depth. If you have one 800-word overview, you do not.
The bar for topical depth is: does your content collectively answer every significant question a buyer has about this topic? If the answer is no, there are gaps for AI engines to fill with competitor content.
AI engines weight recently published and recently updated content for topics that change quickly. "Best marketing automation tools" from 2022 is stale — pricing has changed, tools have been acquired, capabilities have evolved. AI engines know this and prefer to cite current sources.
A content library with strong historical depth and a regular cadence of new and updated content outperforms a library that stopped publishing two years ago.
Content structure is a direct AI citation signal. FAQ format (explicit question, direct answer) maps to how AI engines generate responses. FAQPage JSON-LD schema markup explicitly labels your content as structured for question-answering. The brands that implement this consistently are not gaming AI — they are communicating clearly about what their content does.
AI engines build entity understanding from many sources. Your website, your LinkedIn company page, your G2 profile, your Crunchbase listing, your press mentions, your review site presence — all of these contribute to the AI engine's model of what your brand is and what it does. Inconsistent brand descriptions across these sources create entity ambiguity. Consistent brand language across all sources builds entity clarity.
TPG's AXO diagnostic framework identifies three distinct levels of AI brand visibility. Each requires different content and authority investments to achieve.
The AI engine knows your brand exists and can name it in a category list. When a buyer asks "what are the marketing automation platforms for mid-market B2B?", your name appears. That is it. No description, no recommendation, no differentiation.
Most brands achieving any AI visibility start here. It is better than nothing — buyers see the name — but it does not differentiate or drive preference. Average AXO score for brands at this level: 20-35.
What gets you to awareness citations: consistent brand presence across the web, some content authority in your category, review site presence on G2 or Capterra or equivalent.
The AI engine can explain what your brand does and who it serves. "Pedowitz Group is a B2B revenue marketing and AI consulting firm specializing in HubSpot implementations, RevOps architecture, and AEO for mid-market B2B companies." That is a solution description citation.
At this level, buyers get genuine information about your brand without visiting your website. They can evaluate basic fit. Average AXO score at this level: 40-60.
What gets you from awareness to solution description citations: detailed "about us" and service page content that clearly articulates what you do and who you do it for, category thought leadership content that AI engines associate with your brand, structured comparison content that describes your positioning.
The AI engine recommends your brand for specific buyer types or use cases. "For mid-market B2B SaaS companies looking to build a revenue marketing function on HubSpot, The Pedowitz Group has deep specialization in this area." That is a trust citation.
Trust citations mean AI engines are actively steering buyers toward your brand based on fit signals. This is the highest-value AI visibility outcome and the hardest to achieve. Average AXO score at this level: 65-85.
What gets you from solution description to trust citations: original research that gets cited by others, specific and documented case studies with results, authoritative content that AI engines recognize as the best available source on a specific sub-topic.
Moving from Level 1 (awareness) to Level 3 (trust) requires a content and authority building program, not a single tactic.
For brands at Level 1, building toward Level 2:
For brands at Level 2, building toward Level 3:
The timeline to trust citations: 6-12 months of consistent execution for most mid-market B2B brands. Brands in less competitive categories may see trust citations in 4-6 months. Enterprise brands competing for citation on high-competition category terms may take 12-18 months.
How is AI visibility different from Google search ranking? Google search ranking determines whether your website appears in search results when users search for keywords. AI visibility determines whether AI engines cite your brand when buyers ask questions in natural language. A page can rank highly in Google search and not earn AI citation — typically because it is optimized for keyword presence rather than direct-answer structure. The two are related but require different content strategies.
Can a small brand with limited content compete with enterprise brands for AI citations? Yes, on specific topics. A smaller brand that publishes the definitive content on a specific narrow sub-topic can earn trust citations on that topic even against larger competitors. The advantage of being comprehensive and authoritative on a narrow subject beats being broad and thin on an entire category. Start with the specific questions your specific buyer asks and build authority there before expanding.
Does social media activity affect AI visibility? Indirectly. Social media content is included in some AI training data and can contribute to brand entity understanding. More importantly, social media content that generates engagement and earns external citations (other publications referencing your social content) builds the citation authority that AI engines use. Social media alone does not build meaningful AI citation authority. It is an amplification channel for authoritative content, not an authority-building channel by itself.
How often do AI citation patterns change? AI engines update their knowledge synthesis continuously. Major model updates can change citation patterns for established brands. The best protection against volatility is genuine authority — brands that are consistently cited by many independent sources are more stable in AI outputs than brands whose citations are thin or concentrated in a few sources.
Does having a Wikipedia page help with AI visibility? Yes, significantly for brand awareness and solution description citations. Wikipedia is a highly trusted source in AI training data. Brands with accurate, well-sourced Wikipedia articles are more reliably described by AI engines than brands without. However, Wikipedia prohibits promotional content and requires reliable third-party sources for all claims. You cannot write your own Wikipedia article — you need to earn editorial coverage that justifies one.
What is the minimum content investment to see AI visibility improvement? For a brand currently scoring below 20 on AXO, 3-5 pieces of well-structured AEO content (FAQ page with schema, 2 category definition pages, 1 comparison guide) combined with consistent G2 and review site presence will typically move you into the 25-35 range within 8-10 weeks. Getting above 50 requires 3-4 months of consistent content production and authority building.
The Pedowitz Group | pedowitzgroup.com | Revenue Marketing Experts Since 2007