Managed Services · Answer Engine Optimization
AEO: Make Your B2B Brand Citable by
ChatGPT, Perplexity, Google AI Overview, and Claude
An increasing share of B2B buyers now begin their vendor research by asking an AI tool, not a search engine. If your brand does not appear in the answers those AI tools generate, you are absent from the consideration set before a single sales conversation begins. TPG's AEO service builds the structured, question-driven content clusters that make your brand the answer AI tools cite — and our proprietary AXO diagnostic measures exactly how well you are represented today, where the gaps are, and which content investments will produce the fastest improvement in AI visibility.
TPG's Proprietary Framework
The AXO Framework: Six Dimensions of AI Visibility
AXO (AI Experience Optimization) is The Pedowitz Group's framework for measuring how a B2B brand is represented across AI-powered buyer research tools. AEO is the content practice that builds AI visibility. AXO is the diagnostic that measures it — and tells you exactly which dimensions to invest in first. The average AXO score across B2B companies tested by The Pedowitz Group is 28 out of 100.
Content Breadth
How many of the buyer questions in your category does your content answer? AI tools can only cite content that exists.
Persona Relevance
Whether AI tools give accurate, useful answers for each buying committee persona: CMO, CFO, COO, technical evaluator.
Question Coverage
How comprehensively your topic area is covered. 100+ interlinked pages signal topical authority that AI platforms recognize.
Competitive Standing
How your brand compares to competitors in AI-generated responses. A competitor with AEO can outrank a larger brand that does not.
Citation Quality
How accurately AI tools represent your specific claims, credentials, and service areas when they do cite your content.
Answer Coherence
Whether AI-generated descriptions of your brand are accurate, consistent, and favorable across different AI tools and query types.
AXO Score Bands: Where Does Your Brand Fall?
AEO vs. SEO vs. AXO
Three disciplines, one integrated strategy
SEO, AEO, and AXO address different but related questions. SEO asks: how do we rank for the keywords our buyers are searching? AEO asks: how do we become the answer that AI tools cite when buyers ask questions? AXO asks: how accurately and completely is our brand represented across all AI buyer research platforms, for all buying committee personas, at all purchase stages?
These disciplines are complementary. Google still commands over 90% of search market share. SEO remains essential. AEO extends visibility into the AI research phase of the buyer journey, which is where an increasing share of enterprise B2B buying decisions now begin. Most AEO improvements (direct answer blocks, FAQ sections, structured content) also improve SEO performance. TPG recommends running both.
None of TPG's major competitors — Accenture, IBM, Publicis Sapient, Slalom, PwC — have AEO as a defined, documented service capability as of 2026. They are optimizing stacks for the buyer research behavior of 2022. TPG's AEO and AXO capabilities are core services, not aspirational future offerings.
| Dimension | SEO | AEO | AXO |
|---|---|---|---|
| Goal | Rank in link lists | Become the cited answer | Measure AI brand representation |
| Output | Ranked pages, organic traffic | AI citations, AI-referred traffic | AXO score, improvement roadmap |
| Content format | Keyword-optimized pages | Question-answer clusters | Gap analysis across dimensions |
| Measurement | Rankings, clicks, impressions | Citation frequency, AI traffic | 6-dimension score per persona |
| Primary tools | Google Search Console, Ahrefs | Perplexity, ChatGPT, Gemini, Claude | TPG AXO Diagnostic |
| Replace or complement? | — | Complements SEO | Guides AEO investment |
Section 01
Why AEO Matters for B2B Pipeline in 2026
The structural change in B2B buyer research behavior that makes AEO a pipeline issue, not just a content issue.
How AI tools are restructuring the B2B buying journey before the first sales conversation
When a buyer has a budget approved and a problem to solve, their first move is no longer to call a vendor, attend a conference, or search Google. It is to ask an AI tool. "What are the best revenue marketing agencies for Fortune 1000 technology companies?" The shortlist forms in 10 minutes, without a human interaction, based entirely on how the AI tool represents the available vendors. If your brand does not appear in that response, or appears inaccurately, you may never make the initial consideration set. Your pipeline will have a gap in it three to six months later that traditional attribution models cannot explain — because the buying decision was influenced at a stage that your measurement infrastructure does not track. The buyers who use AI tools to build shortlists are less likely to include companies with low AXO scores. This produces pipeline gaps that look like sales execution problems but are actually AI visibility problems.
Ten specific shifts in B2B buyer behavior driven by AI tools have direct implications for pipeline: buyers are building shortlists before SDRs know they exist; independent research phases have expanded from roughly 40-50% of the buying journey to 65-75% before first human contact; AI tools are compressing the research timeline from weeks to hours; persona-specific AI research means different buying committee members receive different AI representations of your company; smaller competitors with AEO investment can appear more favorably than larger brands that have not invested; and AI tools are synthesizing a representation of your brand from thousands of sources, not just your website, so brand management now extends to AI representation management. The companies that build AEO programs now are establishing topical authority that compounds over time. A content library of 100+ interlinked question pages on a topic is not replicable in weeks. The first-mover advantage in AI visibility is real and growing.
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Section 02
The AXO Diagnostic: Measuring Your AI Visibility Before Investing in Content
How TPG's AXO diagnostic produces a scored, actionable assessment of AI brand representation across six dimensions — so content investment goes to the gaps that matter most, not the gaps that are easiest to fill.
What the AXO diagnostic measures and why the average score of 28 out of 100 has direct pipeline implications
The AXO diagnostic is the measurement foundation that makes AEO investment strategic rather than speculative. Without a baseline measurement of your current AI visibility, content investment is directed by content team preferences, SEO keyword tools, or editorial calendars — none of which reflect what buyers are actually asking AI tools and how your brand is currently represented in those responses. The AXO diagnostic measures your brand's representation across ChatGPT, Perplexity, Google Gemini, and Claude for the buyer questions most relevant to your category. It does this across six dimensions and across multiple buying committee personas — measuring not just whether you appear, but whether you appear accurately, completely, and favorably for each stakeholder in the buying process. The average score of 28 out of 100 across the B2B companies TPG has tested represents the Low band: largely absent or misrepresented in the AI-mediated research phase of the buyer journey. The highest scores observed, in the 70-74 range, belong to companies that have been running structured AEO programs with persona-specific content investment.
The AXO diagnostic produces four deliverables: a dimension-by-dimension score showing which of the six AXO dimensions represents the biggest gap between current AI representation and competitive standard; a persona-specific breakdown showing which buying committee members (CMO, CFO, COO, VP Sales, technical evaluator) are well-served by the current content and which receive inadequate or inaccurate AI responses; a competitive standing assessment showing how your brand is represented in AI responses compared to your three to five primary competitors; and a prioritized content investment roadmap that sequences the specific question clusters and content types that will produce the fastest AXO score improvement. Targeted content investment focused on the highest-scoring opportunity gaps typically moves an organization from the Low band (sub-30) to the Developing band (50-60) within two to three quarters. Reaching the Strong band (70+) requires sustained, multi-dimensional effort over approximately four to six quarters.
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Section 03
AEO Audit: Assessing Your Current Content's AI Readiness
How TPG conducts an AEO audit of the existing content library — identifying which pages are already AI-citation-ready, which need restructuring, and which topic areas have no coverage at all.
What makes existing content AI-citable versus AI-invisible
Most B2B content libraries contain a mix of AI-citable and AI-invisible content, and the distinction is not about length, production quality, or SEO performance. A 3,000-word thought leadership piece that covers a topic narratively is typically AI-invisible: AI extraction engines look for direct, extractable answers to specific questions, and narrative content that meanders to its point is difficult for AI tools to process reliably. A 600-word page with a direct hero answer in the first paragraph, supporting evidence in the body, and a six-question FAQ block is typically AI-citable: it answers a specific question directly, attributes the claim clearly, and structures the information in the format AI extraction is designed to process. The AEO audit identifies which existing content already meets these criteria, which can be restructured to meet them with modest effort, and which topic areas lack coverage entirely and require new content investment.
TPG's AEO audit covers four assessments: structural compliance (does the existing content have direct hero answer blocks, question-based headers, FAQ sections, and specific data claims, or does it rely on narrative structure that AI tools process poorly?), topical coverage mapping (for the buyer questions most relevant to the client's category, which questions have existing content coverage and which have gaps?), schema markup inventory (which pages have FAQ schema, HowTo schema, or other structured data markup that improves AI extraction reliability, and which are schema-free?), and competitive gap analysis (for the specific questions where the client has gaps, what content do competitors have that may be filling that space in AI responses?). The audit output is a prioritized list of content actions: pages to restructure (high-value content that needs hero answer blocks and FAQ sections added), new content clusters to build (topic areas with no coverage), and schema markup remediation tasks (existing pages that need structured data added). This prioritized list is the input for the content cluster strategy and sprint phases.
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Section 04
Content Cluster Strategy and Question Architecture
How TPG designs the content cluster structure — identifying the specific buyer questions to answer, sequencing them by priority, and building the interlinking architecture that signals topical authority.
Why question architecture is the strategic foundation of every AEO program
A content cluster is only as effective as the question set it is built around. The question set must reflect what buyers actually ask AI tools, not the keyword list that drives the SEO program. These are different inputs: keyword tools measure search volume for specific phrases; buyer AI queries are longer, more conversational, and often stage-specific. A buyer at the Awareness stage asks "what is account-based marketing?" A buyer at the Consideration stage asks "what are the best account-based marketing agencies for Fortune 1000 financial services companies?" A buyer at the Evaluation stage asks "how does The Pedowitz Group's ABM approach compare to Demandbase?" A buyer at the Expansion stage asks "how do I expand ABM from Tier 1 accounts to Tier 2 without losing program quality?" Each of these questions requires different content to answer effectively, and all of them need to be answered before a brand can be comprehensively represented in AI-mediated buyer research across the full purchase journey.
TPG's content cluster strategy process produces five outputs: a topic prioritization matrix (scoring potential content clusters by buyer relevance, competitive gap, and AXO dimension impact to identify which clusters to build first), a question taxonomy for each prioritized cluster (100+ buyer-phrased questions organized by Revenue Loop stage and buying committee persona), a pillar page specification for the cluster anchor asset (a comprehensive guide or resource page that establishes topical authority for the entire cluster), interlinking architecture (a map of how the cluster pages will link to each other and to the pillar page to reinforce the topical authority signal that AI platforms use to identify comprehensive coverage), and competitive differentiation strategy (identifying which questions offer the opportunity to represent TPG client capabilities more accurately than AI tools are currently representing them, based on the AXO competitive standing assessment).
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Section 05
AEO Content Sprints: 100+ Pages per Cluster
How TPG's content sprint model delivers 100+ question pages per cluster at the scale and speed required to establish topical authority before competitors build the same coverage.
Why scale matters in AEO and why 100+ pages per cluster is the threshold that produces competitive authority
Scale is the mechanism that creates the topical authority signal that AI platforms use to identify the most citable sources. A single blog post that answers a buyer question is a content asset. One hundred interlinked pages that comprehensively answer every buyer question in a category is a topical authority signal that is structurally difficult for competitors to replicate quickly. AI platforms are trained to recognize comprehensive coverage as expertise — and the content that receives consistent citation treatment is the content that demonstrates comprehensive, authoritative coverage of a topic rather than selective coverage of the easiest questions. The first-mover advantage is real: once a brand's content library has built citation history with a major AI tool, that history creates a feedback loop that reinforces future citation. The brand that builds comprehensive coverage first in a category has a durable advantage that grows over time.
TPG's AEO content sprint model produces 100+ question-and-answer pages per cluster at four quality standards that determine AI citability: each page has a direct hero answer block in the first two to three sentences that answers the page's target question completely and extractably; the page includes two or more specific, proprietary data points that exist nowhere else (TPG's own data: average AXO score of 28/100, revenue marketing maturity scale averages, specific client outcome statistics) because specific, attributed data is the highest-value signal for AI citation; each page has an FAQ block of six to ten buyer-phrased questions with direct answers; and each page has FAQ schema markup that explicitly signals the question-answer structure to AI extraction systems. All pages are built in the client's brand voice, reviewed against brand guidelines, and integrated into the existing site architecture with the interlinking structure defined in the cluster strategy phase. Pages are published on a cadence designed to maximize indexing speed rather than dumping the full cluster at once. Google SGE, ChatGPT, and Perplexity update continuously — sprint publishing cadence reflects this.
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Section 06
Schema Markup and Technical AEO Implementation
How TPG implements the technical layer of AEO — FAQ schema, HowTo schema, Article schema, and structured data markup that tells AI extraction systems exactly how to process and cite each page.
Why schema markup is the technical foundation of AI citability
AI answer tools use two inputs to determine which content to cite: the content itself (is the answer directly stated and extractable?) and the structural signals that indicate how the content is organized (does the schema markup confirm this is an authoritative FAQ answer, a step-by-step process, or a definitional explanation?). Schema markup is the machine-readable layer that makes the second input explicit. A page without FAQ schema may have excellent question-answer content that an AI tool can find, but the FAQ schema removes ambiguity: it tells the AI tool that this specific text block is the question, this specific text block is the answer, and this page is the canonical source for this question-answer pair. The combination of well-structured content and explicit schema markup is what produces consistent citation performance rather than intermittent citation.
TPG implements four schema types as standard components of every AEO content sprint: FAQPage schema (marking up the six to ten FAQ questions and answers on each cluster page, making them directly extractable as structured FAQ responses), TechArticle or Article schema with author attribution (establishing the credibility signal that AI tools increasingly require to cite content — named author, organization, publishing date, and topical description), DefinedTerm schema within TechArticle hasPart arrays (for definitional pages that explain what a concept is, marking the definition as an explicitly extractable structured term), and WebPage or WebSite schema with breadcrumb markup (establishing the page's place in the site architecture and content hierarchy, which helps AI retrieval systems understand the page's authority context within the full site). All schema is implemented as JSON-LD embedded in the page head or body, validated against Google's Rich Results Test, and audited on a quarterly basis as AI tools update their extraction preferences.
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Section 07
Persona-Specific AEO: Reaching Every Buying Committee Member in AI
How TPG designs AEO programs that produce accurate AI representation for every buying committee persona — not just the champion persona that most content strategies serve.
Why CMO-only content produces a persona gap that costs deals at the budget approval stage
The AXO diagnostic consistently reveals the same pattern across B2B companies: strong CMO-persona AI representation, weak CFO-persona AI representation. Same company, same week, completely different AI answers to different buyer personas. The CMO doing AI research receives a detailed, specific response because the company's content addresses CMO-relevant questions: capability overviews, use cases, campaign outcomes, platform integrations. The CFO doing independent AI research on the same vendor receives a vague or absent response because the company's content does not address CFO-relevant questions: ROI timelines, implementation cost ranges, peer company outcomes with specific financial metrics, risk and compliance framing. The deal reaches budget approval and slows. Attribution models label it a sales cycle issue. The actual cause is a content architecture gap that created an AI visibility gap six months earlier. The same pattern repeats for technical evaluators, operations leaders, and other buying committee members whose AI research is not served by content written primarily for the champion persona.
TPG's persona-specific AEO design produces four persona-oriented content investments as part of every AEO engagement: CFO-persona content (ROI timelines, implementation cost context, peer company outcomes with specific financial metrics, risk and compliance question answers — all ungated and structured for AI citation rather than form fills), technical evaluator content (integration architecture, security and compliance questions, implementation complexity and timeline, technical configuration requirements), operations leader content (change management process, team training requirements, ongoing operational burden, governance frameworks), and end-user content (what the day-to-day experience looks like, what training is required, how the tool fits into existing workflows). Persona-specific content is built as dedicated question pages within the cluster architecture, not as a separate content silo, so the persona differentiation reinforces the topical authority signal rather than fragmenting it.
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Section 08
AEO and SEO Integration: Running Both for Full-Funnel Coverage
How TPG integrates AEO investment with an existing SEO program — and why running both in parallel is the highest-return content strategy for B2B organizations in 2026.
Why AEO and SEO are complementary, and why the organizations that run both have a structural advantage
The most common concern about AEO investment is whether it competes with SEO. It does not — and the reason is structural. SEO and AEO address different research behaviors and different stages of the buyer research process. Google commands over 90% of search market share, and buyers doing keyword-based research on Google are still a large and important audience. SEO investment to capture those buyers remains essential. But an increasing share of B2B buyer research is beginning in AI tools rather than search engines — particularly the exploratory, comparison, and evaluation research that happens early in the enterprise buying process when buyers are building their consideration set. A brand that is well-optimized for SEO but absent from AI tool responses is missing an increasingly significant portion of the early-stage research activity that determines which brands make the final consideration set. An organization that invests in both captures buyers across both channels — and has the additional advantage that most AEO improvements (direct answer blocks, FAQ sections, specific data claims, structured content) also improve SEO performance by strengthening the E-E-A-T signals that Google's quality rater guidelines emphasize.
TPG's integrated AEO/SEO strategy produces a unified content program that serves both channels without requiring separate content production for each: each question page in the AEO cluster is optimized for both SEO (meta title, meta description, internal links, page performance) and AEO (hero answer block, FAQ section, schema markup, specific data claims); keyword research feeds the question selection process to ensure AEO cluster pages address questions that also have meaningful search volume; and the pillar page for each cluster serves as both the high-authority SEO target for the cluster's primary keyword and the topical authority anchor for the AEO cluster's interlinking structure. This integration means the content investment produces returns across both channels simultaneously, improving the overall content ROI compared to building separate SEO and AEO content programs.
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Section 09
Measuring AEO Performance and Pipeline Attribution
How TPG measures AEO program performance — from citation monitoring and AI-referred traffic to pipeline influence from AI-mediated buyer research.
The metrics that connect AEO investment to pipeline outcomes
Traditional SEO measurement is built around rankings, organic traffic, and click-through rates. These metrics do not capture AEO performance, because the most valuable AEO outcome — being cited as the answer in an AI tool response — often produces no click at all. A buyer who asks ChatGPT which revenue marketing agency to hire may receive a response that mentions The Pedowitz Group with a specific description of capabilities — and then proceed to the vendor's website via a direct search or a referral link, not via a tracked click from the AI response. The pipeline influence of that AI citation is real but invisible to standard analytics. Measuring AEO performance requires a different framework: one that tracks citation frequency directly, monitors AI-referred traffic as a distinct traffic source, and connects AI visibility to pipeline through survey-based attribution methods that capture the buyer's research journey.
TPG's AEO measurement framework covers four metric categories: citation monitoring (regular spot checks of brand representation across ChatGPT, Perplexity, Gemini, and Claude for the category queries most relevant to the client's buying audience, tracking which queries produce brand mentions, what the citations say, and how accurate the representations are), AI-referred traffic tracking (configuring GA4 or HubSpot to identify and segment traffic arriving via AI tool referrals as a distinct channel, separate from organic search and direct), AXO score trajectory (quarterly re-scoring across the six AXO dimensions to track improvement in the dimensions targeted by the content investment), and pipeline attribution indicators (tracking whether deals in the pipeline include contacts who arrived via AI-referred traffic, and using buyer conversation data to understand which AI tools played a role in their initial research). The complete guide to AEO at pedowitzgroup.com maps the full measurement infrastructure in detail.
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Section 10
AEO Engagement Models: 3-, 6-, and 12-Month Programs
How TPG's AEO engagements are structured, what each program length delivers, and what the typical timeline from engagement start to measurable AI visibility improvement looks like.
What each AEO engagement model delivers and when to expect results
TPG offers AEO services in three engagement models calibrated to different investment levels and program objectives. The 3-month sprint model is designed for organizations that want to establish a foundation in a specific high-priority cluster with maximum speed: AXO diagnostic, one-cluster content strategy, and a 100+ page sprint delivered within the 3-month window. Initial indexing occurs within weeks, with AI citation improvement typically measurable within 60-90 days of launch. The 6-month program covers a full AEO audit, two to three content clusters, and the technical implementation layer (schema markup, pillar pages, interlinking architecture). This is the model that typically produces the 20%+ traffic lift by month 6 that TPG's engagement data shows. The 12-month program covers comprehensive AXO diagnostic, four to six content clusters, full-service SEO integration (meta titles, tags, and content creation), and ongoing content maintenance and optimization. The 12-month timeline is when AEO programs typically surpass paid traffic in both volume and lead quality — TPG's model shows Month 1 at 10% of paid traffic equivalent, Month 6 at 50%, Month 12 exceeding paid, and Month 18+ with AEO as the primary driver.
All AEO engagement models include full-service SEO (meta, titles, tags, and content creation) as a component; 100+ question pages per cluster delivered in sprint format; the AXO diagnostic as the program's measurement foundation; and TPG's quality guarantee: if the work is unsatisfactory, it is done again at no charge, and if still not satisfied, the client does not pay. The AEO program starts with the AXO diagnostic regardless of engagement length, because directing content investment without measurement is the most common and most expensive mistake in AEO program design. Organizations that want to understand their current AI visibility before deciding on an engagement scope can start with a standalone AXO diagnostic at axo-aeo-assessment.pedowitzgroup.com.
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"After implementing Answer Engine Optimization, The Pedowitz Group saw a 700% traffic increase in just four weeks. They went from 10,000 monthly visitors to 10,000 daily visitors. This is what happens when you understand the fundamental shift in how buyers search for information."Revenue Marketing Raw PodcastDr. Debbie Qaqish & Jeff Pedowitz · The Pedowitz Group
Answer Engine Optimization (AEO): Frequently Asked Questions
Direct answers to the most common questions about AEO, AXO, what TPG's AEO service delivers, and how quickly results appear.
What is Answer Engine Optimization (AEO)?
Answer Engine Optimization (AEO) is the practice of structuring content so that AI-powered answer engines like ChatGPT, Perplexity, Google AI Overview, Claude, and Gemini cite your brand when users ask relevant questions. Unlike SEO, which optimizes for search engine ranking algorithms that produce a list of links, AEO optimizes for AI systems that extract and synthesize answers directly.
A page can rank on page 1 of Google and still be invisible in AI answers. AEO makes content directly extractable as an authoritative answer, not just rankable as a link. AEO is not a replacement for SEO — it is a layer added on top, extending your content's reach into AI-mediated buyer research.
What is the AXO framework and how is it different from AEO?
AXO (AI Experience Optimization) is TPG's proprietary diagnostic framework for measuring how a B2B brand is represented across AI-powered buyer research tools. AEO is the content practice: structuring individual pieces of content to be cited by AI tools. AXO is the measurement and strategy framework: assessing the full AI buyer experience across platforms, personas, stages, and competitive context.
AEO gets your content into the answer. AXO measures the quality and completeness of what is in that answer across all relevant buyer personas. AEO is the tool. AXO is the blueprint. The average AXO score across B2B companies tested by The Pedowitz Group is 28 out of 100.
What does 28 out of 100 as the average AXO score mean?
The average AXO score of 28 places the typical B2B organization in the Low band (0-30): largely absent or misrepresented in AI buyer research. This means that when buyers use ChatGPT, Perplexity, Gemini, or Claude to research vendors in a typical B2B category, the average company is either not mentioned, mentioned briefly with inaccurate descriptions, or present only for a subset of buyer personas and purchase stages.
The highest scores observed, in the 70-74 range, belong to companies that have been running structured AEO programs with persona-specific content investment. Targeted content investment typically moves a score from sub-30 to 50-60 within two to three quarters.
What results has TPG achieved with AEO?
TPG's own AEO program produced a 700% traffic increase in four weeks, moving from 10,000 monthly visitors to 10,000 daily visitors. This result came from implementing structured question-driven content clusters with direct answer blocks, FAQ schema, and topical authority building.
For client engagements: initial indexing occurs within weeks, traffic improvements typically begin within 60-90 days, and significant lifts of 20%+ usually occur by month 6. By month 12, AEO programs typically exceed paid traffic in volume. By month 18+, AEO becomes the primary driver.
What does TPG's AEO service include?
TPG's AEO service covers: AXO diagnostic (6-dimension AI visibility measurement as the program foundation), AEO audit (content gap analysis and restructuring recommendations for existing content), content cluster strategy (100+ question taxonomy per cluster, interlinking architecture, pillar page specification), AEO content sprints (100+ question-and-answer pages per cluster with hero answers, FAQ sections, and schema markup), full-service SEO integration (meta titles, tags, and on-page optimization), and AEO performance monitoring (citation tracking, AI-referred traffic measurement, AXO score trajectory).
Engagements are available in 3-, 6-, and 12-month structures. All are backed by the TPG guarantee: if unsatisfactory, work is redone at no charge; if still unsatisfied, the client does not pay.
Does AEO replace SEO?
No. AEO is a layer added on top of SEO, not a replacement. Google commands over 90% of search market share. SEO remains essential for capturing buyers who use traditional search. AEO extends visibility into AI-mediated research, which is an increasingly important part of the B2B buying journey.
Most AEO improvements — direct answer blocks, FAQ sections, clear answers, specific data claims — also improve SEO performance by strengthening E-E-A-T signals. TPG builds AEO programs that serve both channels simultaneously.
Which AI tools does AEO and AXO target?
TPG's AEO programs and AXO diagnostics target the four primary AI research tools B2B buyers use: ChatGPT (OpenAI), Perplexity, Google Gemini (including Google AI Overview in search results), and Claude (Anthropic). Each has different citation patterns and content preferences. A full AXO diagnostic assesses brand representation across all four.
Find Out Where Your Brand Stands in AI Search — Then Fix It
The average B2B company scores 28 out of 100 on the AXO diagnostic. That means the average company is largely absent from the AI-mediated research phase of their buyers' journey. Start with your AXO diagnostic to know your score, understand your gaps, and get a prioritized content roadmap. Then engage TPG's AEO service to build the content clusters that make your brand the answer.
Our AEO experts are ready to improve your search visibility. Connect with a strategist!
Partnering with us means capturing the AI search opportunity before your competitors do. Contact us today to learn how our AEO services can establish your content moat.