How to Audit Your Current AI Search Performance: The Simaia Framework for B2B Companies

How to Audit Your Current AI Search Performance: The Simaia Framework for B2B CompaniesThe next generation of B2B buyers isn't starting their supplier search on Google. They're asking ChatGPT, Claude, Perplexity, and Gemini to recommend vendors, compare solutions, and shortlist manufacturers. If your company isn't visible in these AI-driven search results, you're already invisible to high-intent buyers actively seeking your products.

Traditional SEO won't save you here. AI assistants don't crawl websites the same way search engines do. They prioritize authoritative, structured, and citable content that demonstrates expertise. This shift demands a new discipline: generative engine optimization (GEO), the practice of ensuring your brand appears in AI-generated responses.

The problem? Most B2B companies have no idea how they're currently performing in AI search. Without a baseline audit, you're flying blind. This guide introduces the Simaia Framework, a systematic approach to auditing your AI search visibility and identifying the gaps that are costing you leads.

TLDR

• AI search is replacing traditional discovery: Buyers use ChatGPT, Perplexity, and Claude to find B2B suppliers, making AI search visibility critical for lead generation.

• The Simaia Framework audits five key areas: AI visibility baseline, content citability, technical discoverability, competitive positioning, and keyword coverage.

• Most B2B companies score poorly: Common issues include zero mentions in AI responses, non-citable content formats, and weak E-E-A-T signals.

• Quick wins exist: Structured data markup, expert-backed claims, and AI-native content formats can improve ai search optimization within weeks.

• Measurement matters: Track mention rates, Share of Voice (SOV), and citation frequency across multiple AI platforms to benchmark progress.

Why Traditional SEO Metrics Don't Measure AI Search Performance

Google Analytics shows your organic traffic. Ahrefs tracks your backlink profile. SEMrush monitors your keyword rankings. None of these tools tell you whether ChatGPT recommends your company when a buyer asks, "Who are the top CNC machining suppliers in Asia?"

AI assistants synthesize information differently than search engines. They don't just index pages; they evaluate content for trustworthiness, expertise, and citability. A high Domain Authority doesn't guarantee visibility in AI responses. Your content needs to be structured, authoritative, and directly answerable to conversational queries.

According to research from Princeton University and Georgia Tech, AI search engines prioritize content with clear expertise signals, including author credentials, data citations, and specific, factual claims. Generic marketing copy and keyword-stuffed blog posts get ignored.

This is why B2B manufacturers and suppliers who dominated Google search are now invisible in AI-driven discovery. The ranking factors have fundamentally changed.

The Simaia Framework: Five Pillars of AI Search Auditing

Pillar 1: AI Visibility Baseline

What to measure: Does your company appear when AI assistants answer buyer queries in your category?

How to audit:

• Identify 20-30 high-intent queries your ideal customers would ask (e.g., "industrial valve suppliers in Hong Kong," "custom metal fabrication for automotive parts")

• Query ChatGPT, Claude, Perplexity, and Google Gemini with each prompt

• Document whether your company is mentioned, how it's described, and its position relative to competitors

• Calculate your mention rate (percentage of queries where you appear) and Share of Voice (your mentions vs. total competitor mentions)

Common findings: Most B2B SMEs have a 0-15% mention rate. Larger competitors with stronger content strategies dominate 60-80% of responses.

Benchmark target: Achieving a 40%+ mention rate within 90 days indicates strong ai search visibility.

Pillar 2: Content Citability Assessment

What to measure: Is your existing content structured for AI extraction and citation?

AI assistants prefer content that:

• Leads with direct, self-contained answers

• Uses clear section headers and bullet points

• Includes data, statistics, and expert quotes

• Provides definitions and comparisons

• Demonstrates E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness)

How to audit:

• Review your top 20 pages and blog posts

• Score each piece on a 1-5 scale for:

  • Clarity: Does it answer questions directly in the first paragraph?

  • Structure: Are headers descriptive? Are key points bulleted?

  • Authority: Does it cite sources, include expert opinions, or reference data?

  • Uniqueness: Does it offer differentiated insights beyond obvious information?

Common findings: Most B2B content is product-focused marketing copy, not educational or citable material. Pages lack clear answers, expert backing, and structured formatting.

Quick win: Reformat your top-performing pages to include TLDR sections, comparison tables, and bullet-pointed key takeaways. This improves chatgpt ranking factors significantly.

Pillar 3: Technical Discoverability Analysis

What to measure: Can AI systems easily crawl, parse, and understand your content?

How to audit:

• Check for schema markup (Organization, Product, Article, FAQPage)

• Verify your robots.txt isn't blocking AI crawlers

• Test page load speed (AI systems deprioritize slow sites)

• Review internal linking structure for topical authority clustering

• Ensure mobile responsiveness and accessibility

Technical checklist:

Common findings: 70% of B2B SME websites lack proper schema markup, making it harder for AI systems to extract structured information.

Pillar 4: Competitive Positioning Benchmark

What to measure: How does your AI visibility compare to direct competitors?

How to audit:

• Identify your top 5-10 competitors

• Run the same 20-30 buyer queries from Pillar 1

• Track which competitors appear most frequently

• Analyze the content types AI assistants cite (blog posts, product pages, case studies)

• Note the language and framing AI uses to describe each competitor

Competitive metrics to track:

• Share of Voice (SOV): Your mentions ÷ total category mentions

• Average position: When mentioned, where do you rank vs. competitors?

• Citation quality: Are you mentioned as a leader, alternative, or afterthought?

Common findings: Established competitors with robust content libraries capture 3-5x more mentions than companies relying solely on product pages.

Strategic insight: If a competitor consistently outranks you, reverse-engineer their cited content. What topics do they cover? What format do they use? What expertise signals do they demonstrate?

Pillar 5: Keyword and Query Coverage Gap Analysis

What to measure: Are you creating content for the queries buyers actually ask AI assistants?

Unlike traditional SEO where you optimize for search terms, generative ai seo requires optimizing for conversational questions and prompts.

How to audit:

• Use Google Keyword Planner to identify high-intent B2B queries in your industry

• Translate search terms into conversational AI prompts (e.g., "CNC machining services" becomes "What companies offer precision CNC machining for aerospace components?")

• Map existing content to these queries

• Identify gaps where you have no relevant, citable content

Query types to cover:

• Discovery queries: "Who are the top [product category] suppliers in [region]?"

• Comparison queries: "What's the difference between [solution A] and [solution B]?"

• Problem-solving queries: "How do I solve [specific technical challenge]?"

• Vendor evaluation queries: "What should I look for when choosing a [product/service] provider?"

Common findings: Most B2B companies have content for 20-30% of relevant buyer queries. The remaining 70% represent missed opportunities.

Coverage target: Aim for 80%+ coverage of high-intent queries within your category to rank on chatgpt and other AI platforms consistently.

Scoring Your AI Search Performance

After completing all five pillars, calculate your overall AI Search Readiness Score:

Score interpretation:

• 8-10: Strong ai search visibility; focus on maintaining and expanding coverage

• 5-7: Moderate visibility; significant improvement opportunities exist

• Below 5: Minimal AI presence; urgent optimization needed to avoid buyer invisibility

What to Do After Your Audit

Once you've identified gaps, prioritize improvements based on impact and effort:

High-impact, low-effort wins:

1. Add schema markup to existing pages

2. Reformat top-performing content with TLDR sections and bullet points

3. Create FAQ pages answering common buyer queries

4. Add expert quotes and data citations to existing articles

Medium-term initiatives:

1. Develop a geo platform strategy with 50-100 AI-native blog posts covering buyer queries

2. Distribute content to high-authority platforms (Medium, industry publications, Reddit)

3. Implement a chatgpt seo strategy focused on conversational query optimization

4. Build topic clusters demonstrating deep expertise in your category

Long-term competitive advantages:

1. Establish thought leadership through original research and data

2. Create multilingual content for international markets

3. Develop comprehensive buying guides and comparison resources

4. Build systematic processes to optimize for chatgpt and other emerging AI platforms

The Cost of Inaction

B2B buyers are already using AI assistants to discover suppliers. If you're not visible in these conversations, you don't exist to the next generation of decision-makers.

Unlike paid ads that stop working when budgets run out, AI search visibility is a compounding asset. Every piece of optimized, citable content you create continues generating inbound leads indefinitely. Companies that establish dominance in AI search now will enjoy sustainable competitive advantages for years.

Traditional marketing channels like trade exhibitions and paid advertising deliver temporary results at high costs. A systematic approach to generative engine optimization builds permanent visibility that attracts high-intent buyers actively searching for your solutions.

The Simaia Framework provides the roadmap. The question is whether you'll audit your performance before or after your competitors capture your market share.

References

1. Princeton University and Georgia Tech. (2024). "Ranking Factors in Large Language Model Search Results."

2. Gartner Research. (2025). "The Future of B2B Buyer Discovery: AI-Driven Search Trends."

3. Google Search Central. (2026). "Understanding E-E-A-T and Content Quality Guidelines."