AI Visibility Audit

A one-month paid engagement that analyzes your AI Visibility across the four major AI engines, identifies what is working and what is not, benchmarks you against up to four competitors, and delivers a prioritized action plan you can act on immediately.

What is an AI Visibility Audit

It is a one-month engagement that produces a comprehensive diagnostic of your AI Visibility — what AI engines say about your business, what your competitors look like through the same lens, and what to do about the gaps.

  • Comprehensive where the Snapshot is brief. The Audit covers content, technical readiness, off-site authority, and competitive positioning across up to four competitors of your choosing.
  • Specific where generic AI SEO audits are theoretical. Every finding maps to an action you can take.
  • Best for businesses with an existing SEO foundation that want to understand and improve their AI Visibility. The Audit shows SEO issues only where they directly affect AI Visibility outcomes — we are not auditing all of your SEO; we are auditing what AI engines see.

The Audit is the central hub of Telstar’s service architecture. Findings route directly into Priority Fixes, Content Strategy, or further conversation — depending on what the Audit reveals.

The nine-section deliverable

The Audit produces a structured nine-section document delivered as a PowerPoint presentation, walked through over Zoom in a one-hour conversation.

AI Visibility Audit — Nine-Section Deliverable Structure A diagram showing the nine sections of an AI Visibility Audit deliverable: Executive Summary, Engine-by-engine deep dive, Cross-engine patterns, SEO foundation review, Off-site authority, Technical audit, Prioritized recommendations, Next steps, and Audience question inventory. AI VISIBILITY AUDIT The 9-Section Deliverable Comprehensive cross-engine diagnostic with prioritized recommendations and an audience question inventory 1 DECISION-MAKER’S READ Executive Summary Top findings, priorities, and the recommended action sequence. The owner-level synthesis of everything the Audit revealed. 2 PER-ENGINE ANALYSIS Engine-by-Engine Deep Dive ChatGPT, Google AI Overviews, Gemini, and AI Mode covered individually — what each engine sees and what each engine says. 3 PATTERN SYNTHESIS Cross-Engine Patterns What appears consistently versus what varies. Pattern analysis is where strategic implications emerge. 4 FOUNDATION REVIEW SEO Foundation Review A targeted look at the organic search infrastructure only where it directly affects AI Visibility. Not a full SEO audit. 5 AUTHORITY LANDSCAPE Off-Site Authority Backlinks and brand mentions that influence AI citation across earned media, co-citation, and category-defining publications. 6 TECHNICAL INFRASTRUCTURE Technical Audit Schema markup, llms.txt, AI bot access, crawl readiness, structured data. What determines whether AI engines can read and parse your site. 7 ACTION FRAMEWORK Prioritized Recommendations Tier 1 through Tier 4 framework. Each recommendation comes with rationale, expected impact, and suggested sequencing. 8 FORWARD PATHS Next Steps Specific routes forward based on what your Audit revealed. A tailored set of options keyed to your findings. 9 CONTENT-READY MATERIAL Audience Question Inventory Five topics × five high-value prompts buyers ask AI engines, paired with actual answers. The bridge between diagnostic findings and content work. Delivered as a PowerPoint presentation, walked through over Zoom in a one-hour conversation. Final deliverable yours to keep.
  • Section 1 — Executive Summary. Top findings, priorities, and recommended action sequence. The decision-maker’s read.
  • Section 2 — Engine-by-engine deep dive. ChatGPT, Google AI Overviews, Gemini, and AI Mode covered individually — what each engine sees, what each engine says, and where your domain appears or does not.
  • Section 3 — Cross-engine patterns. What appears consistently across engines versus what varies. The pattern analysis is where strategic implications emerge.
  • Section 4 — SEO foundation review (AI Visibility scope). A targeted look at the organic search infrastructure only where it directly affects what AI engines can find, parse, and cite. It is not a full SEO audit.
  • Section 5 — Off-site authority. Backlinks and brand mentions that influence AI citation. Backlinks feed Google rankings, which feed AI Overviews, and ChatGPT’s residual weighting. Brand mentions across earned media and category-defining publications matter independently of links.
  • Section 6 — Technical audit. Schema markup, llms.txt, AI bot access, crawl readiness, structured data. The infrastructure determining whether AI engines can read and parse your site.
  • Section 7 — Prioritized recommendations. It applies the Tier 1 through Tier 4 framework — the same one Priority Fixes uses for execution. Each recommendation comes with rationale, expected impact, and suggested sequencing.
  • Section 8 — Next steps. Specific routes forward based on what your Audit revealed. Not a generic action plan — a tailored set of options keyed to your findings.
  • Section 9 — Audience question inventory. Five topics relevant to your business, each with five high-value prompts buyers are asking AI engines, paired with the actual AI engine answers — twenty-five prompts and answers in total. This is the bridging artifact between diagnostic findings and content production; Content Strategy and Content Development engagements pick it up as their starting brief.

How the methodology works

The Audit follows a defined process. Each phase produces a specific output that feeds the next.

AI Visibility Audit — Methodology Process Diagram A timeline diagram showing the eight phases of an AI Visibility Audit engagement across four weeks: Discovery, Data gathering, Site analysis, Pattern analysis, Topic and prompt research, Prioritization, Synthesis, and Presentation. AI VISIBILITY AUDIT The Methodology One month from kickoff to presentation, organized as eight defined phases across four weeks WEEK 1 Discovery and data collection WEEKS 2–3 Analysis (engine, pattern, competitive, topic-and-prompt) WEEK 4 Synthesis and delivery ENGAGEMENT PHASES 1 Discovery Kickoff call: scope, competitive set, priority topics 2 Data gathering AI Visibility data collection across four engines and competitors 3 Site analysis Content, technical, schema, SEO foundation (AI Visibility scope) 4 Pattern analysis Cross-engine synthesis; opportunities and gaps identified 5 Topic and prompt research Five topics, five prompts each, with answers 6 Prioritization Tier 1–4 framework applied to all findings 7 Synthesis Findings written into the nine-section deliverable 8 Presentation PowerPoint walked through over Zoom; next steps discussed Each phase has a defined output that feeds the next. The kickoff call (Phase 1) establishes scope; the presentation (Phase 8) delivers the nine-section document.
  • Discovery. A kickoff call to understand business context, competitive set, and priority topics.
  • Data gathering. AI Visibility data collection across the four engines and your competitor set using AI visibility tools.
  • Site analysis (AI Visibility scope). A content audit, technical audit, and schema audit, plus the SEO foundation review focused specifically on factors that affect AI engines’ ability to find, parse, and cite your content.
  • Pattern analysis. Cross-engine synthesis and the identification of opportunities and gaps.
  • Topic and prompt research. Five priority topics for your business, with high-value prompts and AI engine answers captured for the audience question inventory.
  • Prioritization. The Tier 1 through Tier 4 framework applied to all findings.
  • Synthesis. Recommendations and the audience inventory are written into the nine-section deliverable.
  • Presentation. The PowerPoint walked through over Zoom (one to one and a half hours), with discussion of which next steps fit your situation.

Engine coverage

The Audit covers four engines — the four with continuous-search consumer surfaces that AI visibility tools can track.

The Audit covers: ChatGPT, Google AI Overviews, Gemini, and AI Mode.

The Audit does not cover at this tier: Claude, which has no continuous-search consumer surface to track (manual assessment is available in Intelligence), and Perplexity, which is covered in Intelligence engagements.

For coverage that adds Perplexity and a manual Claude assessment, Intelligence is the right tier — five engines, up to nine competitors, a two-month engagement.

Competitive analysis

The Audit includes up to four competitors of your choosing. The competitive lens is where most strategic insight lands.

  • You identify up to three competitors during the kickoff call — businesses you compete with for buyer attention, not the ones with the loudest marketing.
  • We verify which of your named competitors are tracked in the AI Visibility dataset before analysis begins. Most established businesses are; smaller or niche competitors sometimes are not.
  • If a key competitor is not in the tracked dataset, that is intelligence in itself — it typically suggests lower AI Search presence than expected, which is information you can use.
  • Each tracked competitor is analyzed across the same four engines and the same nine deliverable sections — summary form for competitors, full analysis for your domain.
  • Findings name where competitors appear that you do not (opportunities), where you appear that they do not (defensible strengths), and where AI engines treat the category as a whole (positioning territory).

For deeper competitive analysis — up to nine competitors across a two-month engagement — the Intelligence service is the right engagement.

How a one-month engagement runs

Four weeks from kickoff to delivery. Each phase has a defined deliverable and check-in.

  • Week 1 — Discovery and data collection. A kickoff call (one hour) confirming scope, competitive set, and priority topics. Data collection across the four engines and your competitor set begins. You provide any internal context that should inform the analysis.
  • Weeks 2–3 — Analysis. Engine-by-engine analysis, cross-engine pattern identification, site analysis (content, technical, schema, SEO foundation), competitive comparison, and topic and prompt research for the audience question inventory.
  • Week 4 — Synthesis and delivery. Findings are written into the nine-section deliverable, prioritization is applied, and the presentation is delivered as a PowerPoint over Zoom (one to one and a half hours) with discussion of which next steps fit your situation.
  • After delivery. You receive the PowerPoint for ongoing reference. No follow-up reaches you unless you opt in for periodic informational emails on the request form. If you want to proceed with Priority Fixes, Content Strategy, or further conversation, links are included in the delivery email.

Frequently Asked Questions

How much does an AI Visibility Audit cost?

Audit engagements scope to your business situation — pricing is shared on the discovery call. We do not publish a range because the scope variables (competitive set, depth of analysis, content inventory size) meaningfully affect the engagement. Most Audits fall within a defined band, which we discuss directly once we have understood the work you need.

How long does an Audit take from start to finish?

One month from kickoff to presentation. Week 1 is discovery and data collection, weeks 2 and 3 are analysis, and week 4 is synthesis and delivery. The nine-section deliverable lands in the final week, walked through in a one-hour Zoom conversation.

What is the difference between a Snapshot and an Audit?

The Snapshot is free, covers four engines, runs on your domain alone, and produces a short PDF in 1–2 business days. The Audit is paid, covers four engines, includes up to four competitors, produces a nine-section deliverable with prioritized recommendations, and runs across a one-month engagement. The Snapshot establishes the baseline; the Audit acts on it.

What is the difference between an Audit and Intelligence?

The Audit is one month, four engines, three competitors, and a nine-section deliverable. Intelligence is two months, five engines (the four tracked engines plus a manual Claude assessment, and Perplexity in place of AI Overviews), up to nine competitors, and six deliverables, including a full Cross-Reference Workbook. The Audit is the right tier for project-scoped diagnostic work; Intelligence is the right tier for depth, movement patterns, and the engines an audit-tier engagement does not reach.

How is this different from a traditional SEO audit?

A traditional SEO audit examines whether your site is set up to rank in Google’s organic results. The AI Visibility Audit examines whether your site is set up to be cited and described accurately by AI engines — a related but distinct discipline. We touch SEO issues only where they directly affect AI Visibility outcomes. For a comprehensive traditional SEO audit, you would want a different engagement.

What do I do with the Audit findings after delivery?

You have peer-positioned options. You can execute the recommendations yourself using the prioritized roadmap. You can engage Priority Fixes for technical implementation. You can engage Content Strategy for the content planning the audience question inventory directly supports. Or you can schedule a follow-up conversation to discuss which path fits before committing to any of them. The Audit does not lock you into Telstar’s implementation services — but they are available if the findings point that way.

Curious about how your business shows up in AI engine answers?

The AI Visibility Audit shows where you stand across the engines and what to fix first. If you’d rather talk it through, schedule a 30-minute conversation.

Get Your Visibility Audit → Schedule a Conversation →

The CT Brief is a free monthly look at how AI engines answer real questions about Connecticut businesses.

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About the Practice

Telstar Consulting is an independent AI Visibility practice based in Connecticut. It helps businesses show up accurately and often when buyers ask AI engines for recommendations, with SEO as the foundation. That matters because more buyers now begin inside AI engines than on search results pages, and a business the engines don’t name doesn’t make the shortlist.

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