Sample audit. Example data. The company "Apex Analytics" is fictional. All scores, quotes, and findings below are illustrative of the real audit format. No fabricated client names. No testimonials.
AI Visibility Audit: Apex Analytics
This is what your Discovery Audit looks like. Same structure, same depth, same evidence format. Domain changed to a fictional example. All scoring methodology, prompt log excerpts, fix rationale, and hallucination log below reflect how a real audit is structured and delivered.
Overall AI Visibility Score: 18/100
What each AI engine actually says.
ChatGPT (GPT-4o)
10 queries run
When asked: "What are the best revenue analytics platforms for sales teams?" — ChatGPT responded with a 5-tool list. Clari appeared in position 1. Gong in position 2. Apex Analytics was not mentioned.
Perplexity (Sonar)
10 queries run
Across all 10 Perplexity queries, Apex Analytics received zero citations. Gong appeared 7 times. Perplexity cited four third-party review aggregators as sources — none of which include Apex Analytics in their published category lists.
Google Gemini
8 queries run
Gemini cited Apex Analytics twice — but described it as "a data visualization tool", which is factually incorrect. This hallucination likely originates from an older G2 category listing. Competitors were correctly categorized in all 6 instances.
Google AI Overviews
8 queries run
AI Overviews appeared on 5 of 8 queries. Apex Analytics was not cited in any. Clari was cited as a source in 5 Overviews, with a direct URL citation in 3 of them — meaning Clari content is passing the structural eligibility check (passage quality, schema) that Apex Analytics currently fails.
Claude (claude-3-5-sonnet)
6 queries run
Claude mentioned Apex Analytics once — in response to a direct brand search query. For category-intent queries ("best tools for pipeline forecasting"), Gong, Clari, and Chorus.ai appeared. Apex Analytics did not.
What AI gets wrong about your brand.
AI models sometimes cite your brand incorrectly. These hallucinations reduce buyer trust when they do appear — worse than no citation. Every finding below is logged with the source query, the incorrect claim, the correct fact, and a likely root cause.
Query: "What is Apex Analytics?"
Apex Analytics is a data visualization tool for business intelligence teams.
Apex Analytics is a revenue operations analytics platform for B2B sales teams.
Query: "Tell me about Apex Analytics — when was it founded?"
Apex Analytics was founded in 2019.
Apex Analytics was founded in 2021.
Query: "How much does Apex Analytics cost?"
Apex Analytics offers plans starting at $49/user/month.
Current pricing starts at $199/seat/month for team plans.
15 fixes, ranked by impact-to-effort ratio.
Every fix includes: one-sentence diagnosis, specific action, effort estimate (hours, not "weeks"), and expected impact. Ordered so you can hand the first 5 to a developer today.
Add Organization + SoftwareApplication JSON-LD to every page
apex-analytics.io has no Organization schema. Clari and Gong both have correct @type:SoftwareApplication markup with applicationCategory, operatingSystem, and offers sub-schemas. This is the single most common reason mid-size SaaS brands are passed over in AI Overview citations.
Add Organization + SoftwareApplication JSON-LD to your homepage, pricing page, and product landing pages. Use schema.org/SoftwareApplication with applicationCategory: "BusinessApplication". Include your description, foundingDate, and knowsAbout fields.
Fix the Gemini category hallucination via entity disambiguation
Gemini describes Apex Analytics as a 'data visualization tool'. The likely root cause: an outdated G2 category tag ("Data Visualization") that predates your current positioning. AI models frequently pull category descriptions from G2, Capterra, and GetApp before your own site copy.
Update your G2, Capterra, GetApp, and Trustpilot profiles to correctly categorize the product as 'Revenue Operations Software' or 'Sales Analytics'. Add an explicit entity disambiguation paragraph to your About page: 'Apex Analytics is a revenue operations analytics platform — not a data visualization tool. We help B2B sales teams...'
Get listed on AI-indexed category aggregators
Perplexity cites four category aggregators in 8 of 10 revenue analytics queries. None of them include Apex Analytics. These are: G2 category pages (you are listed but ranked 47th — below AI's typical 10-result threshold), Capterra (same), Software Advice (not listed), and GetApp (listed, outdated description). AI models use these pages as structured category signals.
Priority actions: (1) Request a review campaign on G2 targeting 15+ recent reviews — G2 category pages typically need top-20 ranking to be cited in AI answers. (2) Add a complete listing to Software Advice (missing entirely). (3) Update GetApp description to match current positioning. (4) Target 2–3 vertical publication roundups ('best RevOps tools 2026') — these are Perplexity's highest-weighted citation sources.
Restructure the pricing page for AI extractability
The apex-analytics.io pricing page uses a JavaScript-rendered comparison table. AI crawlers (including Googlebot for AI Overviews) cannot extract the feature comparison data because it loads client-side. Clari's pricing page uses static HTML with FAQ schema — AI models can directly cite Clari's plan descriptions in structured answers.
Convert the pricing page to static HTML with server-side rendering. Add FAQ schema for the top 5 questions prospects ask about pricing. Include a plaintext feature comparison table (no JS rendering required).
Add FAQ schema to your top 3 use-case pages
Your '/pipeline-forecasting' and '/revenue-analytics' pages have no FAQ schema. Gong's equivalent pages have 5–8 FAQ schema blocks each, and Gong is consistently cited in AI answers to forecasting-intent queries. FAQ schema is the highest-leverage structural signal for AI Overview citation eligibility.
Add 5–8 FAQ schema blocks per page, formatted as questions a buyer would ask. Use genuine answer text — not marketing copy. Example: 'How does Apex Analytics handle pipeline coverage gaps?' — answer in 80–120 words with specific product mechanics.
Allow GPTBot and PerplexityBot in robots.txt
apex-analytics.io/robots.txt contains a wildcard Disallow rule that blocks all non-Google crawlers, including GPTBot and PerplexityBot. This means Perplexity cannot access any Apex Analytics pages for real-time grounding. Your Perplexity citation rate of 0% is partly structural — the crawler is blocked.
Add explicit Allow rules for GPTBot, PerplexityBot, and anthropic-ai in robots.txt. Consult your legal team on whether your content qualifies as training-data-eligible — if not, use the new meta tag approach (x-robots-tag: noai) on specific pages instead of blocking the entire crawler.
Add llms.txt to site root
llms.txt does not exist at apex-analytics.io/llms.txt. This emerging standard (analogous to robots.txt for LLMs) lets you provide structured brand guidance, key pages, and preferred description text directly to AI crawlers. Multiple AI providers have committed to reading it — including Perplexity, You.com, and SearchGPT.
Create /llms.txt with: company name, description, key pages (homepage, pricing, use-case pages), and a 200-word authoritative brand description in plain text. Reference the emerging llmstxt.org standard for format.
Create one authoritative comparison page: Apex Analytics vs. Clari
ChatGPT comparison queries ('apex analytics vs clari', 'clari alternative') return Clari as the default recommendation with no Apex Analytics alternative listed. Third-party comparison posts are the highest-weighted citation source for ChatGPT category queries. Zero such comparison content currently links to apex-analytics.io.
Publish a 1,500-word comparison page: 'Apex Analytics vs. Clari: Honest Comparison for RevOps Teams'. Use structured HTML with a static comparison table. Include an FAQ schema block. Distribute to 2–3 RevOps newsletters for backlink seeding. This page becomes a citation target for AI comparison queries.
Claim and complete your Wikipedia presence
Apex Analytics has no Wikipedia article. Clari has a Wikipedia page with 3,200 words and 22 citations. AI models weight Wikipedia as a primary entity validation source — its presence correlates strongly with consistent multi-platform citation. This is not about traffic; it is about entity authority in AI training data.
Check Wikipedia's notability requirements — at $X ARR with Y customers, Apex Analytics may qualify. If so, draft a neutral, citation-backed article. If not yet notable, build the citation footprint first (press coverage, industry blog mentions) and return to this step in 60–90 days.
Create an About page optimized for AI entity extraction
The current apex-analytics.io/about page is 140 words. It does not include founding date, founding team names, headquarters city, or a clear category statement. AI models building entity records for a brand pull from About pages — the current page provides insufficient structured context. Gong's About page is 420 words with explicit entity signals.
Rewrite the About page to 350–450 words. Include: exact founding year, city, product category (spelled out as 'revenue operations analytics software'), description of the customer profile (B2B, $10M–$100M ARR, RevOps teams), and founding team names with role titles. Use paragraph format — not bullet points (AI parsers extract paragraphs more reliably than bullets).
Add BreadcrumbList schema to all non-homepage pages
BreadcrumbList schema is absent from product and use-case pages. Google AI Overviews use breadcrumb data to understand page hierarchy and validate that a cited URL is a topical authority within a domain — not a random landing page.
Add BreadcrumbList JSON-LD to all use-case and product pages. Each crumb should match the visible page hierarchy: Home > Products > Pipeline Forecasting.
Submit a press release to 3 vertical RevOps publications
Apex Analytics has 4 press mentions in 2025 total. Clari has 38. The gap matters because AI models trained on recent web crawls weight press-mentioned brands more heavily in recommendation outputs. Perplexity's real-time grounding index surfaces recent press as fresh evidence — no press = lower citation weight.
Identify 3 publications covering your ICP (RevOps Co-op, Modern Sales Pros, The SaaS CFO). Submit a data-backed press release tied to a real company milestone (customer milestone, product launch, research data). Prioritize publications that publish structured "tool roundup" articles — these are the highest-citation-value placements.
Fix site crawlability for ClaudeBot and AI Overviews crawler
Crawl test shows three product pages (including /revenue-analytics and /deal-inspection) return 401 Unauthorized to non-authenticated crawlers. AI crawlers do not log in. These pages — which describe core use cases — are invisible to all AI models. Competitors who allow crawl access to equivalent pages appear in corresponding AI answers.
Set these pages to publicly accessible (no login wall). If showing pricing or account-specific content on those pages, move auth-gated content to a separate /dashboard path and keep the marketing landing pages fully public.
Publish a primary-research data asset on RevOps AI Adoption
The most-cited content in AI answers about revenue analytics is survey data and benchmarks. Gong publishes a State of Revenue report annually — it is cited in 14% of relevant Perplexity queries and in 3 of 10 Claude queries. Apex Analytics has no comparable owned research asset.
Survey 50–100 RevOps professionals on a specific, measurable question (e.g. pipeline coverage ratios by stage, or AI tool adoption rates). Publish findings as a web-native data page with embedded charts. This becomes a citation-eligible research asset — both for AI models and for third-party publications linking to it.
Standardize brand entity signals across all third-party profiles
Cross-referencing the company description on G2, LinkedIn, Crunchbase, and the apex-analytics.io homepage reveals four different category labels and three different employee count figures. AI models use entity matching across sources — inconsistency reduces confidence in the entity record, which correlates with lower citation frequency.
Audit all public profiles (G2, LinkedIn, Crunchbase, Capterra, AngelList, GetApp, Software Advice, PitchBook). Standardize: company name (exact), founding year, employee count range, product category label, and description paragraph. One canonical 150-word description that all profiles use.
Your domain. Your competitors. Your fix list.
The sample above is the exact format, depth, and evidence standard you get for your domain. Same 5 platforms. Same hallucination log. Same ranked fix list with effort estimates your developer can act on.
10 actionable fixes — or your money back.
If your Discovery Audit does not surface at least 10 actionable AI-visibility gaps — specific fixes your team can act on — we refund every cent. No forms. No questions. This guarantee is specific on purpose: in every audit we have run, every brand had more than 10 gaps. Yours will too.
5 business day delivery · 5 AI platforms · 10-fix guarantee · full refund if we miss