SAMPLE REPORT · FICTIONAL EXAMPLE
How a real Expert AI Visibility Audit is structured: locked buyer questions, clean multi-platform tests, mention / citation / accuracy / share-of-voice scoring, site readiness, and a commercial 30-day plan. All brands below are fictional examples.
Example company · not a real client
Offer
B2B revenue intelligence platform for mid-market SaaS teams
Market
United Kingdom
Test date
15 July 2026
Prompts
30 buyer questions
Pages
8 priority URLs
Session
Primarily logged out / clean session
Platforms sampled
ChatGPT
Gemini
Perplexity
Google AI searchIllustrative sample only
Northline Analytics, ApexRev, ClearMetric, and PipelineOS are fictional. Numbers, charts, and findings show report structure—not results for any real company.
Aligned with common GEO / AEO practice: define queries, test clean sessions, measure mentions and citations, inspect readiness, then prioritize commercially—not a single automated score.
Lock 30 buyer-intent questions across discovery, comparison, and purchase stages—adapted to offer, ICP, market, and language. The list stays consistent so findings are comparable over time.
Run prompts on ChatGPT, Gemini, Perplexity, and Google AI search where accessible—primarily logged out—to reduce personalization noise. Record date, market, language, and account state.
For each answer: is the brand named? Is the primary site cited? Is the description accurate? Who else appears? Aggregate into mention rate, citation rate, recommendation presence, and share of voice versus competitors.
Review crawl access, entity clarity, structured data, answer-first content, trust signals, and third-party authority gaps on up to ten priority pages—separate from observed AI answers.
Convert gaps into a top-five priority list, quick wins versus strategic work, effort/impact, affected URLs, and a sequenced 30-day roadmap—with confidence and limitations documented.
Rates are % of the 30 tested prompts in this fictional sample. Real reports document every prompt and condition.
Mention rate
23%
Brand named in answers
Citation rate
12%
Primary site cited
Recommendation rate
8%
Actively recommended
Description accuracy
41%
Matches site claims
Share of voice
14%
Vs 3 competitors
Share of voice
Intent coverage
Discovery is stronger than comparison and purchase-intent in this sample—common when entity clarity is weak and alternatives pages are missing.
Cross-platform breakdown
ChatGPTGeminiPerplexityGoogle AI searchEvery real report records platform, date, market, language, account conditions, and confidence.
Documented sample
Northline is occasionally named on generic “revenue intelligence” lists but is often omitted when the prompt specifies UK mid-market SaaS. When mentioned, the product is described as “analytics software” without RevOps or forecasting specificity.
Evidence · Logged-out sample, English, UK market framing, 15 July 2026. Three discovery prompts; one produced a mention without a primary-site citation.
Documented sample
Answers preferred category leaders and review-style sources. Northline’s homepage claims were not reflected; description accuracy could not be validated because the brand was absent from two of three comparison prompts.
Evidence · Search-assisted sample where available. Competitor pages and aggregator-style sources dominated citations.
Documented sample
When Northline appeared, Perplexity cited a third-party roundup rather than northline.example. Product scope was compressed to “sales dashboard,” missing forecasting and RevOps workflow claims present on the site.
Evidence · Citation-forward sample. Primary site cited less consistently than review and directory sources.
Documented sample
Where AI overview-style experiences were accessible, category queries surfaced larger suites. Northline did not appear in the preserved observation set for purchase-intent prompts.
Evidence · Access and layout vary by market and account state; treated as a documented sample only.
Thirty questions across discovery, comparison, and purchase. Below is a shortened illustrative set.
Fictional brands only. Real audits use the prospect’s named direct competitors—never implied endorsement of third parties.
Mention rate comparison
Category suite · forecasting + CRM-adjacent analytics
Mentions
72%
Citations
58%
Dominates generic category lists and comparison prompts in the sample.
Enterprise revenue platform alternative
Mentions
64%
Citations
51%
Wins enterprise-framed prompts; less precise for mid-market RevOps.
SMB pipeline and reporting tool
Mentions
41%
Citations
28%
Appears on cost-focused shortlists more often than the sample subject.
PerplexityPrompt tested
“What does Northline Analytics do?”
Observed answer pattern
Northline Analytics is a sales dashboard tool for tracking deals and reporting pipeline metrics.
Expected site-aligned description
Northline Analytics is a revenue intelligence platform for mid-market B2B SaaS teams. It helps RevOps and sales leaders improve forecast accuracy, unify pipeline reporting, and operationalize revenue workflows across common CRM platforms.
Gap
Missing RevOps positioning, forecasting outcomes, target segment, and integration context. “Sales dashboard” understates the commercial offer.
Discovery prompts that name UK mid-market SaaS rarely surface Northline. Category leaders dominate. Commercial risk: buyers never reach a comparison stage with Northline in the set.
Sample answers compress the offer to “sales dashboard” or generic analytics. Forecasting, RevOps workflow, and mid-market positioning on the site are not reflected in generated descriptions.
When Northline appears, citations more often point to third-party roundups than to product or integration pages. Primary pages lack clear answer-first summaries and evidence blocks AI systems can reuse.
ApexRev and ClearMetric win comparison-style prompts. Northline’s public site lacks structured alternatives framing for the exact shortlist language buyers use.
Organization and SoftwareApplication markup is incomplete or inconsistent with visible claims. Author, evidence, and trust signals are thin on product pages.
Separate from observed AI answers: how extractable and citation-ready the public site is.
Add a concise BLUF block on the homepage and product page: who it is for, what problem it solves, and what outcomes it claims—with one evidence sentence.
Standardize brand/product naming and implement accurate Organization + SoftwareApplication markup that matches on-page content.
Ship a market-and-ICP page that answers “who is this for in the UK mid-market” with proof, integrations, and clear differentiation.
Publish careful alternatives framing versus ApexRev, ClearMetric, and PipelineOS without unsupported superiority claims.
Prioritize review profiles, partner listings, and original evidence (metrics, methodology notes) that AI systems can cite alongside primary pages.
Sequenced weeks
Buyer questions tested
30 (discovery, comparison, purchase-intent)
Testing date
15 July 2026
Target country
United Kingdom
Target language
English
Platforms
ChatGPT, Gemini, Perplexity, Google AI search (where accessible)
Account state
Primarily logged out / clean session
Competitors
ApexRev, ClearMetric, PipelineOS (fictional examples)
Pages in scope
Up to 10 strategically important public pages (8 sampled here)
Important limitation
Documented visibility sample—not a permanent ranking
AI-search outputs can vary by platform, model, prompt wording, location, language, account state, personalization, time of testing, and repeated execution. This report presents a documented visibility sample and strategic baseline. It does not claim a permanent or universal AI-search ranking. All company and competitor names in this sample are fictional examples.
You are not buying a PDF or another automated score.
See how AI search describes your brand. Fix what is limiting visibility. Build the foundation to be recommended.
A manually reviewed sample that proves specific visibility problems without the full audit or roadmap.
Best for · Qualified B2B sites considering work in the next 30–90 days
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Not included
Target: 2 business days after acceptance
Request free briefExpert-led diagnosis: how AI discovers, describes, compares, and recommends you—plus what to fix first.
Best for · Teams that need a commercial baseline before building or buying implementation
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Target: 5 business days after intake is complete
Start with free briefNot another report—fix the highest-priority website, entity, and content gaps and set a recheck baseline.
Best for · Companies ready to implement after (or with) the Expert Audit
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Not included
Target: 10 business days after access + intake
Start with free briefMonthly measurement + one or two defined execution lanes—not unlimited marketing.
Best for · After audit or sprint, when continuous visibility work is needed
You get
Not included
3-month minimum · monthly cycle
Start with free briefEvidence showing how AI systems currently represent the company
Competitive visibility intelligence
Clarity about what matters commercially
Implementation of the highest-priority improvements
A documented baseline and continuation plan
LoudScale helps B2B companies improve how they are discovered, described and recommended across AI search. We identify where competitors are winning, fix the website and entity signals holding the brand back, and build the content foundation required for long-term visibility. Commercial pricing and contracts are shared when fit is clear—this page focuses on structure and scope.
NEXT STEP
Request a free, manually reviewed AI Visibility Opportunity Brief for a qualified B2B website. Submission does not guarantee acceptance.