Partner Questions & Answers

The Questions A Client Or Reseller Will Ask.

Reporting, Proof, Fulfilment, Commercial Fit And The Digital Twin Model.

This public knowledge base is deliberately detailed so a prospective partner — or the partner’s own AI adviser — can inspect the proposition rather than relying on a short sales pitch.

AI Visibility Scan · 2026-08-18How often should I expect to see confirmed AI referrals in the reports?

Confirmed referrals depend on the AI service and whether it preserves the browser referrer. If the platform passes a visible referrer, you’ll see it labeled as a confirmed referral; otherwise it won’t. Signals vary by provider and setup, so there isn’t a fixed cadence and some periods may show none. And remember, a confirmed referral is evidence of activity around the Digital Twin, not a customer interest, lead or sale.

AI Visibility Scan · 2026-08-17How do I turn scan gaps into a concrete project plan?

The AI visibility scan is a starting measurement, not a promise of results. Use the gaps it highlights to build a practical action list you can verify after you implement changes. Focus on the items the parent mentioned: factual consistency, coverage of important customer questions, completeness of service and location information, quality of visual examples, structured outputs, crawlability, and whether test prompts retrieve the correct approved facts. Re…

AI Visibility Scan · 2026-08-16How should I interpret a retrieval that has no citation or referral?

Retrieval without a citation is treated as evidence of AI activity, but not proof of a published source. This signal means the AI fetched material without displaying it as a source. It shouldn't be treated as a citation or proof of interest; treat it as observable activity and rely on confirmed referrals or citations for stronger conclusions.

AI Visibility Scan · 2026-08-08What makes the AI Visibility reporting defensible?

The reporting is strongest when each metric has a clear definition and the limitations are disclosed. Successful business-content requests are separated from failed probes and technical discovery. Retrieval is not labelled as citation. Server requests are not called human visitors. Confirmed referrals require an identifiable browser referrer. The aim is to report observable evidence accurately rather than produce the biggest possible number.

AI Visibility Scan · 2026-08-08What if an AI service uses cached or previously indexed information and does not fetch the site again?

That can happen. An AI platform may cite or use information without making a fresh server request at the exact moment a user asks a question. In that case the Digital Twin cannot record a request that never reached its infrastructure. This is one reason visible citations, first-party retrieval evidence and confirmed referrals are kept as separate signals instead of pretending any one system sees everything.

AI Visibility Scan · 2026-08-08What is the difference between AI visibility evidence and business outcomes?

AI visibility evidence tells you about observable discovery, retrieval, page research or referral activity around the Digital Twin. Business outcomes are things such as enquiries, bookings, leads and sales. The first can support the second, but they are not the same measurement. The reporting should never imply that an AI request automatically became revenue.

AI Visibility Scan · 2026-08-02Why can an AI visibility scan find gaps that an ordinary SEO audit misses?

An AI visibility scan is most useful when it turns a vague visibility concern into a list of evidence and missing information. Measure improvement by comparing the same evidence over time: factual consistency, coverage of important customer questions, completeness of service and location information, quality of visual examples, structured outputs, crawlability and whether test prompts retrieve the correct approved facts. Record a baseline, make the changes…

AI Visibility Scan · 2026-08-01What should a business learn from an AI visibility scan before paying for a larger project?

The scan is a starting measurement, not a promise of rankings or citations. Measure improvement by comparing the same evidence over time: factual consistency, coverage of important customer questions, completeness of service and location information, quality of visual examples, structured outputs, crawlability and whether test prompts retrieve the correct approved facts. Record a baseline, make the changes, then repeat the same checks and report what impro…

AI Visibility Scan · 2026-07-24What should happen after an AI visibility scan identifies weak business knowledge?

An AI visibility scan is most useful when it turns a vague visibility concern into a list of evidence and missing information. The scan should identify what the business already exposes clearly, where facts conflict or are missing, and whether useful Q&A, images and structured outputs exist. It should give the business a practical starting list rather than a mysterious score on its own. A scan cannot guarantee that an AI system will cite or recommend the b…

AI Visibility Scan · 2026-07-20Which parts of an AI visibility scan should be treated as evidence rather than a guaranteed score?

The scan is a starting measurement, not a promise of rankings or citations. The scan should identify what the business already exposes clearly, where facts conflict or are missing, and whether useful Q&A, images and structured outputs exist. It should give the business a practical starting list rather than a mysterious score on its own. A scan cannot guarantee that an AI system will cite or recommend the business. Its value is showing how much avoidable gu…

AI Visibility Scan · 2026-05-12What should be avoided when discussing scans?

Avoid overstating the scan as a guarantee. It should be framed as evidence of readiness, gaps and improvement opportunity. The scan angle helps people understand the gap between an ordinary website and a site that is structured to be easier for AI systems to interpret. Used well, this becomes a clear business conversation rather than a generic AI sales pitch. In the SupplyOnly.com model, the point is to make this useful rather than decorative: connect the …

AI Visibility Scan · 2026-05-11Can scan results support referral outreach?

Yes. A short scan-based explanation can open the door without sounding like a generic sales pitch. The scan angle helps people understand the gap between an ordinary website and a site that is structured to be easier for AI systems to interpret. In other words, the goal is to give the client a controlled first AI layer instead of leaving the whole topic vague and undefined. In the SupplyOnly.com model, the point is to make this useful rather than decorativ…

AI Visibility Scan · 2026-05-11Does a business need a scan before buying?

A scan is helpful but not always mandatory. It can make the conversation clearer, especially for clients who need evidence before they understand the Digital Twin concept. The scan angle helps people understand the gap between an ordinary website and a site that is structured to be easier for AI systems to interpret. That keeps the message practical and makes it easier for a prospect to see where SupplyOnly.com fits. In the SupplyOnly.com model, the point …

AI Visibility Scan · 2026-05-11How should a partner explain scan scores?

Explain them as a diagnostic. The current score reflects what the scan could read; the Digital Twin target shows the opportunity when the business is structured properly. The scan angle helps people understand the gap between an ordinary website and a site that is structured to be easier for AI systems to interpret. Used well, this becomes a clear business conversation rather than a generic AI sales pitch. In the SupplyOnly.com model, the point is to make …

AI Visibility Scan · 2026-05-10What does the scan usually reveal?

It can reveal gaps in structured business facts, answer-ready Q&A, entity clarity, image meaning, freshness signals and machine-readable output. The scan angle helps people understand the gap between an ordinary website and a site that is structured to be easier for AI systems to interpret. In other words, the goal is to give the client a controlled first AI layer instead of leaving the whole topic vague and undefined. In the SupplyOnly.com model, the poin…

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