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.
We separate signals with clear definitions: discovery, retrieval, visible citation, and confirmed referral, and report them as distinct lines. A retrieval is considered successful only when the retrieved page contains approved facts that answer the question. If there’s no approved content, it’s a failed or partial match and reported separately. Also, do not treat any signal as a guarantee of interest or sales—the same signals are used to measure knowledge …
AI Visibility Scan · 2026-09-24What’s the simplest dashboard to show knowledge growth to a client?You want a dashboard that shows progress without promising sales. Use a lightweight view that ties AI visibility changes to your approved facts, Q&A and images. Keep it grounded in concrete measures rather than guesses. Focus on three things: (1) core questions coverage — how many key questions are now supported by approved facts; (2) retrieval activity linked to those facts; and (3) updates to Q&A, images or structured outputs. Include a clear baseline an…
AI Visibility Scan · 2026-09-23What concrete steps should I take to turn AI visibility signals into knowledge actions for a client?Signals like discovery, retrieval, and referrals are evidence of AI activity, not guarantees of revenue. To move from signals to knowledge for a client, start by documenting a baseline of what has been observed and which approved facts it touches. Then build a simple, repeatable plan: 1) define a baseline set of signals (discovery, retrieval, referrals) and map them to the exact facts, Q&A, images, and structured information that exist today; 2) measure co…
Explain that evidence parts show current readiness and gaps, not guaranteed outcomes. Describe discovery, retrieval, and referral signals as indicators of what the site can support today, and clearly say they don't guarantee AI citations or rankings. Use plain language and connect each gap to a concrete action you can take, like updating a fact, adding a FAQs, or improving an image cue. A short walkthrough can then lay out the plan to close those gaps, wit…
AI Visibility Scan · 2026-09-21What extra metrics should I add next, and when should I update the baseline?Start with the baseline signals you can observe consistently: discovery events over time; first-party retrievals aligned to approved facts; the proportion of questions resolved using approved knowledge; confirmed AI referrals or browser arrivals; and outputs that include visible citations. These form the defensible core you can show a client. Then plan progressive metrics that reveal deeper knowledge and usefulness, not guarantees. Track changes over time,…
AI Visibility Scan · 2026-09-16What evidence should we show the client to prove the fixes helped?Provide a brief, client-ready summary of what changed: which core pages (services, locations) were fixed, what Q&A were added or tightened, and where visual examples was improved. Keep it factual and concrete. Show the observable signals before and after the fixes: discovery counts, retrievals with approved facts, any citations, and coverage of the top customer questions. Remember these signals are evidence of progress, not a promise of sales. Close with t…
Start with a small, evidence-based set of metrics that show progress without promising outcomes. Focus on signals you can observe consistently: discovery events over time; first-party retrievals aligned to approved facts; the proportion of questions that resolve with approved knowledge; confirmed AI referrals or browser arrivals; and whether outputs include visible citations. Use a baseline from an initial period and compare current results to that baselin…
AI Visibility Scan · 2026-09-11What exact data points should appear on a client-facing progress dashboard?Show discovery events, first-party retrievals with approved facts, and confirmed referrals. Also include how many core customer questions are covered by the approved knowledge and whether the outputs show visible citations. Compare a baseline to current results and explain that improvements reflect deeper knowledge and better answer quality, not guaranteed sales. Keep the dashboard simple and use it to guide next steps like adding Q&A or updating facts.
AI Visibility Scan · 2026-09-10What concrete metric should I show a client to prove progress if signals don’t guarantee sales?Treat AI visibility signals as evidence, not results. To show progress to a client, track several elements over time: discovery events, first-party retrievals with approved facts, and any confirmed referrals. Also measure how much of the core customer questions are covered by the approved knowledge and whether the outputs include visible citations. Compare a baseline to current results and explain that improvements reflect deeper knowledge and better answe…
After the scan, identify gaps that block key customer questions or service details. Use the baseline evidence: which pages were discovered, which ones were retrieved with or without citations, and where coverage is missing. Plan small, testable edits to fill those gaps—update missing Q&As, tighten location and service details, and ensure approved facts are reflected. Then re-run the same checks to measure improvement. Remember, observable signals show acti…
AI Visibility Scan · 2026-08-30Which parts of the scan should I treat as evidence, not a guarantee?The parts that count as evidence are the concrete things your scan can actually confirm: what facts are clearly exposed, where those facts clash or are incomplete, whether you have useful Q&A, visual examples, structured information, and any structured outputs. Treat those as evidence of readiness and gaps, not as a promise of results. Use that evidence to create a short action list you can walk a client through: fix the facts first, add or improve Q&A, ad…
AI Visibility Scan · 2026-08-26How should I explain the three signals to a client clearly?There are three signals you should describe: discovery, retrieval, and referral. Discovery is when an AI or crawler spots a public resource. Retrieval is when the AI fetches material to answer, but it may not show it as the source. Referral means an identifiable AI service arrived with a browser referrer. Explain to a client that a retrieval without a citation isn’t proof of interest; it’s observable activity. A citation or a referral is a stronger signal,…
A visible citation is when the AI displays or separately reports the page as a source. Not every retrieval includes a citation—the reporting keeps discovery, retrieval, and referral separate so signals don't get inflated. If you see a retrieval with a citation or a confirmed referral, that's stronger, but it's not proof of interest or a sale. Interpret signals over time rather than drawing conclusions from a single event.
AI Visibility Scan · 2026-08-24What specific baseline metrics should I track to prove progress?Start with a baseline of the items you’ll be measuring: factual consistency, coverage of key customer questions, completeness of service and location details, quality of visuals, and whether your prompts retrieve the approved facts. Then run changes, re-check with the same tests, and compare results over time. Remember: citations or recommendation frequency are secondary signals and not guarantees.
AI Visibility Scan · 2026-08-23How should I weigh a bare retrieval against a later citation or referral?Retrieval with no citation only shows AI activity, not a published source. It means material was fetched but without displaying a source. For stronger conclusions, rely on a confirmed referral or a visible citation. If you later see either, treat that as stronger evidence of movement rather than assuming ongoing interest.
After the scan, focus on gaps that block key customer questions or service details. Start by establishing a baseline of evidence: which pages were discovered, which were retrieved with or without citations, and where coverage is missing. Make small, testable changes to fill those gaps—update missing Q&As, improve location and service details, and ensure approved facts are reflected—then re-run the same checks to measure improvement. Remember, observable si…
AI Visibility Scan · 2026-08-20So, which signals should I track together to judge progress over time?Track a small set of signals over multiple time windows: discovery, retrieval, citations, and confirmed referrals. A retrieval by itself is weaker; a retrieval with a visible citation or a confirmed referral is stronger evidence. Don’t treat any single signal as proof of interest or a sale. Compare how these signals evolve over time to see genuine movement in visibility, not one-off spikes. If you see consistent retrieval plus a citation or a referral acro…
AI Visibility Scan · 2026-08-19If caching is in play, how should I trust the report’s signals?Caching means an AI might cite or reuse information without fetching the site at query time. The Digital Twin can’t record a request that never reached its infrastructure. That’s why we keep visible citations, first-party retrieval evidence, and confirmed referrals as separate signals rather than treating one signal as definitive. In practice, interpret signals by looking at multiple data points over time: when a retrieval comes with a citation or a referr…























