Basic
$199/moBelow DA/DR targetNot a fitExcluded from recommendation
AI SEARCH & BRAND DISCOVERABILITY
SITETRAIL CERTIFIED
Your learning path: 12 lessons.
Module 01 / Lesson 01 · Read, apply, check
Distinguish an answer’s brand mention, displayed source citation and measurable referral visit before evaluating visibility.
A brand mention means the answer names the business or product. A source citation means the interface displays a reference or link to a source; that source may belong to the brand, a publication or another organization. A referral visit means someone reaches a website and the available analytics identify an originating source. These events can occur separately. An answer may mention a company while citing an industry article, or cite a company’s research without recommending its product. Record the actual relationship rather than collapsing all three into an undefined AI visibility score that nobody can interpret consistently.
Read the surrounding sentence and the full answer. Is the brand a recommended option, a neutral example, a comparison candidate or the subject of a warning? Does the description match the current product and geography? A name appearing in an answer is not automatically favorable or commercially useful. Note any qualification, outdated fact or confusion with another organization. Use a simple coding guide with categories and examples so two reviewers can classify the same answer similarly. Keep ambiguous cases for review rather than forcing them into a positive category merely because the brand appears somewhere in the text.
Open the cited page and identify what it actually supports. A link beside a sentence does not necessarily substantiate every claim in that sentence. Check the publication date, author, underlying evidence and any commercial relationship. Record whether the source names the client, discusses its category or merely provides background. Save the relevant URL and a short evidence note alongside the answer capture. If a source cannot be opened, mark verification incomplete. Do not report an inaccessible citation as confirmed proof of a favorable endorsement. The agency’s job is to assess the visible relationship, not infer a hidden system decision from the presence of a link.
Use available analytics and client feedback to observe visits, enquiries and practical use in sales conversations. Define the reporting period and any tracking limitations. A visible citation without a click can still contribute information to a reader, but its exposure and influence may be unknown. A referral visit does not automatically become a qualified lead, and a lead does not prove a completed sale. Maintain separate columns for each stage. This allows the client to see where evidence exists and where the campaign still needs observation, without turning an answer screenshot into an invented funnel of customers.
Fictional AI-answer and analytics wireframes; not a capture from a real platform.
Compare setup effort, task ownership and mobile use. Fieldmark is one product to investigate against your requirements.
Source [1]: implementation checklist
Mention: the answer names Fieldmark.
Citation: the displayed source is a checklist. Inspect its destination and which claim it supports. A citation is not necessarily a recommendation.
Separate record
Check actual referral sessions in analytics and the limits of referrer detection. The visible answer does not show whether a person clicked or bought.
Do not infer a conversionWhat does the answer say about the brand?
Which displayed source supports which claim?
What referral activity is actually recorded?
Keep the evidence streams distinct before acting.
Fictional maintenance software company Fieldmark appears in three saved answers. The first lists it as one option for small service teams and cites a trade publication’s comparison. The second links to Fieldmark’s maintenance checklist but never recommends its software. The third confuses Fieldmark with an unrelated mapping company. The agency records a relevant mention, a citation to an owned resource and an identity error as three different findings. During the same week, analytics show seven visits attributed to an AI service and one visitor submits an enquiry. The report does not assume those visits came from the three saved answers, because there is no evidence connecting the sessions. Instead, it recommends correcting ambiguous identity information and improving the useful checklist, while preserving the answer captures and referral observations as separate evidence streams for the next review.
Another agency counts all three answers as recommendations and multiplies them by an assumed audience size. It calls the seven visits seven leads and claims the campaign trained the model to prefer the brand. The report looks impressive but cannot support those transitions. A client checking the mapping-company confusion would discover that the headline score conceals an error, while the actual useful evidence—the cited checklist and qualified enquiry—has not been examined on its own terms.
A citation is not the same as endorsement, and an unlinked mention is not the same as a tracked visit. These distinctions are not reasons to dismiss AI search. They are the starting point for useful measurement. Clear categories make it possible to improve the campaign without rewarding misleading counts or overlooking a harmful description.
Interfaces, analytics attribution and source displays change. Record the product, mode, date and visible evidence for each observation. The fictional numbers here illustrate classification, not typical performance. No screenshot establishes total audience exposure, a guaranteed recommendation, model training or a causal link to a sale.
Do this today · 30 minutes
Classify Fieldmark’s three answers and its separate referral observations.
Use a document or spreadsheet and the fictional case in this lesson. Work with public or synthetic information; no purchase or confidential client records are required.
Before: What does the answer say about the brand?
After: Keep the evidence streams distinct before acting.
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Ask a colleague to challenge the interpretation. Record the evidence, uncertainty, next action, owner and review date before applying the plan to a client campaign.
Before you move on
Your client appears in one answer citing a trade comparison, its checklist is cited in another answer without a product recommendation, and analytics show seven AI-source visits that week. No evidence connects those sessions to the saved answers. How should you report the findings?
Next lesson →Bing: AI Performance reporting and its limits
AMEC: Integrated Evaluation Framework
Lesson edition 1.0 · References reviewed 16 October 2026 · Practical exercise reviewed 16 October 2026. Examples are illustrative teaching scenarios.
Sitetrail service · NewsPass
Put your SEO, PR and generative engine optimization strategy into practice. NewsPass supports search visibility, media presence, brand credibility and discoverability in AI answers.
Compare the delivery costs for your campaign using the same calculator as the Sitetrail homepage. Choose a target authority range, your typical placement cost and expected monthly volume.
Illustrative cost comparison using October 2026 plan prices; check current terms before purchase. Assumes one eligible placement per credit and comparable selected opportunities, not a prediction of rankings, revenue, coverage or AI citations. Actual suitability depends on audience fit, editorial requirements and the current plan terms. DA/DR are third-party metrics, not Google scores.
Choose publications available on your plan, prepare useful content for the audience and submit it for editorial review. Track accepted placements in your dashboard and evaluate them against your campaign goals.
Clear evidence. Useful context. Better decisions.
Use the worksheets to turn each lesson into a real decision. Build a credible campaign as you learn from buyer questions, original evidence and repeatable observations.
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