White-Label GEO Reporting: The Agency Playbook

In short

A white-label GEO report puts your agency’s name behind a measurement, not just a design. Choose separately between a delivered PDF, a read-only client portal and team-wide administration. AI Labs Audit places these capabilities at different plan levels. Your purchasing brief should also specify the questions tested, the limits of the findings and the decision the client should be able to make.

Looking to sell AI visibility reporting under your own brand? Start with a deliverable your client can defend internally. A logo will not do that for you. This playbook covers commercial scoping and report acceptance, rather than repeating a portal setup tutorial or a guide to managing agency collaborators.

What should white-label GEO reporting actually cover?

GEO here concerns a brand’s visibility in AI assistant responses; AEO concerns providing answers that answer engines can use. A report explains what was observed, under which conditions and with which limitations. White labelling presents that work under your agency’s identity. It does not turn a single collection of responses into a universal statement about the market, and it does not transfer responsibility for interpretation away from your team.

Our view: the billable value lies in interpretation and decisions, not a replacement cover. A client needs to understand why an answer matters, what an absent mention means and which issue deserves attention. If that chain is missing, a better-looking PDF fixes nothing. Use this as your buying criterion: can the report support a clear conversation about evidence, uncertainty and the next decision?

Separate the PDF, the portal and agency operations

AI Labs Audit offers white-label PDF reports from Consultant. The read-only client portal starts at Consultant+: recipients view results through a secure link without creating an account. Centralised white labelling and shared team credits belong to Agency+. REST API and MCP access starts at Agent. These are different capabilities, not alternative names for the same package of services.

An agency delivering a standalone diagnostic may need a PDF but no portal. A team providing continuing measurement may need a client-facing viewing space. Several consultants working under one identity have another requirement: consistent delivery governance. Choose around that requirement, then check the current scope on the plans page. Buying by plan name alone is a poor substitute for defining what your team and client actually need.

Turn the proposal into acceptance criteria

Before collecting responses, write down what the client will receive and what the engagement excludes. Specify the brand, market, question language, comparison brands and interrogation modes. Separate responses drawn from a model’s native knowledge from responses using web search. Switching modes can change findings even when the agency has made no changes to the client’s website, content or external presence.

• Deliverable: a fixed document, viewing access, or both.
• Scope: questions, models, modes, language and collection date.
• Interpretation: verifiable observations and proposed priorities.
• Limitations: response variability and no guarantee of future citations.

This also protects the commercial relationship. It stops a client expecting revenue attribution from a tool measuring AI responses. A measurement engagement can inform an investment decision; it cannot, on its own, establish the return on that investment. Put the distinction in the scope rather than discovering the disagreement during the final presentation.

Use a real study to explain the numbers

Our public children’s toys study provides a concrete reporting example. Collected on 29 October 2026 for the French market, it publishes 20 questions, four models using web search and 80 analysed responses. It ranks 49 brands. Lego has 64% presence and 7.6% share of voice. Those figures are not two ways of expressing the same metric.

Published measure	Value	Reporting interpretation
Analysed responses	80	Observed response corpus, not user search volume
Ranked brands	49	Scope of the published ranking
Lego presence	64%	Presence in answers under the study protocol
Lego share of voice	7.6%	A separate metric from presence
95% confidence interval for presence	46–78%	Published uncertainty around the estimate

Keep those distinctions visible in a client report. These figures describe this study, this market and this collection. They are not global toy market figures or results achieved for an agency customer. We use them as a reporting example, not a customer testimonial. Translating the explanation into English does not change the market or language of the underlying research.

Do not hide uncertainty behind a ranking

Lego’s published presence confidence interval runs from 46% to 78%. Removing it leaves a cleaner headline, but a less faithful report. The study uses confidence intervals clustered by question: observations associated with one question should not be treated as completely independent experiments. The public methodology explains the collection and the role of those intervals. Preserve that context when choosing which numbers to put on a slide.

Another boundary matters just as much. A highly visible brand is not necessarily better than its competitors. The study measures presence in responses, not product quality. In a presentation, explain what you know, then what you do not know. Your agency does not lose credibility by showing uncertainty. It loses credibility when a marketing director discovers that a supposed market ranking was actually a bounded sample of AI answers.

Show the evidence before proposing a fix

A useful report allows the reader to connect a finding to the question and answer behind it. When discussing a missing mention, state whether the question named the brand. Repeating a name supplied in the prompt is not spontaneous visibility. AI Labs Audit distinguishes spontaneous presence from identity grounding: an assistant can produce an answer about a business while inventing characteristics of that business.

Your commentary should separate presence, accuracy and interpretation. An invented URL or unsupported certification does not become a success because the client’s name appears nearby. Do not copy a generated claim into the report as a verified fact. The public study labels assistant responses as unverified. Keep that caution when selecting an extract for your own presentation, even when the wording sounds plausible or flattering.

Make the portal access to evidence, not a promise of work

A PDF fixes a presentation at a point in time; a portal provides viewing access. The end client does not edit audit settings through the read-only portal. This separates the consultant’s workspace from the client’s reporting space. It does not remove your responsibility to explain the metrics. An uncommented dashboard can simply move confusion from a document onto a screen, where the same unanswered questions remain.

The client portal guide covers that specific use. The purchasing question here is different: does your contact need a fixed document for an internal committee, access to results, or both? Also define who receives the link and what may be shared. A viewing link should not be treated as general permission to redistribute client information outside the agreed scope.

Cost the service without inventing a fixed audit price

Credit consumption depends on configuration, including models, questions and modes. Do not convert a subscription into a guaranteed number of identical reports. Use the estimate shown before execution and account for your own preparation, critical review and presentation time. The software is only one component of delivery cost. More responses also mean more evidence to inspect, not automatically more useful advice for the client.

In your quote, separate collection, analysis, the presentation meeting and any corrective implementation. Your agency sets its service price; this guide promises neither a resale price nor a guaranteed margin. That separation avoids a familiar disagreement: a client assuming every future correction is included because the PDF contains a list of findings. Describe recommendations and implementation as distinct deliverables whenever the engagement treats them differently.

Run an acceptance review before delivery under your name

Read the report as someone who has never used the platform. Can you identify the observation date? Can you distinguish a measurement from a recommendation? Do the document and portal use the same names for the same metrics? Check business identity, namesakes, competitors and languages. An identity error matters more than a formatting inconsistency, however polished the cover may be.

Then compare outputs from the same audit. They should refer to the same measurement scope even if their presentation differs. Distinguish the AI-generated action plan, available from Agent, from market-specific AI recommendations, reserved for Agency+. These are not two names for the same deliverable. Your consultants can provide their own analysis, but should identify it as agency work rather than implying that it is an automatically included platform deliverable.

Buy clear accountability, not simply complete branding

The agency offering establishes the available delivery formats and capabilities. This playbook adds a decision filter: can you defend the measurement, its scope and its interpretation under your own name? If so, white labelling supports a coherent service. If not, adding a visual identity will not solve the underlying problem. A clear boundary is worth more than a broad promise that nobody can substantiate.

Before choosing a plan, take an audit you are authorised to use, prepare a presentation and ask someone to read it without an oral explanation. Record the unanswered questions. This acceptance exercise does not demonstrate a visibility improvement. It reveals whether your deliverable actually helps a client decide. That is a more useful basis for buying a reporting platform than a promise of future AI citations.

Un exemple de livrable, anonymisé

Voici ce qu'une agence remet à son client après un audit (données fictives, structure réelle) :

• Page 1, le verdict : la marque apparaît dans 8 réponses sur 30 (27 % de taux de mention), toujours en position 3 ou 4, jamais citée en source.
• Page 2, la comparaison : le concurrent A atteint 60 % de mentions et est cité en source dans 4 réponses, le concurrent B plafonne à 20 %. Le graphique montre l'écart, pas un score isolé.
• Page 3, le plan : 5 actions classées par effort et par impact attendu, chacune reliée au constat qui la justifie, avec la preuve de validation attendue.
• Pages 4 à 6, les détails : les réponses brutes par modèle, les URLs citées, les incohérences détectées et les éléments à corriger en priorité.

Le document sort sans aucune mention de l'éditeur de l'outique : logo, couleurs et pied de page de l'agence. C'est le livrable que l'agence signe et remet.

See all our resources on the subject in the AI visibility audit hub: guides, checklists and methodologies in one place.