Run a repeatable GEO program across every client.
Standardize onboarding, measurement, evidence review and reporting while keeping every client’s market, competitors and data boundaries separate.
Focus the GEO program on decisions that matter.
Standardize onboarding, measurement, evidence review and reporting while keeping every client’s market, competitors and data boundaries separate.
Portfolio overview
Compare account health without mixing client data or baselines.
Reusable playbooks
Turn proven prompt, evidence and content workflows into service templates.
Client-ready reporting
Translate technical evidence into clear progress, risk and next actions.
A practical path from signal to action.
Keep measurement comparable while giving each finding supporting evidence and a next check.
What decides AI visibility for agencies
An agency's problem is not measuring one brand well; it is measuring many brands the same way, month after month, so that a client's number means something when compared to last month and to another client.
| The ruler has to be versioned, not just the data | Adding a model, enabling retrieval or extending a question set changes the measurement rather than the brand. Without a methodology version stamped on every stored run, a client will be shown an internal change as their own improvement. |
|---|---|
| Question sets are per client and must stay fixed | Every percentage has a question set as its denominator. Adding easier questions raises the average without anything improving, so a set that changes silently invalidates the trend it appears on. |
| Report absence, not just presence | The useful deliverable is the list of questions where the client is absent and a competitor is not, because that list is the content brief. A dashboard that only shows what went well gives an account manager nothing to sell next month. |
| Search demand for agency tooling is still thin | Keyword data for agency-specific terms such as white-label AI visibility reports and multi-client GEO platforms currently shows negligible volume. That does not mean the need is absent, but it does mean buyers are not searching for it yet, and pitches land through relationships rather than through search. |
Start with these three
- Stamp every stored run with a methodology version and refuse to compare across versions in client reports.
- Freeze each client's question set and restate history whenever you change it.
- Lead the monthly report with the questions the client lost, not the ones they won.
See the question, answer status and evidence together.
Sample UI demonstrates the evidence depth of a formal project.
Visibility evidence
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Questions teams ask before they start
Does a snapshot replace onboarding?
No. A snapshot is a limited sample. A formal project still needs confirmed markets, competitors and monitored prompts before continuous measurement begins.
Will snapshot data be charged twice in the App?
Not by default. Claimable snapshot results can be inherited, while a new formal run starts only after onboarding is confirmed.
Can teams measure more than one market?
Yes. Markets and languages should be treated as separate measurement segments so results remain comparable.
How long before results are meaningful?
A single run gives a baseline. Trends need several runs, because one sample cannot separate a real change from model variance.
What is actually needed to get started?
One domain. The brand profile, traceable facts and buyer questions are generated from it and stay editable before any formal run.
Who on the team uses this day to day?
Usually whoever owns content and organic growth. The measurement side needs no engineering work, and publishing always stops at a human approval step.
Turn AI visibility into a repeatable growth system.
Create a project, confirm your market and start measuring the questions that matter.