Sooner or later, a client asks the question. "I searched for our category in ChatGPT and a competitor came up. We didn't. What are we doing about that?"
For agencies, that question is both a threat and an opening. Clients who hear nothing from their agency about AI search will eventually find someone who talks about little else. Agencies that bring it up first get to define the service.
This guide covers how agencies can add generative engine optimization to their offer: what to sell, how to run it, and how to report it in a way clients understand.
Most of the work that improves AI visibility is work agencies already do. Content strategy, digital PR, technical SEO, structured data and review management all feed the signals AI models rely on. What is new is the measurement layer and the framing.
That means agencies do not need to rebuild their teams. They need a clear audit process, a reliable way to track AI answers, and a reporting format that connects familiar work to a new outcome. If you want the underlying concepts first, our introduction to GEO is a good primer to share with your team.
An audit is the easiest service to sell and the best way to learn. It has a clear scope, produces a tangible document, and almost always surfaces problems the client did not know existed.
A solid audit answers four questions:
Our GEO audit guide walks through the full checklist, and our competitor audit method covers the comparison piece in detail.
The single biggest quality lever in any audit is the prompt set. Build it with the client's sales and support teams, using the questions real buyers ask. We explain the process step by step in how to build a prompt set for tracking AI visibility.
Involving the client here has a second benefit. When they recognise the prompts, they trust the results.
An audit that ends with a list of problems is not worth much. Clients pay for a plan. Group recommendations into three buckets so the client can see what happens when.
| Bucket | Typical actions | Timeline |
|---|---|---|
| Foundations | Fix inconsistent brand descriptions, add Organization markup, update review profiles, correct outdated facts | First 30 days |
| Content | Create comparison and use-case pages, restructure FAQs, add clear answers to key buyer questions | Days 30 to 90 |
| Authority | Earn inclusion in category roundups, grow review volume, secure expert commentary and coverage | Ongoing |
This structure maps well onto the phased approach we laid out in our 90-day AI visibility roadmap, which you can adapt directly into a client proposal.
After the audit, the natural next step is monthly tracking. This is where many agencies stumble, because running prompts by hand across five assistants does not scale past one or two clients.
Whatever tooling you use, the requirements are the same:
AI answers vary from run to run, so frequency matters. Daily tracking lets you report on trends rather than on a single snapshot that might have been an outlier.
Clients do not want a spreadsheet of AI answers. They want to know whether things are getting better and why. A good monthly report fits on two or three pages and covers five things.
Out of all brand mentions across the prompt set, what percentage belong to the client, and how does that compare with the main competitors? This is the headline number. Our guide to tracking share of voice in AI answers explains how to calculate it consistently.
A simple table showing mention rate in each assistant. Clients are often surprised to learn they are strong in one and absent in another, and it helps explain why different tactics matter.
Split results by the prompt groups: category discovery, use case, comparison, problem and branded. This shows where the client is winning new buyers and where they only show up when someone already knows their name.
List any incorrect facts the assistants repeated, and what you are doing to fix them. This is often the section clients care about most, because wrong pricing or a discontinued product in an AI answer is a direct commercial risk.
Show which sources the assistants cited when they mentioned the client or competitors, and connect them to the work you did that month. "The roundup we pitched in June is now cited in Perplexity answers for three of our category prompts" is the kind of line that renews retainers.
A consistent audit document makes the service repeatable and easier to sell. The structure below works well for most clients and keeps the document to around ten to fifteen pages.
Include a handful of real answer excerpts, especially ones where a competitor is recommended and the client is not. Nothing makes the problem concrete faster than seeing the actual words a buyer would read.
"But we rank first on Google for that." Show them the answer. Ranking and being named are different outcomes, and the audit is the evidence.
"Can't we just tell ChatGPT to mention us?" Explain that models reflect what the web says about a brand, which is why the plan focuses on sources and content rather than tricks.
Agencies we talk to generally use one of three models:
Whichever model you choose, make sure your tooling costs scale with the number of clients and prompts. Per-scan or per-prompt pricing is often easier to pass through than flat seats, especially while the service is new.
The fastest way to lose a client on GEO is to overpromise. No one controls which brands an AI model names, and anyone who guarantees citations is guessing.
Be clear about what is realistic:
Research on generative engines supports investing in well-sourced, evidence-rich content: the original GEO study found that adding citations, statistics and quotations improved visibility in AI-generated answers (Aggarwal et al.). That is a direction, not a guarantee, and it is worth saying so.
GEO works best when it is connected to the rest of the retainer rather than sold as a separate experiment. Content teams get a sharper brief, because the prompt set shows exactly which questions the client needs to answer. Digital PR gets a clearer target list, because the source analysis shows which publications and roundups the assistants actually read. Technical SEO gets a new reason to prioritise structured data and crawlability.
Framed this way, AI visibility is not a new silo competing for budget. It is a measurement layer that makes the work you already do easier to justify.
AI visibility is a natural extension of what good agencies already do. Lead with a paid audit, turn findings into a phased plan, fold tracking into retainers, and report on share of voice, coverage, accuracy and sources.
The agencies that start now will not just keep their clients. They will be the ones clients call when the question comes up.
Most agencies do best starting with a paid audit, then folding ongoing tracking into existing SEO or content retainers. A separate line item makes sense once you have case studies and a repeatable process, because clients understand what they are buying.
Frame it as the same goal on a new surface. SEO asks whether you rank for a search; GEO asks whether you are named in the answer. Then show them a few real prompts from their market where competitors appear and they do not. That usually lands faster than any definition.
Promise process and measurement, not specific citations. No one controls which brands a model names. You can commit to a baseline, a prioritised plan, consistent tracking and regular reporting on share of voice, accuracy and cited sources.
Bold GEO monitors how your brand is cited across ChatGPT, Perplexity, Gemini, Claude, and Copilot on a daily refresh. 7-day free trial, no credit card.