How to Sell GEO/AEO to Your Clients as a Performance Marketing Agency

If you're running an agency with SEO, paid media, or content clients, you've probably noticed something: the AEO conversation is already happening without you.

CEOs and CMOs are acutely aware that their potential customers are increasingly relying on AI tools to research solutions and make decisions. We haven't had to push hard to start these conversations. In many cases, they're already happening at the executive level. It's also becoming a natural topic in SEO KPI discussions: as Google sends fewer clicks, the common realization is that AI Overviews are answering the top-of-funnel queries that teams once relied on for traffic.

The real challenge in selling AEO comes down to tying it back to measurable ROI.

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Measuring Zero-Click AEO ROI

This is the attribution model we've been using to connect AI visibility to business outcomes:

AI Visibility → Brand Search Demand → Pipeline Attribution → Revenue

That chain matters because AEO lives in a zero-click world. The measurement model has to reflect that reality. We break it into three layers:

Leading Indicators (AI Visibility) tell you whether your brand is showing up at all. Is it being mentioned as a recommendation? Is your onsite and offsite content cited as a reference in AI answers? What's your share of AI voice compared to competitors? What's your average recommendation position? These are the signals that tell you whether the work is actually moving the needle inside AI engines.

Mid Indicators (Demand Creation) tell you whether that visibility is translating into real demand. Are branded searches going up? Is direct traffic growing? Are people searching for your category and including your brand name?

Lagging Indicators (Revenue Impact) connect to the bottom line. Pipeline influenced by AI visibility, influenced revenue, win-rate improvements. This is where sales reps manually tie back attribution in CRMs, and where you prove the business case to leadership.

Where we've seen early traction is when leadership is in a heightened awareness state: after reading industry headlines or watching competitors surface in AI answers. Most executive teams are already asking, "Are we showing up?". The opportunity is to move that concern from fear-based curiosity into a structured, measurable strategy.

Key Learning: We initially led with an "AI Visibility Ratio" metric, an experimental composite score meant to simplify everything into one number. CEOs didn't particularly love it. It was too fuzzy and too abstract. So, we've moved away from leading with it. Sentiment tracking, on the other hand, has similar limitations. AI assistants rarely position one brand as definitively better than another. They frame things contextually, "Brand X is strong for Y" and "Brand A is better for B." While the directional value is there, it's difficult to translate into clean, quantitative metrics that executives want to see on a dashboard.

Would you like to know how your clients' brands actually show up in AI? Verbatim can help you build this practice.

The Prompt Problem: Most Teams Are Measuring Wrong

This is one of the most important things we've learned, and it catches almost everyone.

Most SEO-mature teams are already measuring AI visibility in some form. While we have our own proprietary platform, we're not dogmatic about tooling and are comfortable collaborating with teams using other solutions. We use similar underlying methodologies and signals as leading platforms, and we consistently see that when performance improves in our environment, it lifts across other tools as well.

The issue, though, almost always comes back to the prompts.

When we review the prompts teams are tracking, they're often not measuring in a meaningful way. Many rely too heavily on branded terms, which artificially inflates AI share of voice at the roll-up level and makes everything look rosier than it is. Others focus on informational prompts that sit too high in the funnel, the kind where AI simply answers the question without recommending anyone. In those cases, there's little to actually measure.

The takeaway: prompt selection is the foundation of a successful AEO engagement. Prompts must be strategic, commercially aligned, and tightly focused. Without that discipline, the data becomes misleading and the work becomes difficult to tie back to meaningful outcomes.

Position Yourself Now… Or Get Replaced

Here's a pattern we keep seeing: many clients are inclined to hire a dedicated AI expert rather than viewing their existing SEO team as the natural extension to handle AEO. If your agency doesn't establish itself early as the authority in this space, you risk being displaced. Over the next year, teams that aren't positioned as leaders here will likely watch clients bring in a separate, dedicated AEO partner instead.

Here's how to frame your positioning. At your agency, you want to communicate that you've invested in this discipline. That means having a dedicated AI expert building and leading your AI Visibility practice, an enterprise-grade approach that includes AI Visibility tracking, a tested framework refined over real client engagements, and proven experience across a diverse client base.

For context, our own practice has been refined over two years across 15+ clients spanning global HR and payroll, global SaaS, supply chain, local businesses, a publicly traded crypto asset management firm, and an AI and TV advertising platform. That depth of experience is what allows us to package this as a repeatable offering,  and it's what your agency can tap into without starting from scratch.

Verbatim can help you build this practice and offer it to your clients.

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The Story That Resonates

When you're pitching AEO to paid media, social, SEO, or CRO clients, here's the narrative that lands:

The funnel has compressed. Users are moving from awareness to consideration in a dramatically shorter timeframe. With just a few prompts, a potential customer can shift from information gathering to active consideration, sometimes within a single interaction with an AI assistant.

Brands need to understand how they're being represented inside these AI systems and act on that data to strengthen their presence. Those who do will be early adopters and leverage AI visibility as a meaningful driver of business growth. Those who wait will keep wondering why competitors keep surfacing and they don't.

How to Introduce AI Visibility: Start with the Audit

We start with a Light AI Visibility Audit & Strategy. This gives your client a clear understanding of how their brand shows up inside AI assistants and where the opportunity is.

Here's what the audit covers:

Prompt Research: True prompt data isn't available from any AI tool. Our approach is to research real user questions in communities like Reddit to get a directionally accurate view of how people naturally frame their problems. This works because AI interprets intent based on mathematical meaning and patterns. Synthetic prompts have been shown to closely mirror the answers generated from real user queries.

Prompt Measurement & Competitive Benchmarking: How often does the brand appear? How is it positioned? How does that compare to competitors? Are they recommended, mentioned, or ignored entirely?

Key Learning: Select an index of 10 prompts that represent a high-value topic for your client and measure them together over time. Once defined, do not change the prompts. This creates true apples-to-apples comparisons and clearly shows whether your AEO efforts are driving measurable impact.

Website Content Audit (AI Retrievability): How well is their site structured and optimized for AI systems to retrieve, understand, and cite their content? You can position this similarly to an SEO tech audit, but keep in mind that LLMs are less sophisticated than Google here. They can read HTML but have issues with JavaScript.

Off-Page Citations: Is the brand present in the third-party sources AI relies on to build its answers? You can position this as the natural evolution from link building. It doesn't replace link building, but adds a layer that increases the probability of getting offsite content used as grounding data for LLMs.

Community Positioning: How does the brand show up in Reddit, YouTube, and Quora? These communities heavily influence AI outputs.

This audit gives you a powerful sales narrative: "Here's exactly how AI sees your brand today, here's how your competitors are positioned, and here's the gap we can close."

It's strategic, measurable, and easy to position as the natural evolution of SEO, paid media, and content.

Focus Tight to Show Real Results

To demonstrate real movement, your focus must be tight. Choose a topic that is meaningful and commercially valuable, but not overly broad. The ideal scenario is a category your client is known for, yet competes against three stronger or more established competitors.

Select 10 prompts tied to that specific topic and track them as your index. Then align all AEO efforts around that theme: community engagement, citation building, service page optimization, new blog content, and review management.

When these efforts are coordinated around a single, focused topic, results move faster and more measurably. In most cases, a 3-month pilot is sufficient to demonstrate lift and justify continued investment.

The Full AEO Service Offering

Once the audit opens the door, here's what a full engagement looks like.

Full AI Visibility Audit & Strategy

A fully built-out prompt research initiative. Based on your client's personas, you dive into how their potential customers are using AI, select the search intent categories you want to target, and build a tightly focused campaign.

On-Site / Technical AI Optimization

Optimizing website content to increase the probability of being cited by AI. This typically means taking a set of service or product pages and building in AI visibility optimization on top of existing SEO work.

Wikipedia Page Creation & Editing

Wikipedia pages carry enormous weight in AI grounding data. Experienced Wikipedia editors who understand the platform's strict guidelines, editorial standards, and approval nuances can create pages for clients who don't yet have a presence and improve existing ones in a compliant way.

This starts with a formal assessment. Not every brand meets Wikipedia's notability standards, and publication depends heavily on credible third-party coverage. To qualify, a brand must have an authoritative presence across respected, independent publishers that have covered the company in an unbiased way. We evaluate the current landscape, determine the likelihood of successful publication, and provide a probability-based recommendation.

For brands that aren't ready yet, the output is a clear publication roadmap outlining the authority and coverage needed to qualify.

The publishing process follows Wikipedia's editorial standards and neutrality guidelines. The brand reviews for factual accuracy and policy compliance, and then the page goes through submission and publication following established editorial protocols. The client only pays the publishing fee if the page is successfully published and lasts six months.

After publication, the page is monitored to ensure it remains live and compliant. Adjustments, corrections, and editorial updates are made as needed to help the page stabilize and persist. For brands that already have a Wikipedia presence, the focus shifts to updating outdated information, improving structure and sourcing, and keeping the page accurate and aligned with current developments.

Citation Building

Based on citation data, this means engaging with industry publishers to increase the quality and quantity of mentions where AI pulls its grounding data.

Key Learning: Don't position this as "Digital PR." We've learned that when clients already have a PR team, they shut down and won't engage. Frame it differently.

There are two types of citation building, each with very different effort levels:

Mention Placement is highly manual, think traditional link building. The majority of effort goes into identifying and contacting publishers, often with low response rates. You may need to reach out to 20 publishers to secure one meaningful engagement. The focus is on positioning your brand within content that is already published and actively cited in AI-generated answers. By getting into sources that AI systems already trust and reference, you strengthen the likelihood of inclusion in AI responses.

Mention Publishing leverages a network of highly authoritative publishers to secure and publish strategic content that elevates the client's brand and increases the likelihood of being cited by AI systems. These placements are designed to strengthen authority signals, reinforce entity recognition, and improve inclusion within AI-generated responses.

Strategic Consulting for PR Teams: For clients in highly authoritative industries where AI citations come from top-tier media (Forbes, TechTarget, G2), the right approach is often to supply guidance to their existing PR team rather than running outreach directly.

Building a citation strategy from scratch is heavy lifting. Verbatim has the publisher network and methodology already in place.

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Community Engagement

Reddit is a major source of training and grounding data for AI models. Top-tier Reddit accounts and knowledgeable Redditors work within the community to authentically seed conversations that build genuine brand presence.

YouTube: Publishing comments on videos where AI is pulling citations helps seed conversations and increase mention count.

Quora: Established accounts and top commenters seed conversations to increase credibility for brands in another channel AI models reference frequently.

Review Management

A strategic approach to reviews that goes beyond simple monitoring. This includes identifying and prioritizing the platforms that matter most for the category, creating a stack-ranked review strategy, and leveraging available widgets and integrations to maximize visibility and credibility. Smart, compliant methods for generating more high-quality reviews are implemented alongside ongoing sentiment monitoring to identify trends, risks, and opportunities to strengthen brand perception.

Packaging AEO for Your Clients

Once you've validated the approach through a pilot, the natural next step is structuring it into a recurring service. We've found that a tiered monthly model works well here, because it gives clients a clear entry point and a path to scale as results come in.

A strong AEO package typically combines four core components: authoritative citation building (mention placements, mention publishing, and community engagement), on-site AI content optimization, AI-focused content creation, and ongoing AI visibility tracking across the major platforms.

Three-month minimums have worked well for us. That's generally enough time to demonstrate measurable lift on a focused topic and justify continued investment. It also protects the editorial relationships you're building with publishers: those take time to develop and shouldn't be cut short mid-pitch.

The key is keeping the packages turnkey. Focus on the tactics that consistently move the needle and are straightforward to deliver at scale. Self-serving "Best X" lists have performed well recently, but we've moved away from recommending them as a primary tactic, as the impact is likely short-lived. Securing placement within third-party "Best X" lists as part of a broader citation strategy provides more durable, long-term visibility.

For custom programs, on-page AI optimization and blog creation can be layered in, though these are typically easier for internal teams or partner agencies to handle. We recommend positioning them alongside the core packages rather than making them the centerpiece.

Ready to offer AEO as a service to your clients? Verbatim can help you build this practice from the ground up, or plug into your existing operations. Start with a free AI Visibility audit of your clients here.

The Bottom Line

The agencies that move on this now are going to own the client relationship when AI visibility becomes table stakes. The awareness is already there at the executive level. The measurement frameworks exist. The playbook works.

The question is whether your agency is going to be the one running it.

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