Your last SEO RFP likely requested domain authority scores and backlink velocity. That framework is now obsolete. With 94% of B2B buyers consulting large language models during their purchasing journey, judging a new partner by old metrics is a costly mistake. You need AEO agency vetting that focuses on performance in generative search, not just traditional organic rankings. The core challenge is distinguishing genuine expertise in AI-driven visibility from a standard SEO agency repackaging keyword tactics. A simple list of questions won’t reveal this difference. Instead, you need a structured process to verify if the vendor can track citations, manage AI-specific data ingestion, and influence the sources that language models trust. This approach ensures you are investing in a partner who understands the mechanics of the new search landscape, rather than one guessing at it.
What to Ask in Your First Call
Traditional vendor evaluation relies on metrics like domain authority and organic traffic, but these signals fail for generative search. In AEO, the outcome is not a click, but a citation. To assess a vendor, you must shift your focus from rankings to citation rate and share of voice in AI outputs. This shift is the core of effective AEO vendor selection.
Start your screening call with two specific questions to test operational depth. First, ask: “How do you measure AI search visibility?” A competent partner will reject the notion of a single “overall” score and instead discuss model-specific tracking. Second, ask: “Which specific surfaces do you track?” Listen for explicit mentions of ChatGPT, Perplexity, Google AI Overviews, and Claude. If the agency speaks in generalities without naming these distinct environments, they are likely repackaging traditional SEO.
A strong answer includes the naming of specialized tracking tools like Profound, Peec AI, or AthenaHQ. More importantly, the agency should explain a methodology for competitor benchmarking on high-intent buyer prompts, not just generic brand terms. If the response is vague or lacks dedicated tools for specific AI models, treat it as a red flag. Vague claims about “AI visibility” usually indicate a lack of the technical infrastructure required to prove their value in a 90-day window.
Verifying the 90-Day Service Scope and Pricing
A generic retainer is useless in generative search. The AEO service scope must be tied to specific technical and off-page deliverables that directly influence how language models perceive your brand. When evaluating AEO pricing models, look for a contract that names the exact work involved, rather than vague hourly blocks or generic “SEO support.”
The most critical questions to ask during the evaluation call focus on methodology. Specifically, ask: “How do you earn citations?” A credible agency will explain that citations are earned through a dual approach. On one side, you need on-page structural optimization to ensure your content is easily parseable by AI scrapers. On the other, you need off-page consensus building to establish your brand as a trusted entity across the web. If an agency only mentions content creation without discussing these two pillars, they are likely repackaging traditional SEO.
Before signing any contract, require a baseline audit. The agency must map your brand’s current footprint across both product-specific and category consideration queries. This audit should clearly show where competitors are currently replacing your brand in AI-generated answers. Without this baseline, you have no way to verify progress later.
The 90-day timeline should be structured as a series of contract-bound milestones:
- Month 1: Foundation. This phase focuses on model-output audits. The agency should be identifying which prompts currently trigger your competitors and establishing the technical baseline for indexing.
- Month 2: Execution. This is the on-page structuring phase. Expect specific deliverables like schema deployment (Organization, Product, SoftwareApplication) and page restructuring to ensure direct answers appear in the first 100–200 words of key sections.
- Month 3: Optimization. This month involves off-page PR launches and consensus building. The agency should be managing your presence on high-weight platforms like G2, Capterra, and niche communities where LLMs look for validation.
Be wary of two common traps. First, the “30-day guarantee.” This is unrealistic because LLM indexing cycles are not that fast. Real changes in citation rates typically take longer. Second, the unstructured retainer. If the proposal lists open-ended hours without named deliverables like “deploy FAQPage schema” or “restructure comparison pages,” you are paying for time, not outcomes.
When aligning pricing with these milestones, ensure the retainer covers both the technical work and the off-page outreach. A fair pricing model should reflect the cost of setting up llms.txt files, implementing advanced schema, and securing mentions in trusted external sources. If the price seems too low to cover both, the agency is likely skipping the off-page consensus building, which is essential for long-term visibility in generative search.
Testing Technical Depth and Buyer Prompt Patterns
Verifying technical execution is where many engagements diverge from promise to performance. A superficial approach treats the website as a static document, whereas LLM web scrapers parse site code differently than search engine web crawlers, often failing to parse complex JavaScript frameworks. Ask your prospective partner about their server-side rendering strategy to ensure your content is actually visible to AI agents. The conversation must cover the implementation of an llms.txt file, a markdown-formatted text file created in the root directory specifically for LLM ingestion, alongside advanced schema markup. A competent agency will reference nested Organization, Product, SoftwareApplication, and FAQPage schemas as essential signals for entity clarity.
Off-Page Citation Footprint and Community Consensus
Technical structure alone does not create authority; LLMs heavily weight external consensus. The off-page strategy must extend far beyond traditional guest posts. Because LLMs treat discussion platforms like Reddit and Quora, as well as software review directories like G2, Capterra, and TrustRadius, as trusted sources, your service scope includes managing presence on these channels. An agency that ignores these high-trust community spaces is missing a critical layer of the citation footprint. They should outline a plan for executive thought leadership and community engagement that reinforces the brand’s authority in the specific vertical you operate in.
Understanding B2B SaaS Buyer Behavior
The quality of an agency’s questions reveals their understanding of your market. Do they understand software unit economics and the complexity of multi-stakeholder decision groups? They must be able to handle specific query types, including comparison, alternative, and use-case prompts. For example, a prompt asking for “best [Your Category] software for [Specific Use Case]” requires a different optimization strategy than a general brand query. If the agency cannot explain how they target these high-intent buyer prompts, they are likely applying a generic SEO playbook to an AEO problem.
Requiring Prompt-Level Proof of Performance
Finally, demand specific evidence rather than broad claims. Ask for a case study that includes a specific client vertical, the exact buyer prompt tracked, and a clear before-and-after baseline. A strong example might show citation recurrence moving from 0% to 45% within 90 days. This level of detail proves the agency can measure what actually matters: Citation Recurrence Rate, defined as the percentage of time a brand appears when a prompt is run across multiple test variations. This data point is far more valuable than any traffic report, as it directly correlates with your ability to influence the AI-generated answers that now shape B2B vendor shortlists.
AEO Agency Questions for the 90-Day Review
The 90-day checkpoint is where vetting shifts from promising potential to verifying performance. Reporting at this stage must move beyond static screenshots of single AI responses. A professional partner tracks dynamic metrics like Citation Recurrence Rate, which measures the percentage of times a brand appears across multiple prompt variations. They also monitor Share of Voice (SoV) and Answer Accuracy & Sentiment. If a proposal only includes a single screenshot of a favorable answer, it lacks the depth required for genuine generative search oversight.
Connecting these visibility metrics to actual pipeline revenue is critical. According to HubSpot data, visitors arriving via chat-based AI answers achieve 3x higher lead-to-opportunity conversion rates than those from standard search. However, because AI tools rarely pass standard referrer tags, direct attribution is difficult. You should ask how the agency tracks this impact, likely through self-reported attribution fields in your CRM that capture how leads discovered you.
Setting Realistic Timelines
Expect specific phases of growth rather than immediate revenue spikes. During the first two weeks, the focus is technical indexing and schema deployment. From months one to three, baseline citation performance typically shifts from a low 5-15% rate to a 30-50%+ share of voice. Significant pipeline and revenue impact usually follows in months three and four, once the brand becomes a consistent source in AI model recommendations.
Red Flags to Watch
During the 90-day review, watch for these five signs of a traditional agency in disguise:
| Red Flag | Indicator | Why It Matters |
|---|---|---|
| Click-Only Focus | Reports emphasize traffic/clicks | Ignores the core goal of citation and answer inclusion |
| Vague AI Claims | Uses “AI-driven” without specific tools | Suggests lack of dedicated AEO methodology |
| No Dedicated Tools | Lacks platforms like Profound or Peec AI | Makes tracking citation rate and SoV impossible |
| Website-Only Focus | Ignores Reddit, G2, or Quora | Misses high-trust consensus sources LLMs rely on |
| Unrealistic Timelines | Promises results in 30 days | Disregards LLM indexing cycles and data propagation lag |
These indicators reveal whether the partner is actually executing an AEO service scope or simply repackaging legacy SEO tactics.
Frequently Asked Questions
How is AEO different from traditional SEO?
AEO optimizes for direct citation in AI-generated answers using semantic clarity and structured data, whereas SEO targets search result rankings via keywords and backlinks.
What are the key metrics for measuring AEO success?
Citation rate, share of voice in AI answers, and query coverage are the core metrics, as the goal is to be the cited authority in AI responses on platforms like ChatGPT and Perplexity.
What signals an agency is just repackaging SEO as AEO?
Proposals that emphasize keyword rankings and organic traffic without mentioning citation-based metrics or dedicated tracking tools for specific AI models.
The shift in B2B buyer behavior is not a trend to be managed; it is a permanent structural change. With 67% of buyers preferring a rep-free experience and AI chatbots now the primary source influencing vendor shortlists, the way you evaluate your marketing partners has fundamentally altered. Vetting an AEO agency is no longer about checking a box for compliance; it is a direct investment in your future pipeline. When you move from passive visibility to active citation in AI-generated answers, you are securing the ground on which your next cycle of revenue will be built. The quality of your vetting process determines whether you capture that shift or get left behind by competitors who are already being cited. As you review the proposals on your desk, consider the final distinction: are you tracking the wrong outcome (ranks) or the right one (citations)? The answer to that question will tell you more about the agency’s intent than any contract clause ever could.
