The Enterprise AEO RFP Template: Questions to Ask AEO Providers

The AEO vendor landscape is full of noise

AI visibility optimization is a new category, and that means the vendor landscape is chaotic. SEO agencies have bolted "AEO" onto their service pages. PR firms claim that media placements alone drive AI citations. Content agencies promise that writing more blog posts will make you visible to ChatGPT. And a handful of actual AEO specialists are doing the real work.

The problem for enterprise procurement teams is obvious: everyone sounds the same. The vocabulary is new, the metrics are unfamiliar, and there is no established framework for evaluating these vendors.

That is what this template fixes. We built it based on the questions that actually separate genuine AEO capability from repackaged SEO services. Use it as-is or adapt it to your organization's procurement process.

Section 1: Measurement methodology

This is the most important section of the RFP. If a provider cannot clearly explain how they measure AI visibility, nothing else matters.

Questions to ask

Q1: How do you measure AI visibility, and across which platforms?

Good answer: "We monitor citation rates, mention frequency, and recommendation positioning across ChatGPT, Claude, Gemini, DeepSeek, and Perplexity. We run structured prompt sets weekly, tracking whether your brand is named, in what context, and how often relative to competitors."

Bad answer: "We track your SEO performance and correlate it with AI traffic." This tells you they have no AI-specific measurement at all.

Q2: How many prompts do you test per reporting period, and how are they selected?

Good answer: "We test 100-200+ prompts per reporting cycle, selected based on your target personas, buying journey stages, and competitive landscape. The prompt set evolves as we learn which queries matter most for your category."

Bad answer: "We test a representative sample." No specifics means no methodology.

Q3: How do you handle the non-deterministic nature of AI responses?

Good answer: "AI models give different answers to the same prompt over time. We account for this by running each prompt multiple times across multiple sessions, then calculating mention rates and citation consistency rather than treating any single response as definitive."

Bad answer: "We take screenshots of AI responses." Screenshot-based reporting is not measurement. It is anecdote collection.

Q4: Can you show me a sample report from an anonymized client?

This is a litmus test. A provider with real methodology will have a standardized reporting format they can share. If they cannot show you what a report looks like before you sign, they are building their process on the fly.

Red flags in this section

Section 2: Platform coverage and multi-model strategy

Enterprise brands cannot afford to optimize for a single AI platform. Each model has different training data, retrieval mechanisms, and biases. A provider that only works with ChatGPT is leaving most of the AI landscape uncovered.

Questions to ask

Q5: Which AI platforms do you actively optimize for, and how does your strategy differ across them?

Good answer: "We optimize across ChatGPT, Claude, Gemini, DeepSeek, and Perplexity. Each model weights different signals. ChatGPT relies heavily on web-sourced entity information. Claude emphasizes structured, well-reasoned content. Gemini pulls from Google's knowledge graph. We tailor entity and content strategy to each platform's characteristics."

Bad answer: "We focus on ChatGPT because it has the largest market share." Market share is irrelevant if your buyers use Claude or Gemini.

Q6: How do you track platform-specific differences in how your brand is cited?

Good answer: "Our reporting breaks down visibility by platform. You will see your citation rate on ChatGPT separately from Claude, Gemini, and DeepSeek. This allows us to identify where you are strong and where you have gaps, and prioritize accordingly."

Bad answer: "We give you an overall AI visibility score." A single number hides critical platform-level gaps.

Q7: How do you adapt when AI platforms update their models or change their retrieval methods?

Good answer: "Model updates happen frequently. We monitor them and re-run our measurement suite within days of major updates to detect shifts in citation patterns. We adjust strategy based on what changes."

Bad answer: "Our evergreen content strategy works across all updates." This means they are not monitoring model changes at all.

Section 3: Entity strategy and technical implementation

AEO is not just content marketing. It requires technical work on entity clarity, structured data, and citation architecture.

Questions to ask

Q8: What does your entity audit process look like?

Good answer: "We audit your brand's entity presence across your website, structured data, industry directories, review platforms, Wikipedia and Wikidata, social profiles, and press coverage. We map inconsistencies in naming, categorization, and description, then build a remediation plan to create a clean, unambiguous entity profile."

Bad answer: "We review your website and social media." An entity audit that ignores third-party sources misses half the picture.

Q9: What structured data implementation do you recommend and manage?

Good answer: "We implement Organization, Product/Service, Person, FAQ, and HowTo schemas as a baseline. We also build SameAs connections to your authoritative external profiles. We validate quarterly and monitor for breakage after CMS updates."

Bad answer: "We add schema markup to your blog posts." Blog-only schema is table stakes. Entity-level structured data is what moves AI visibility.

Q10: How do you approach citation architecture, meaning the way your content is structured to be citable by AI models?

Good answer: "We restructure content to include explicit question-answer pairs, comparison tables, clear factual claims, and recommendation-worthy statements. Each piece of content is designed so an AI model can extract a clean, attributable answer."

Bad answer: "We write high-quality content." Content quality and citation architecture are different things.

Section 4: Reporting and transparency

Clear, actionable reporting is non-negotiable for enterprise engagements.

Questions to ask

Q11: What is your reporting cadence, and what does each report include?

Good answer: "Monthly comprehensive reports with weekly status updates. Each monthly report includes citation rates by platform, competitive benchmarking, prompt-level results, trend analysis, and specific recommendations for the next period."

Bad answer: "Quarterly reports." Quarterly reporting in a space that moves this fast means you are flying blind for months at a time.

Q12: How do you benchmark our performance against competitors?

Good answer: "Every report includes a competitive leaderboard showing your citation share relative to named competitors across all monitored platforms. You will see who is gaining, who is losing, and why."

Bad answer: "We focus on your brand's absolute performance." Without competitive context, you have no way to evaluate whether your results are good or if competitors are simply outpacing you.

Q13: Can I access raw data, or only your interpreted reports?

Good answer: "You get both. Our platform gives you access to raw prompt-response data so your team can run their own analysis. We also provide interpreted reports with strategic recommendations."

Bad answer: "Our reports contain everything you need." If you cannot access raw data, you cannot verify their methodology or run independent analysis.

Section 5: Results and track record

Questions to ask

Q14: Can you share anonymized case studies showing AI visibility improvement over time?

Good answer: Shows month-over-month citation rate improvement with specific numbers, identifies what interventions drove the improvement, and demonstrates sustained growth rather than one-time spikes.

Bad answer: Shares testimonials or vague success claims without data.

Q15: What does a typical client's first 90 days look like in terms of measurable outcomes?

Good answer: "In the first 30 days, we establish baselines and implement entity foundations. By day 60, we typically see initial citation appearances on at least two platforms. By day 90, clients average a measurable increase in citation rate with specific competitive positioning improvements."

Bad answer: "Results vary." Results do vary, but a provider with experience should be able to describe typical trajectories.

Q16: What happens if we stop working with you? Do citation gains persist?

Good answer: "Entity and structural improvements are durable. If you stop active optimization, your existing entity foundation and structured data continue to benefit you. But citation rates plateau and eventually decline as competitors continue investing, models retrain, and new content displaces old. AEO is ongoing, not one-and-done."

Bad answer: "Your gains are permanent." Nothing in AI visibility is permanent. Models change, competitors evolve, and stale content loses relevance.

Section 6: Pricing and contract structure

Questions to ask

Q17: How is your service priced, and what is included at each tier?

Look for clear, predictable pricing that scales with the scope of work. Beware of providers who price based on "number of citations achieved," because that suggests they are either gaming measurements or making promises they cannot control.

Q18: What is your minimum contract term, and why?

Good answer: "We recommend a minimum six-month engagement because AEO results compound over time. The first 60-90 days are foundation-building. Months 4-6 are where compounding citation growth becomes visible."

Bad answer: "We require a 24-month commitment." Excessively long commitments in a new category signal low confidence in retention through results.

Q19: What does your team structure look like for an enterprise engagement?

Good answer: Names specific roles (strategist, technical implementer, content specialist, analyst) with clear accountability. Enterprise engagements need dedicated attention, not a shared pool of generalists.

The scoring framework

When evaluating responses, use this weighted scoring framework:

Score each category 1-5. Multiply by weight. Any provider scoring below 3.5 overall is likely not a genuine AEO specialist.

What this RFP reveals

The real value of this RFP is not just in selecting a vendor. It is in forcing clarity about what AEO actually requires. If you send this to five providers and three of them cannot answer the measurement questions coherently, you have learned something critical about the market.

At OnlyAEO, we built our practice around the exact capabilities this RFP evaluates: multi-platform measurement, entity-level strategy, transparent reporting, and proven compounding results. We welcome these questions because they are the questions that matter.