AEO Agency RFP: Questions That Reveal Real Capability

TL;DR

A 2024 Princeton-led study found that the strongest AEO tactics—adding statistics, quotations, and citations—lifted visibility up to 40% in generative AI responses, but that ceiling varied by domain and is often misquoted as an average. Most agencies calling themselves AEO shops have simply renamed SEO packages, with case studies still showing traffic and keyword-rank charts instead of evidence for AI citation behavior. The article’s question set targets five failure modes, starting with methodology: a credible vendor should explain how they map content changes to a hypothesis about language model retrieval, not just keyword edits. The highest-leverage RFP section demands proof of citation share-of-voice across specific AI platforms, not organic sessions or rank.

Bottom line: drop these five sections into your procurement process to force vendors to show real AEO capability, and expect 60–90 days for low-competition queries—any agency promising results in 30 days or guaranteeing a specific citation is overpromising.

Most agencies now list "AEO" or "GEO" on their services page. Few have changed what they actually do. Independent buyer guides published in 2026 keep landing on the same warning: many firms calling themselves AEO or GEO shops haven't changed their methods, they've just renamed existing SEO packages, and the giveaway is usually in the case studies — traffic and keyword-rank charts standing in for evidence of actual AI citation behavior (Scale Theory, 2026).

A standard marketing RFP won't catch that. It's built to compare creative quality, media plans, and account teams — not to test whether a vendor can demonstrate, with evidence, that content changes move citation behavior in a generative model. This piece is a question set built specifically for that gap: a template you can drop into your existing procurement process, organized around the five things that actually separate a credible AEO/GEO partner from a relabeled content shop.

Why the generic marketing RFP undersells this category

Direct answer: General RFP guidance is still useful as scaffolding. Buyers are advised to keep the document to roughly 8–14 pages, publish evaluation criteria transparently, share a budget range so proposals are comparable, and use at least three qualified evaluators rather than one stakeholder's gut call (Inventive AI, RFP Evaluation Criteria Best Practices; Inventive AI, Digital Marketing RFP Guide). Keep all of that. What's missing from those frameworks is category-specific: nothing in a generic scoring rubric forces a vendor to show their work on AI citation, as opposed to organic rank.

That's the gap this template closes. Five sections, each built to surface a specific failure mode buyers are currently reporting.

1. Methodology — is there an actual system, or a renamed SEO checklist?

Direct answer: Ask agencies to walk through their process in concrete terms: how they identify which entities and pages need work, what changes they make to content structure, and how those changes map to a hypothesis about how a language model retrieves and cites sources. Buyer guides consistently flag that real AEO/GEO work involves entity architecture, structured data, and off-site citation building — not just keyword-density edits with a new label (Scale Theory, 2026).

There's now a reasonably well-known academic anchor for this conversation. A 2024 Princeton-led study (with Georgia Tech, IIT Delhi, and the Allen Institute for AI) introduced "Generative Engine Optimization" as a formal research problem and tested nine content interventions across roughly 10,000 queries. The headline finding — up to a 40% relative visibility lift from the strongest tactics — is frequently over-quoted as an average; it was the ceiling for the best-performing methods (adding statistics, adding quotations, and citing sources), not a typical result, and effectiveness varied meaningfully by domain (Aggarwal et al., "GEO: Generative Engine Optimization," Princeton University). A vendor who can locate their own methodology relative to that research — where they agree, where their field experience diverges — is signaling they actually track the field. A vendor who's never heard of it is a signal too.

2. Evidence and citation standards — what counts as proof, to them?

Direct answer: This is the single highest-leverage section of the RFP, because it's the one most agencies will try to answer in generalities. Push for specifics: which AI platforms do they track citations across, how do they distinguish a brand mention from a cited/linked source, and how do they validate that a visibility change is attributable to their work rather than a model update or seasonal query shift?

Buyer guides are blunt about the alternative: ask for case studies that show citation share-of-voice improvement, not traffic growth or keyword position, and ask directly whether they can show clients actually appearing in AI-generated answers (NoGood, Best Answer Engine Optimization Agencies). If a case study's only exhibits are organic sessions and average rank, it's an SEO case study wearing an AEO label.

3. Measurement and reporting rigor

Direct answer: AI search attribution is genuinely unresolved as a discipline — there's no equivalent yet of a mature analytics standard for "this citation drove this outcome." The honest agencies say so. Guidance aimed at buyers explicitly warns that attribution from AI search is messy, and any agency promising clean, exact reporting from day one is overpromising (Scale Theory, 2026).

Ask what they report on a monthly or quarterly cadence, how often they re-test the same prompt set to control for model drift, and whether reporting is built from your data (your own prompt monitoring, your own analytics) or purely from their internal dashboard. Cross-reference this against the guaranteed-timeline red flag: multiple 2026 buyer comparisons note that agencies promising results inside 30 days are overpromising, with realistic ranges running 60–90 days for lower-competition queries and 3–6 months for competitive head terms — and that no reputable agency can guarantee a specific citation outcome, because none of them control what the underlying model chooses to cite (Position Digital, Top GEO Agencies 2026).

4. Technical scope — what they own vs. what you supply

This is where budget disputes usually start after signing, not before. Get explicit, in writing, on: who owns structured data / schema implementation, who owns the content itself (drafting vs. reviewing), who handles technical crawlability and site infrastructure changes, and who's responsible for testing across which AI platforms. A B2B-focused review of the GEO/AEO agency landscape notes that the strongest programs treat traditional search and AI search as one integrated system rather than a bolt-on service, and that agencies building or using their own tracking layer — rather than reselling a single third-party dashboard — tend to correlate with deeper technical capability (Growpad, Best GEO/AEO Agencies for B2B Tech).

5. Honesty about limits — the tell that matters most

Direct answer: The single most reliable signal across every buyer guide reviewed for this piece is how an agency talks about what it can't promise. Reputable sources describe the category as still being figured out industry-wide, and treat any guarantee of "AI placements" or a specific citation count as disqualifying (Position Digital, 2026). Ask directly: what's the realistic range of outcomes for a program like ours, what could go wrong, and what won't this fix. An agency that answers with hedges and specifics is more trustworthy than one that answers with confidence and round numbers.

One more practical check worth building into the process, independent of the written RFP: before you sign, run your own prompt set — the actual questions your buyers ask — against the models yourself, both for your brand and the agency's stated case-study clients. Buyer guides increasingly recommend this as a baseline step precisely because agency-reported visibility numbers are hard to audit externally (AEO Vision, Best AEO/GEO Agencies Directory 2026).

Sample RFP questions: strong answer vs. weak answer

RFP Question	Strong Answer Signals	Weak Answer Signals
Walk us through your methodology for improving AI citation.	Names specific interventions (entity clarity, structured data, source citations, content restructuring), explains why each maps to how models retrieve and synthesize answers, and distinguishes this from their organic SEO process.	Describes generic "content optimization" or "keyword strategy" with "AEO" or "GEO" appended; can't explain how it differs from what they'd do for organic rank.
Show us a case study with AEO/GEO-specific outcomes.	Shows citation appearance rate or share-of-voice change across named AI platforms, tied to a defined prompt set and time window.	Shows organic traffic growth or keyword rank improvement and calls it an AI search result.
How do you measure success, and how often do you re-test?	Explains a repeatable prompt-testing cadence, acknowledges attribution limits, and separates "we influenced this" from "the model changed on its own."	Promises a single dashboard number with no discussion of model drift, no re-testing cadence, no caveats.
What's the realistic timeline for results?	Gives a range (weeks to months depending on query competitiveness) and explains what depends on the client vs. the agency.	Promises results in under 30 days or guarantees a specific number of citations/placements.
What do you own technically, and what do we need to provide?	Explicit split: schema/structured data, content drafting vs. review, technical implementation, platform-by-platform testing — stated per line item.	Vague "full service" claim with no breakdown of client-side dependencies.
What won't this fix, or what's out of your control?	Names specific limits — model behavior they can't control, categories where AI search doesn't yet meaningfully affect demand, data they can't access.	Deflects with confidence; no substantive limitation named.

Run these five sections through your existing procurement scoring rubric — weighted the way your team already weights strategy, experience, and pricing — and you've adapted a generic marketing RFP into one that actually tests for the discipline you're buying. The agencies that answer these questions well are worth a paid pilot. The ones that answer with confident generalities are the ones the 2026 buyer guides keep warning about.

Sources: