Choose the right AEO agency: 24 questions for B2B SaaS VPs

Updated December 8, 2025

The complete AEO Agency Evaluation Spreadsheet (Excel) includes all 24 questions, vendor scorecard with auto-calculated weights, and side-by-side comparison matrix.

Your CEO just forwarded you a Slack message from a prospect. They evaluated three vendors in your category, signed with a competitor, and your sales team never heard about the opportunity.

When you asked how they found the shortlist, the answer was simple: "I asked ChatGPT."

Nearly half of B2B buyers now use AI tools to research software, and a recent Forrester study found that 89% of B2B buyers rely on generative AI for self-guided research. Your traditional SEO agency optimizes for Google rankings, but they have no methodology for getting your brand cited when prospects ask AI for recommendations.

You can measure this gap. If your brand appears in only 5% of relevant AI answers while competitors dominate the other 95%, you're invisible to the fastest-growing segment of your market.

You need different criteria to evaluate an AEO agency than you used to hire your SEO firm. You cannot use your traditional SEO scorecard to assess an AEO partner. This guide gives you 24 essential questions, organized by category, to identify agencies with genuine Answer Engine Optimization expertise.

Why your SEO RFP fails for AEO

The way your buyers discover brands has shifted. Traditional SEO optimizes web pages to rank in the "10 blue links" of search results. Answer Engine Optimization aims to get your content cited directly within AI-generated answers on platforms like ChatGPT, Claude, Perplexity, and Google AI Overviews.

SEO relies on signals like backlinks, keyword density, and domain authority to rank entire web pages. AEO uses Retrieval-Augmented Generation, where Large Language Models first retrieve relevant chunks of information based on semantic similarity, then synthesize those chunks into answers with citations.

Simply ranking #1 for a keyword no longer guarantees your content will appear in an AI answer. LLMs evaluate content based on how verifiable, structured, and entity-clear your information is, not just keyword presence.

Consider the business impact. A SparkToro study from July 2024 found that 58.5% of Google searches in the U.S. end without a click to any website. For every 1,000 searches, only 360 result in a click to the open web.

A comprehensive 2025 study by GrowthSrc found that the average CTR for the #1 organic position on Google fell by 32% year-over-year, dropping from 28% to 19% after AI Overviews rolled out. The #2 position saw a 39% decline.

Your traditional SEO agency reports that you rank #3 for a key category term. But if AI platforms never cite your brand when buyers ask for vendor recommendations, that ranking generates minimal pipeline.

You need to track fundamentally different metrics:

• Citation rate: The percentage of times AI platforms cite your brand when answering relevant queries. Measuring AEO performance requires tracking this across ChatGPT, Claude, Perplexity, and Google AI Overviews, not just Google.
• Share of voice: Your brand's visibility in AI answers compared to competitors, measured across all major platforms where your buyers research.
• Answer accuracy: Whether the information AI platforms present about your brand is correct and positively framed, tracked through citation sentiment analysis.
• Query coverage: The breadth of relevant buyer questions for which AI platforms feature your brand, from early-stage educational queries to late-stage comparisons.

The 24-question evaluation framework

Use these questions in your agency RFP to separate genuine AEO specialists from traditional SEO agencies rebranding their services.

Methodology and framework questions

1. Describe your proprietary framework for AEO. How does it specifically address LLM retrieval and ranking mechanisms?

A genuine AEO agency should articulate a clear, documented methodology. We developed the CITABLE framework with seven components: Clear entity structure, Intent architecture, Third-party validation, Answer grounding, Block structure for RAG, Latest timestamps, and Entity schema. Each component serves a specific function in how AI systems retrieve and cite information.

Good answer: The agency walks you through each component, explains how it maps to LLM retrieval, and provides published documentation you can review.

Red flag: Vague statements about "AI-optimized content" without specific methodology, or traditional SEO practices with "AI" added to descriptions.

2. How do you identify the most critical user queries and topics for our business to target in AI answers?

The agency should describe a research process beyond traditional keyword tools. Look for testing actual queries in AI platforms, competitor citation analysis, and mapping the buyer's journey to questions prospects ask AI at each stage.

Good answer: "We test 200+ buyer-intent queries across ChatGPT, Claude, and Perplexity, analyze which competitors get cited and why, then map those to your buyers' decision stages. We mine your sales call transcripts and support tickets for actual customer language."

Red flag: "We use Semrush and Ahrefs for keyword research, then optimize blog posts around high-volume terms."

3. What is your process for creating and structuring content to maximize its chances of being cited?

Look for specific structural elements like entity-based organization, conversational Q&A formats, and block-structured content designed for RAG systems. The agency should explain how they format content into discrete, self-contained chunks that AI systems can extract and cite.

4. How do you leverage structured data and schema markup for AEO, and which types are most important for B2B SaaS?

The agency should demonstrate deep technical knowledge of schema.org markup. For B2B SaaS, the most critical schema types include SoftwareApplication, Organization, FAQPage, and HowTo. Each serves a specific purpose in helping AI systems understand and cite your content.

5. Explain your strategy for optimizing our brand's presence across multiple AI platforms.

Different AI platforms have different retrieval preferences. A sophisticated AEO agency should articulate platform-specific strategies. They should understand that ChatGPT with search behaves differently from Perplexity's citation model.

6. How do you build third-party validation and authority signals that AI systems trust?

The agency should describe their approach to securing mentions on Wikipedia, Reddit, G2, industry forums, and tech publications. AI models weight external validation heavily. Our Reddit marketing service uses dedicated account infrastructure to build this validation systematically.

7. What is your philosophy on content volume and publishing frequency for AEO?

AI models favor fresh, frequently updated information. An agency offering 10-15 blog posts per month is applying traditional SEO cadence to a fundamentally different challenge. Effective AEO requires higher frequency, often daily publishing, to build topical authority.

Measurement and attribution questions

You cannot distinguish between an agency driving results and one that's guessing without specialized tracking. These six questions reveal whether the agency has the infrastructure to measure AEO performance.

8. What specific AEO metrics do you track, and how do they differ from traditional SEO KPIs?

The agency should clearly articulate metrics like citation rate, share of voice in AI platforms, answer sentiment, and zero-click impression growth. If they only discuss organic traffic and keyword rankings, they're measuring the wrong outcomes.

9. What tools and platforms do you use to monitor our citation rate and share of voice in AI answers?

Ask them to name specific platforms and demonstrate the dashboards. Be wary of agencies that use only incognito mode testing, as this misses how real users with logged-in AI accounts experience different results.

10. Can you provide a sample AI Visibility Audit and explain the key deliverables?

A comprehensive audit should test hundreds of buyer-intent queries across multiple AI platforms, showing exactly where you appear and where competitors dominate. The deliverables should include citation frequency, position in AI answers, and competitive benchmarks.

11. How do you attribute business outcomes like leads and conversions to your AEO efforts?

Ask the agency to explain their UTM tagging strategy, CRM integration, and how they track the buyer's journey from AI platform to conversion. Ahrefs research shows that AI search visitors convert at 23x higher rates than traditional search traffic, but you only capture that value if you can attribute it properly.

12. What is the frequency and format of your reporting, and what key insights can we expect?

Look for weekly or bi-weekly reporting that shows citation rate trends, competitive share of voice, and specific content pieces driving AI mentions. Monthly reports alone don't provide enough signal to optimize effectively.

13. How do you separate signal from noise when measuring AEO results?

AI platforms update constantly, creating natural variance. The agency should explain how they use statistical modeling to separate signal from noise when citation rates fluctuate.

Operational cadence questions

The agency's operational structure determines whether they can execute at the speed AEO requires. These five questions assess their production capabilities and technical depth.

14. What is your recommended content publishing cadence for effective AEO, and why?

Traditional agencies recommend 10-15 pieces per month. Effective AEO often requires daily publishing to build the topical authority and freshness signals AI systems prioritize.

15. Describe your team's structure and the specific expertise each member brings to our account.

The team should include data scientists or LLM specialists, not just traditional SEOs and content writers. Moving from SEO to AEO requires architectural changes that demand technical expertise in how AI models work.

16. How do you ensure the factual accuracy and quality of the content you produce?

AI systems prioritize verifiable facts with citations. The agency should describe their fact-checking process, source attribution standards, and how they build answer grounding with proper citations into every piece.

17. What is your process for integrating with our existing marketing and content teams?

AEO should complement, not replace, your existing efforts. The agency should explain how they coordinate with your team, what approvals they need, and how they handle your brand voice.

18. What are the technical requirements for implementing your AEO strategy on our website?

The agency should outline specific schema implementations, site structure recommendations, and any developer resources required. They should show how keyword ranking works in AI search and what technical foundation supports it.

Experience and results questions

19. Can you provide at least two B2B SaaS case studies with specific before-and-after AEO metrics?

Look for case studies showing citation rate improvements, share of voice gains, and attributed pipeline impact. We helped one B2B SaaS company grow AI-referred trials from 550 to 2,300+ in four weeks using systematic AEO.

20. What is a realistic timeline to see measurable results from your AEO program?

Be wary of agencies promising results in 2-4 weeks or requiring 12 months before showing progress. A realistic timeline shows initial citations in 1-2 weeks, meaningful citation rate improvements in 1-3 months, and measurable pipeline impact in 3-4 months.

21. How do you stay current with rapid advancements in AI and LLM technology?

Look for evidence of original research and systematic experimentation, not just following industry blog posts.

Commercial and contract questions

22. What is your pricing model, and what is the typical monthly investment for a company like ours?

AEO agency pricing typically ranges from $5,000 to $20,000+ per month depending on content volume, platform coverage, and authority-building campaigns. The agency should explain what's included at each tier.

23. What are your standard contract terms, including initial commitment and cancellation policy?

Month-to-month contracts signal confidence in results. Long-term contracts with aggressive termination penalties shift risk to you.

24. What are the potential risks or challenges we should be aware of when implementing an AEO strategy?

Transparent agencies acknowledge that AI platforms update unpredictably, attribution can be challenging, and building authority takes time. They should explain mitigation strategies rather than making unrealistic guarantees.

The vendor scorecard

Use this weighted scorecard to compare agency proposals objectively. Assign each vendor a score from 1-5 for each criterion, multiply by the weight, and total the scores. A vendor scoring above 4.0 shows strong capability, 3.0-4.0 suggests adequate capability with gaps, and below 3.0 signals fundamental concerns.

Scoring guide:

• 5 - Exceptional: Exceeds expectations with clear differentiation and data-driven approach
• 4 - Strong: Meets all requirements with solid, well-articulated plan
• 3 - Satisfactory: Addresses requirements but lacks depth or competitive advantage
• 2 - Weak: Vague, generic responses that don't inspire confidence
• 1 - Unacceptable: Fails to address key requirements or demonstrates lack of AEO understanding

Red flags: Warning signs of a traditional agency in disguise

As AEO gains prominence, many traditional SEO agencies rebrand services without changing methodology. Use this checklist when reviewing proposals:

• Traditional metric obsession: Proposal emphasizes keyword rankings and organic traffic without citation-based metrics
• Vague methodology: Cannot articulate a proprietary framework beyond "AI-optimized content"
• Unrealistic timeline promises: Guarantees results within 2-4 weeks or demands 12+ month contracts before showing progress
• No specialized tracking tools: Cannot demonstrate tools for measuring citations across ChatGPT, Claude, and Perplexity
• Missing technical depth: Strategy lacks focus on schema.org markup, entity structure, or RAG optimization
• Team skill gaps: Consists solely of SEOs and content writers with no LLM specialists or data scientists
• Can't show sample reports: Unable to provide examples of citation tracking or competitive analysis dashboards
• Website-only strategy: Ignores third-party validation from Wikipedia, Reddit, G2, and industry publications
• Dodges technical questions: Becomes evasive when asked about LLM retrieval mechanics or differentiation from SEO
• "AI-optimized" content claims: Describes traditional keyword research and backlink building with "AI" labels added

If an agency triggers three or more of these flags, they likely added "AEO" to their website without building genuine capabilities. The differences between AEO and SEO run deep, and rebranding doesn't create expertise.

How Discovered Labs answers these questions

To illustrate genuine AEO capabilities, here's how we address the framework's hardest questions.

On methodology: We developed the CITABLE framework specifically for LLM retrieval. Each of the seven components maps to how AI systems evaluate trustworthiness and extractability.

On measurement: We built internal tools to track citations across ChatGPT, Claude, Perplexity, Google AI Overviews, and Bing Copilot. Our AI visibility audits test hundreds of buyer-intent queries to show exactly where you're invisible and where competitors dominate.

On commercial terms: We offer month-to-month contracts with no long-term lock-in. This pricing structure reflects confidence that we'll earn your business by delivering measurable citation improvements.

Start with an AI visibility audit

You need to understand your current state before you can evaluate whether an agency is right for you. Where does your brand appear when prospects ask AI for vendor recommendations? Where are you invisible while competitors dominate?

We test hundreds of buyer-intent queries across ChatGPT, Claude, Perplexity, and Google AI Overviews in our AI visibility audits. You'll see your citation rate, competitive share of voice, and the specific gaps you need to fill.

Use the 24 questions in this guide to evaluate agencies' capabilities. Look for proprietary methodology, specialized tracking infrastructure, high publishing cadence, and month-to-month contracts that prove confidence in results.

B2B buyers now adopt AI search at three times the rate of consumers. Your agency partner must adapt.

Book a free AI visibility audit to see where you stand, or use our ROI calculator to model the pipeline impact of improving your citation rate from 5% to 40%.

FAQs

How long does it take to see results from AEO?
Initial citations appear in 1-2 weeks, meaningful citation rate improvements in 1-3 months. Measurable pipeline impact emerges in 3-4 months with consistent execution.

What's a good citation rate benchmark for B2B SaaS?
Most companies start at 5-15% citation rate for relevant queries. Top performers achieve 40-50%+ citation rates.

Should we build an in-house AEO team or hire an agency?
Building an in-house AEO team costs approximately $403K in the first year versus $66K annually for specialized agency services.

How is AEO different from traditional SEO?
AEO differs from SEO because it optimizes for retrieval and citation by AI systems rather than ranking in traditional search results.

Can our existing SEO agency add AEO services?
Most traditional SEO agencies lack the specialized tools, LLM expertise, and high-frequency publishing infrastructure required for effective AEO.

Key terms glossary

Answer Engine Optimization (AEO): The practice of structuring content to ensure AI platforms cite your brand in generated answers. Success is measured by citation rate and share of voice rather than keyword rankings.

Citation rate: The percentage of relevant buyer-intent queries where an AI platform includes your brand in its generated answer. This is the primary success metric for AEO programs.

CITABLE framework: A proprietary seven-component methodology designed to maximize content's likelihood of being cited by AI systems. Components include Clear entity structure, Intent architecture, Third-party validation, Answer grounding, Block structure for RAG, Latest timestamps, and Entity schema.

Retrieval-Augmented Generation (RAG): The technical process where Large Language Models first retrieve relevant information chunks from external sources, then synthesize those chunks into coherent answers with citations.

Share of voice: The comparative metric showing how often your brand appears in AI answers versus competitors for a defined set of buyer-intent queries.

Zero-click search: A search result where the user's question is answered directly without clicking through to any website. Now represents 58.5% of Google searches according to SparkToro data.