The AEO agency scorecard: how to evaluate vendors without getting sold hype

Updated December 19, 2025

A VP of Marketing at a mid-market SaaS company recently discovered they lost a six-figure deal before the sales team ever knew the opportunity existed. The prospect had asked ChatGPT for vendor recommendations, evaluated three competitors mentioned in the response, and signed a contract. The VP's company was never cited.

This is not an isolated incident. 89% of B2B buyers have adopted generative AI as one of their top sources of self-guided information throughout the buying process, according to Forrester's 2024 Buyers' Journey Survey. If your brand is not cited when buyers ask AI for recommendations, you are invisible to nearly half your potential pipeline.

If you are evaluating AEO partners, you face a vetting challenge. Dozens of agencies now claim "AI optimization" expertise. Most are traditional SEO shops that added AEO to their service menu three months ago. This scorecard helps you separate genuine retrieval engineers from repackaged SEO vendors and make a defensible selection decision.

Why your traditional SEO agency scorecard fails in the age of AI

The metrics your SEO agency uses no longer matter for AI visibility. Ranking #3 on Google for "best project management software" means nothing if ChatGPT recommends three competitors and never mentions you.

The fundamental difference is simple: SEO optimizes for rankings. AEO optimizes for retrieval.

In traditional search, Google's algorithm evaluates your page and assigns it a position. In AI search, Large Language Models use Retrieval Augmented Generation (RAG) to fetch external facts and incorporate them into responses. Your content either gets retrieved and cited, or it does not exist.

This technical shift requires completely different KPIs:

Reference rate, the percentage of relevant AI-generated responses that cite your brand, now serves as the standard for measuring AEO success. This replaces traditional click-through rates because users often do not click through at all. The AI delivers the complete answer.

The conversion implications are significant. ChatGPT traffic converts at 15.9% compared to Google Organic's 1.76%, according to Seer Interactive's analysis of client data. That represents a 9x differential. AI platforms act as intent filters, bringing users who are already engaged and further along in their decision journey.

If you evaluate an AEO vendor using traffic and rankings, you are measuring the wrong things.

The 5-part weighted scorecard for evaluating AEO partners

This framework assigns weights to five evaluation criteria based on their impact on results. Total weight: 100%.

1. Methodology: do they have a retrieval-first framework?

"Writing good content" is not enough for AI citation. Content must be structured for how LLMs retrieve and process information.

Traditional SEO content builds toward an answer. AEO content leads with direct answers in 40-60 words, uses structured blocks of 200-400 words, and prioritizes third-party validation over keyword density. The biggest difference: AEO content must be quotable, formatted so AI can extract and cite specific facts without losing context.

A qualified AEO agency should have a documented, published methodology. The CITABLE framework provides an example of what this looks like:

• C: Clear entity and structure with 2-3 sentence BLUF opening
• I: Intent architecture that answers main and adjacent questions
• T: Third-party validation through reviews, UGC, community mentions, and news citations
• A: Answer grounding with verifiable facts and sources
• B: Block-structured for RAG using 200-400 word sections, tables, FAQs, and ordered lists
• L: Latest and consistent information with timestamps plus unified facts everywhere
• E: Entity graph and schema with explicit relationships in copy

Using this framework, a B2B SaaS company increased AI-referred trials from 550 to 2,300 in 4 weeks, a 4x improvement.

Litmus test question: "Show me your specific framework for LLM retrieval structure. Walk me through how each element influences citation likelihood."

If the agency responds with generic content quality principles or SEO best practices, they do not have a true AEO methodology. A real answer includes technical details about entity clarity, block structure, and third-party validation signals.

2. Technology: can they actually track citation rates?

AI search presents a measurement challenge. Unlike Google Search Console, there is no native dashboard showing when ChatGPT or Claude cites your brand. Most marketers are flying blind on where they appear in AI answers.

A qualified AEO partner needs proprietary tracking technology or robust integration with AI visibility monitoring platforms that measure:

• Citation rate: Percentage of buyer-intent queries where your brand appears
• Share of voice: Your citation frequency relative to competitors
• Platform coverage: Tracking across ChatGPT, Claude, Perplexity, and Google AI Overviews

The formula for share of voice in AI answers is: (Number of AI responses mentioning your brand / Total responses mentioning any brand in your category) x 100. A 40% share of voice means you appear in 4 out of 10 relevant AI answers.

We built internal technology to audit where brands appear across platforms, testing thousands of buyer queries to identify gaps where competitors dominate. Our Knowledge Graph tracks winning patterns across hundreds of thousands of clicks monthly.

Litmus test question: "How do you track my brand's mentions in ChatGPT week-over-week? Show me a sample dashboard or report."

If the agency says they "monitor AI results manually" or "use general SEO tools," they lack the infrastructure for systematic AEO measurement.

3. Content operations: is it high-volume and entity-rich?

LLMs crave fresh, consistent information. Four blog posts monthly will not move citation rates when AI models constantly refresh their retrieval databases.

Traditional SEO campaigns produce approximately 4 blog articles per month of average quality, according to First Page Sage benchmarks. Thought leadership campaigns reach 6-8 high-quality content pages monthly.

AEO requires a fundamentally different cadence. We ship daily for clients, owning the entire content production process and using internal technology to research, draft, and optimize faster than traditional agencies.

Beyond volume, content must be entity-rich:

• Explicit relationships: Clear connections between your brand, products, and related concepts
• Schema markup: Organization, Product, and FAQ schemas that feed signals to AI systems
• Third-party validation signals: Reviews on G2 and Capterra, Reddit mentions, Wikipedia references

AI models prioritize external sources for brand information. Consistent information across platforms matters because AI models skip citing brands with conflicting data.

Litmus test question: "Can you support daily publishing without sacrificing accuracy? What is your process for ensuring entity consistency across all content?"

4. Attribution: do they measure pipeline or just visibility?

Vanity metrics kill marketing programs. "Improved AI visibility" means nothing if you cannot tie it to revenue.

A qualified AEO agency establishes UTM tracking for AI-referred traffic and connects citations directly to pipeline in your CRM. According to Semrush's AI search study, the average LLM visitor is worth 4.4x more than the average traditional organic search visitor. That value only matters if you can measure it.

Here is what proper AI attribution looks like:

1. Traffic tracking: Custom GA4 channel groups that segment ChatGPT, Perplexity, and Claude referrals
2. UTM parameters: Tagged links in AI-cited content that carry through to lead capture
3. CRM integration: AI-referred MQLs identified in HubSpot or Salesforce
4. Pipeline reporting: Revenue influenced by AI citations

Litmus test question: "Show me a report linking an AI citation to a closed-won deal. How do you attribute pipeline to specific content pieces?"

If the agency focuses on "awareness" or "reach" without connecting to business outcomes, they are not measuring what matters.

5. Commercials: are they hiding behind long-term contracts?

The AEO landscape changes rapidly. AI Overviews now appear in 13.14% of SERPs, more than double the 6.49% in January 2025, according to Semrush analysis. Twelve-month contracts in this environment trap you with strategies that may become obsolete.

Month-to-month terms signal confidence. An agency willing to earn your business every month believes their methodology works. Long-term lock-ins suggest they need contractual protection because results are uncertain.

Many agencies require 6-12 month commitments as standard practice. This makes sense for traditional SEO where campaigns need months to prepare and execute. AEO operates on faster cycles. You should see initial citations within 2-8 weeks. If results do not materialize, you need flexibility to pivot.

Litmus test question: "Do you offer month-to-month terms based on performance? What is your cancellation policy if results do not materialize by month three?"

Red flags: how to spot AI-washing in proposals

Watch for these warning signs when reviewing agency pitches:

• "Page 1 rankings" promises: Irrelevant for AI chat where there is no page 1
• Generic AI writing tools: Volume without strategy produces noise, not citations
• No citation case studies: Only traffic-focused results, not AI visibility outcomes
• Vague knowledge graph explanation: Generic answers about "quality content" instead of technical methodology
• Traditional SEO metrics: Measuring success by keyword position that does not translate to RAG retrieval
• Unrealistic timelines: Promises of results in 2-4 weeks when realistic AEO takes 3-4 months for significant impact

AEO optimizes for discoverability within AI-generated responses, many without clickable results. Traditional SEO optimizes for ranking within search engine results pages. Any agency conflating these approaches has not adapted their methodology.

Making the decision: a side-by-side comparison matrix

Use this matrix to score vendors across the five criteria:

Scoring instructions:

1. Score each vendor 1-5 for each criterion (5 = excellent, 1 = poor)
2. Multiply score by weight to get weighted score
3. Sum weighted scores for total evaluation score

How Discovered Labs scores against this framework

We built this scorecard based on gaps we saw in the market, and we designed our service to address each criterion. Here is how we measure up and where we are not a fit.

Methodology (25%): We developed the CITABLE framework specifically for LLM retrieval, testing every content piece in our sandbox before publishing. However, CITABLE is not a magic formula. It takes 8-12 weeks of consistent application before you see meaningful citation improvements.

Technology (20%): We built proprietary auditing technology because off-the-shelf tools did not exist when we started. Our AI visibility audits map where you appear across ChatGPT, Claude, Perplexity, and Google AI Overviews. The limitation: AI platforms change their algorithms constantly, so tracking requires continuous work, not a one-time audit.

Content Operations (15%): We ship daily for clients. Our entry package includes 20 articles monthly compared to the industry standard of 4-8. We own production end-to-end using internal technology. The trade-off: daily publishing focuses on breadth across query types rather than 3,000-word thought leadership pieces. If you need 10 comprehensive pillar articles per quarter rather than high-frequency Q&A content, we are not the right fit.

Attribution (20%): We help clients establish proper GA4 tracking for AI-referred traffic and connect citations to pipeline in HubSpot or Salesforce. The challenge: attribution is not perfect because many AI interactions do not result in immediate clicks. We track what we can measure, but some influence remains invisible.

Commercials (20%): We work month-to-month. If our approach does not work for you after 90 days, you can cancel. The honest timeline: most clients see initial citations within 2-8 weeks, but significant pipeline impact takes 4-6 months. If you need results in 30 days to hit quarterly targets, the timeline does not align.

The result? A B2B SaaS client increased AI-referred trials from 550 to 2,300+ in 4 weeks. That result is not typical. Most clients see 15-30% citation rate improvements in quarter one, which translates to 20-40 additional AI-referred MQLs monthly depending on category search volume.

Ready to see where you stand versus your top three competitors in AI search? Request an AI Visibility Audit and we will show you side-by-side screenshots of where your brand appears (or does not) when prospects ask ChatGPT, Claude, and Perplexity for recommendations in your category. We will be honest about whether we are a good fit for your situation.

Frequently asked questions

What is the difference between AEO and GEO?

AEO and GEO describe the same strategy with different terminology. Answer Engine Optimization and Generative Engine Optimization both focus on getting your content cited by AI systems. Some practitioners use GEO specifically for generative models like ChatGPT and Claude, while AEO encompasses broader AI-powered search features. In practice, the methodology is identical.

How long does it take to see results from AEO?

Most businesses see initial AI citations within 2-3 months of comprehensive implementation, with significant pipeline impact appearing in 6-12 months. The first 30 days establish baseline tracking. Weeks 4-12 typically show initial citation improvements as new content indexes and gains authority.

Can I just use an internal team for this?

You can, but the economics are challenging. An in-house SEO specialist earns $70,000-$90,000 annually before benefits. A complete AEO function requires strategy, content, technical, and analytics capabilities, typically 2-3 FTEs minimum at $150,000-$270,000 total. A $10,000/month agency retainer costs $120,000 annually, often delivering better results because of specialized expertise and tooling.

How much does an AEO agency cost?

Mid-market AEO retainers range from $8,000-$25,000/month compared to $2,000-$20,000/month for traditional SEO agencies. Most clients reallocate budget from underperforming SEO retainers rather than finding net-new budget. Our packages start at EUR 5,495/month for comprehensive AEO and SEO coverage.

How do I track if AEO is working?

Focus on three metrics: citation rate (percentage of buyer-intent queries citing your brand), share of voice (your citations versus competitors), and AI-referred conversions tracked through GA4 custom channel groups. Avoid measuring success by traditional SEO metrics like rankings or organic traffic volume.

Key terminology

Citation Rate: The percentage of buyer-intent queries where your brand appears in AI-generated answers. A 23% citation rate means AI cites your brand in 23 out of 100 relevant queries your prospects are actually asking.

Share of Voice (AI): Your brand's visibility compared to competitors within AI-generated answers. Formula: (Your brand mentions / Total market mentions including your brand) x 100. A 40% share of voice means you appear in 4 out of 10 competitive AI responses.

Retrieval Augmented Generation (RAG): The process AI uses to fetch external facts before generating a response. RAG enhances LLMs by incorporating an information-retrieval mechanism that accesses data beyond original training sets. Optimizing for RAG retrieval is the core technical challenge of AEO.

Answer Grounding: Structuring content with verifiable facts and sources positioned for easy LLM extraction. AEO content leads with direct answers in 40-60 words, provides evidence, and formats information so AI can quote specific facts without losing context.

Entity Clarity: How clearly AI systems can identify and categorize your brand, products, and their relationships. Strong entity clarity through schema markup and consistent information across platforms increases citation likelihood.