7-Step AI Visibility Audit: How to choose a B2B SaaS marketing agency for AEO or GEO

Updated November 25, 2025

According to Forrester's 2025 B2B buyer research, 89% of B2B software buyers now use AI assistants during their purchasing process. Meanwhile, Gartner predicts a 25% decline in traditional search volume by 2026. Your current SEO metrics hide this shift because they measure the wrong surface area.

Agencies still optimizing solely for ten blue links on Google are optimizing for a channel losing share every month. You need a partner who engineers visibility where your buyers actually research: ChatGPT, Claude, Perplexity, and Google AI Overviews.

This guide gives you the exact 7-step audit framework to separate agencies with real AI search capabilities from those simply rebranding their SEO services with "AI" buzzwords.

B2B SaaS Agency Vetting Checklist

(Copy this for your discovery calls)

□ Step 1: Agency appears in ChatGPT/Claude when I search for "AEO agencies" or similar
□ Step 2: Agency has documented retrieval framework (not just "quality content")
□ Step 3: Agency has proprietary AI visibility tracking (not just Google Analytics)
□ Step 4: Agency can produce 20+ pieces/month at daily cadence
□ Step 5: Agency understands entity optimization, schema, knowledge graphs
□ Step 6: Contract is month-to-month with clear ownership and exit terms
□ Step 7: Agency has B2B SaaS case studies with pipeline metrics

If any of steps 2-4 fail, end the conversation and move to your next candidate.

Why traditional software marketing agencies are failing B2B SaaS

The search market shifted faster than most agencies adapted. Traditional SEO was built on a simple premise: rank your pages on Google's first page, earn clicks, convert traffic. That playbook drove results for two decades.

AI-powered answer engines changed the game. When prospects use ChatGPT or Perplexity, they don't click through to ten different websites. AI synthesizes information and delivers recommendations directly, often without the user ever visiting your site. Ahrefs' 2025 traffic study documented that AI search visitors convert at a 23x higher rate than traditional organic search because buyers arrive with context and intent already established.

Your traditional agency tracks keyword rankings, backlink profiles, and domain authority. None of these predict whether ChatGPT will cite you when a prospect asks for vendor recommendations.

One B2B SaaS case study documented going from 550 AI-referred trials per month to over 3,500 in seven weeks by shifting from traditional SEO to Answer Engine Optimization. Their AI visibility quadrupled and our content also outperformed their existing SEO content 3-5x in the SERP (impressions, clicks, avg. position on page 1 compared to global position of 30+)

Most software marketing agencies lack the technical depth to optimize for LLM retrieval. They don't understand how models weight third-party validation, why entity consistency matters across platforms, or how structured data influences citation probability.

You need specialized expertise to navigate the shift from search to answer engines. Generic digital agencies and traditional SEO shops can't pivot fast enough.

The 7-step AI visibility audit for agencies

Use this framework during discovery calls and vendor evaluations. Each step includes decision gates. If an agency fails steps 2-4, end the conversation and move to your next candidate.

1. Audit their own AI visibility

An agency claiming AEO expertise should demonstrate it through their own visibility. Test their presence before your first call:

Run these queries in ChatGPT, Claude, and Perplexity:

1. "Best marketing agencies for B2B SaaS companies"
2. "Answer engine optimization services for software companies"
3. "How to improve AI search visibility for B2B tech"

Does the agency appear in any responses? Are they cited with specific examples? If they're invisible in the channel they claim to dominate, that's your answer.

Ask for screenshots showing where they rank in AI-generated vendor lists for their own category. A confident agency will have this ready. At Discovered Labs, we track our own AI visibility across platforms and can show exactly where we appear for relevant queries.

Decision gate: If they can't prove their own AI visibility, they can't engineer yours. Move on.

2. Demand a documented retrieval framework

"We create high-quality content" is not a strategy for AI citation. LLMs don't evaluate quality the way humans do. They retrieve content based on structure, verifiability, entity clarity, and freshness.

Ask the agency to walk you through their specific methodology. They should have a documented framework with clear principles, not vague promises.

The CITABLE framework used at Discovered Labs provides a concrete example. Here's how each element works:

• Clear entity & structure (2-3 sentence BLUF opening)
• Intent architecture (answer main + adjacent questions)
• Third-party validation (reviews, UGC, community citations)
• Answer grounding (verifiable facts with sources)
• Block-structured for RAG (200-400 word sections, tables, FAQs)
• Latest & consistent (timestamps + unified facts everywhere)
• Entity graph & schema (explicit relationships in copy)

Your potential agency doesn't need this exact framework, but they must articulate their approach with similar specificity. If they fall back on "SEO best practices" or "creating valuable content," they're guessing.

What to ask:

• "Can you show me the specific content structure you use to increase citation probability?"
• "How do you optimize for passage retrieval versus page ranking?"
• "What role does entity disambiguation play in your process?"

An agency fluent in AEO will answer these questions with technical detail. One that pivoted from traditional SEO last month will struggle.

Decision gate: No documented methodology equals no repeatable results. Require specifics or walk away.

3. Check their tracking infrastructure

You can't optimize what you don't measure. An AEO-capable agency must track citation rates across major AI platforms.

Traditional analytics tools like Google Analytics and SEMrush don't capture AI visibility. Ask potential agencies: "How do you track where clients appear in ChatGPT, Claude, Perplexity, and Google AI Overviews?"

They should describe proprietary tracking tools or specialized platforms. At Discovered Labs, we built internal software that audits AI visibility and tracks share of voice against competitors for specific query sets.

Look for agencies that can show you:

• Citation rate: Percentage of buyer-intent queries where your brand appears
• Share of voice: Your mentions versus competitors for your category
• Sentiment tracking: Whether AI platforms describe your brand positively or negatively
• Platform-specific performance: Separate metrics for ChatGPT, Claude, Perplexity, Google AI Overviews

Watch for agencies that emphasize rankings, traffic, and impressions without connecting them to pipeline. For example, an agency might report "150% increase in organic traffic" while your AI-referred MQLs dropped by 20%. These metrics are inputs, not outcomes. You care about qualified leads, pipeline contribution, and closed revenue.

Decision gate: No tracking infrastructure means no accountability. Demand specific tools or pass.

4. Verify content volume and technical depth

Traditional SEO agencies produce 4-8 blog posts per month. That volume worked when competing for 50 keyword rankings. It fails for AEO, where you need coverage across thousands of potential buyer queries.

AI models favor content that covers topic clusters comprehensively. Publishing one pillar post per month leaves massive gaps for competitors to fill. Comprehensive coverage drives citation rates because LLMs retrieve from the most thorough, up-to-date sources.

Ask about production capacity:

• How many pieces can they ship monthly?
• Do they publish daily or weekly?
• Can they respond to trending topics within days?

At Discovered Labs, our packages start at 20 articles per month for comprehensive topic coverage. For larger clients, we can produce 2-3 pieces daily.

Compare this to traditional agencies producing 10-12 blogs monthly. That's 120-144 pieces per year covering maybe 150 buyer queries. You need coverage across 2,000+ potential questions to achieve a 40% citation rate. The math doesn't work at traditional agency pace.

Probe their technical knowledge:

"What structured data types do you implement, and how do they influence AI citations?" A competent agency will discuss Organization, Product, FAQPage, and HowTo schemas. They should explain that schema helps LLMs understand entity relationships and extract accurate information.

"How do you ensure consistent entity information across platforms?" AI models skip citing brands with conflicting data. If your website says you were founded in 2018 but Wikipedia lists 2019, that inconsistency reduces citation probability.

One technical case study from Discovered Labs demonstrates statistical testing methods for AEO. The agency you hire doesn't need our exact approach, but they should show similar rigor in understanding LLM mechanics.

Decision gate: If they can't commit to at least 15-20 pieces monthly with daily publishing capability, or if they can't explain entity disambiguation and structured data in concrete terms, they lack the infrastructure to compete in AI search.

5. Scrutinize the contract terms

Traditional agency contracts lock you into 12-month commitments with aggressive termination penalties. This worked when SEO required long ramp times. AEO can show early signals within 4-6 weeks, and you should have flexibility based on performance.

Key contract terms to demand:

Month-to-month engagement structure: The agency should earn your business every month by delivering measurable results. Discovered Labs operates on rolling monthly contracts because we're confident in our ability to show citation improvements quickly. If an agency insists on annual commitments before proving value, they're protecting themselves from underperformance.

Clear ownership of assets: The contract must state explicitly that you own all content, data, and creative work. Some agencies retain ownership to create lock-in. That's unacceptable.

Transparent pricing structure: All costs should be clearly itemized. Watch for vague language about "additional optimization fees" or "technical implementation charges."

Performance-based opt-outs: Even with month-to-month terms, negotiate specific performance thresholds. For example, a fair performance clause reads: "If AI citation rate doesn't improve by at least 10 percentage points within 90 days, client may terminate with 14 days notice." Contrast that with vague language like "Results may vary; termination requires 60-day notice and forfeiture of setup fees."

Red flags in contracts:

• Auto-renewal clauses that roll into another 12 months unless you cancel 60+ days in advance
• Ownership provisions that keep creative work "licensed" to you rather than owned
• Termination fees exceeding one month's retainer
• Vague scope of work that lets them define deliverables after you've signed

Decision gate: Unfavorable contract terms signal low confidence in results. A strong agency will offer fair, flexible terms because they trust their methodology.

6. Assess B2B SaaS specialization

Software companies have unique marketing challenges that generalist agencies don't understand. The buyer journey is long (6-18 months for enterprise deals), involves multiple stakeholders, and requires technical depth in content.

What to ask:

• "Show me case studies from B2B SaaS companies with 6+ month sales cycles."
• "How do you track pipeline contribution in Salesforce for deals with 8+ touchpoints?"
• "Walk me through how you'd position a complex API feature for both technical and executive buyers."

Request examples from B2B SaaS, fintech, or technology companies similar to yours. Generic B2C work doesn't translate. You need an agency that understands technical buyers, long sales cycles, and complex product positioning.

Ask how they'd approach content for different personas in your buying committee. Can they articulate the difference between creating content for end users (product managers) versus economic buyers (CFOs) versus technical gatekeepers (IT directors)?

Don't assume past Google SEO performance predicts AEO success. The skills overlap partially, but AI optimization requires different technical depth around entity structure, passage retrieval, and LLM training data. Prioritize proven AEO results over traditional SEO track records when your goal is capturing the majority of buyers using AI for research.

Decision gate: If they lack B2B SaaS case studies or can't demonstrate understanding of technical buyer journeys, they're not the right fit regardless of their AI capabilities.

Red flags: When to end the sales call

You should treat these warning signs as immediate disqualifiers:

Guaranteed results promises: No legitimate agency can guarantee "first page rankings" or "500% increase in leads" before understanding your market position. AI search is probabilistic. Ethical agencies discuss expected outcomes in ranges with caveats, not guarantees.

Conflating AI content creation with AEO: Many agencies now claim "AI expertise" because they use ChatGPT to write blog posts faster. That's AI-assisted content production, not Answer Engine Optimization. AEO is about optimizing FOR AI systems, not creating content WITH AI tools.

No current AI visibility data: The agency should be able to show their own presence in AI search results. If they've been doing AEO for clients but haven't applied it to their own marketing, why not?

Resistance to performance-based terms: When an agency insists on 12-month commitments and refuses any performance accountability, they're protecting themselves from churn. Confident agencies welcome performance clauses because they consistently deliver results.

How to evaluate agency capabilities: A comparison

You'll encounter three types of agencies when evaluating software marketing partners, each with different capabilities:

The AEO ROI calculation matters more than upfront cost. If an AEO specialist generates leads converting at 23x the rate of traditional search, the premium pays for itself quickly.

How Discovered Labs passes this audit

We built our agency to meet every criterion in this framework because we knew B2B software companies would demand proof.

Our AI visibility: Test us yourself. Ask ChatGPT or Perplexity about "Answer Engine Optimization agencies for B2B SaaS." We appear consistently because we apply our methodology to our own marketing.

Our documented framework: The CITABLE methodology is published openly with specific implementation details, covering everything from entity clarity to third-party validation and structured data.

Our tracking infrastructure: We built proprietary software to audit AI visibility across ChatGPT, Claude, Perplexity, and Google AI Overviews. Every client gets weekly reports showing citation rates, share of voice versus competitors, and specific queries where they appear or are missing.

Our content capacity: Our packages start at 20 articles per month with the ability to scale to 2-3 pieces daily. We maintain quality through a 10-step human-in-the-loop process while achieving the volume needed to compete in AI search.

Our technical depth: Co-founder Ben Moore brings AI research experience from working on LLM systems. This isn't SEO intuition repackaged as "AI optimization." We understand retrieval mechanics, entity disambiguation, and knowledge graph construction at a technical level.

Our contract terms: We offer month-to-month engagements because we're confident in our ability to show measurable improvements. You own all content and data.

Our B2B specialization: We work exclusively with B2B SaaS, fintech, and technology companies. Our case studies include documented results like 4x increases in AI-referred trials. One client went from 550 to over 3,500 AI-referred trials in seven weeks. Another improved ChatGPT citations by 29% and closed 5 new customers in month one.

Why timing matters now

Early movers in AI search are capturing category mindshare that will be difficult to displace. When AI models consistently cite three competitors in your space, becoming the fourth recommendation requires significantly more effort than securing initial visibility.

The agencies with real AEO capabilities are rare enough that demand outpaces supply. The best firms are selective about clients because they can afford to be.

Use this 7-step audit to identify your strategic partner before your competitors secure AI visibility that will take you months to displace. You can be one of the category leaders if you apply this audit framework to find the right partner this quarter.

Don't guess where you stand. Request a free AI Visibility Audit from Discovered Labs. You'll see side-by-side screenshots of how ChatGPT, Claude, Perplexity, and Google AI Overviews cite your brand versus your top three competitors, with specific examples of the citation gaps we'd fill and the competitive advantages you'd gain.

Frequently asked questions

What's the difference between SEO and AEO?
SEO optimizes for Google's ranking algorithm to earn clicks from search result pages. AEO optimizes for citation in AI-generated answers where users get recommendations without clicking. The technical approaches differ significantly around entity clarity, third-party validation, and structured data compared to how Google's traditional algorithm weights backlinks and content length.

How long does it take to see results from AEO?
Initial citations typically appear in 4-6 weeks as AI models crawl and index new content. Measurable pipeline impact takes 3-4 months as you build comprehensive topic coverage and secure third-party validation signals. Companies expecting instant results are better served by paid advertising.

How do you measure ROI from AI search?
We track AI-referred leads through UTM parameters and integrate with your CRM to show pipeline contribution. Key metrics include citation rate (percentage of buyer queries where your brand appears), share of voice versus competitors, and conversion rates of AI-referred leads compared to traditional organic sources. Pipeline contribution typically ranges from 22:1 to 60:1 for comprehensive AEO programs.

Can we do AEO in-house instead of hiring an agency?
Companies with budget and technical expertise can build internal AEO teams. The first-year cost typically runs $403K for six specialized roles. Most mid-market companies find specialized agencies more cost-effective until they reach $50M+ revenue.

How much should we budget for a competent AEO agency?
Expect €5,000-15,000 monthly for comprehensive services including daily content production, AI visibility tracking, technical optimization, and third-party validation campaigns. Cheaper options exist but typically lack the specialized infrastructure needed for measurable impact. Compare the pricing against potential pipeline value, not against traditional SEO agency costs.

Key terms glossary

Answer Engine Optimization (AEO): The practice of structuring content so AI-powered search tools can understand, verify, and cite it as authoritative answers to user questions. Distinct from traditional SEO which optimizes for ranking in search result pages.

Citation Rate: The percentage of relevant buyer-intent queries where an AI platform mentions your brand in generated responses. A 40% citation rate means your brand appears in 4 out of every 10 AI answers for your target query set.

CITABLE Framework: Discovered Labs' 7-part methodology for creating content optimized for AI citation, covering clarity, intent, third-party validation, answer grounding, block structure, latest information, and entity relationships.

Entity: A distinctly identifiable thing or concept (person, company, product, location) that AI systems track across sources. Entity disambiguation is the process of ensuring AI correctly identifies your brand versus similar entities.

Knowledge Graph: The internal representation AI models build connecting entities, attributes, and relationships. Strong AEO establishes clear nodes and edges for your brand in these graphs.

Share of Voice: Your brand's mentions in AI-generated answers as a percentage of total competitor mentions for a defined query set. A 30% share of voice in a three-competitor market means you appear in 30% of relevant AI answers.

Third-Party Validation: External sources (reviews, news articles, Reddit discussions, Wikipedia entries) that reference your brand and provide credibility signals AI models weight heavily when deciding what to cite.