The B2B leader's guide to hiring a GEO agency

Updated January 08, 2026

Forrester reports that 89% of B2B buyers now use AI to research vendors before they ever talk to sales. When your prospects ask ChatGPT or Perplexity "What's the best [your category] for [their use case]?" your company either appears in the answer or you've lost the opportunity to enter their consideration set.

Search Engine Land analysis shows 60% of Google searches now end without any click to a website. Your buyers are getting their answers directly from AI systems, and those systems decide which brands to recommend based on completely different signals than Google's algorithm.

This guide walks you through what separates a specialized Generative Engine Optimization (GEO) agency from traditional SEO firms, how to evaluate partners based on methodology rather than promises, and what measurable results you should expect within 90 days.

What is a GEO agency and how does it differ from SEO?

Generative Engine Optimization is the practice of adapting content to improve visibility in AI-generated answers from systems like ChatGPT, Claude, Perplexity, and Google AI Overviews. Unlike SEO, which optimizes for ranking in a list of links, GEO optimizes for citation within synthesized answers.

The distinction matters because AI systems don't crawl and rank pages the same way Google does. They retrieve passages from across the web, evaluate them for relevance and authority, then synthesize them into direct answers. Conductor's research confirms traditional SEO tactics like keyword density and backlink volume don't translate to AI citations.

Here's how the two disciplines differ:

SEO agencies optimize for Google's algorithm. They focus on domain authority, backlinks, and on-page keyword optimization. Their deliverable is a page 1 ranking.

GEO agencies optimize for how AI models decide what to cite. We focus on entity clarity, third-party validation, verifiable facts, and structured content that LLMs can confidently extract and synthesize. Our deliverable is consistent brand mentions when buyers ask AI for recommendations.

Your current SEO agency likely doesn't have the tooling to track citations across ChatGPT or Perplexity, doesn't write content structured for Retrieval-Augmented Generation (RAG), and can't explain why competitors appear in AI answers while you don't.

Why B2B buyers are shifting to AI search for vendor research

B2B buyers want synthesized answers, not 10 blue links to research themselves. Complex purchases like SaaS platforms require evaluating features, pricing, integrations, and fit. AI systems do that synthesis work in seconds.

The behavior shift is measurable. In the B2B sector, Forrester analysis shows AI-generated traffic now represents 2% to 6% of total organic traffic and is growing at more than 40% per month. Ahrefs data shows AI traffic has increased 9.7x in the past year.

More important than volume is quality. When buyers use AI to research vendors, they arrive at your site already pre-qualified. The AI system told them you're a good fit for their use case. That's why AI-referred visitors convert at 2.4x higher rates than traditional organic search traffic, based on Ahrefs' analysis of conversion data across multiple platforms.

If AI systems don't cite you, you're not in the consideration set. Buyers create shortlists of 3 to 5 options from ChatGPT recommendations before they contact anyone. Understanding why competitors get cited while you don't requires specialized visibility audits most marketing teams can't run internally.

5 criteria for evaluating a specialized GEO partner

Most agencies claiming "AI optimization" services are traditional SEO firms adding a new line to their website. Here's how to separate real expertise from rebranded tactics.

1. Proprietary methodology, not adapted SEO playbooks

Ask the agency to explain their framework for optimizing content for LLM retrieval. Generic answers about "quality content" or "E-E-A-T" signal they're guessing.

At Discovered Labs, we use the CITABLE framework to structure every piece of content specifically for AI citation. Each letter represents a technical requirement for LLM retrieval:

• C - Clear entity & structure: Content opens with 2-3 sentence BLUF (bottom line up front) that explicitly states what the entity is
• I - Intent architecture: Content answers the main question plus adjacent questions buyers ask
• T - Third-party validation: Content includes references to reviews, community discussions, and external citations
• A - Answer grounding: Every claim is backed by verifiable facts with sources
• B - Block-structured for RAG: Content is organized in 200-400 word sections with tables, FAQs, and ordered lists
• L - Latest & consistent: Content includes timestamps and aligns with information across all platforms
• E - Entity graph & schema: Content explicitly states relationships between entities in natural language

This framework reflects how Retrieval-Augmented Generation systems actually work. They chunk content into passages, evaluate each passage for relevance and authority, then synthesize the strongest passages into answers. Writing for passage retrieval requires different structure than writing for keyword rankings.

2. AI citation tracking capabilities across platforms

Most agencies can show you Google Search Console reports. Few can show you what ChatGPT, Claude, or Perplexity say about your brand across 50 to 100 buyer-intent queries.

Ask to see examples of their citation tracking reports. They should be able to demonstrate systematic testing across multiple AI platforms and show you competitive benchmarking (what percentage of relevant queries cite you vs. competitors).

We track citations using internal tools that test thousands of queries monthly and build a knowledge graph of what content drives citations. We deliver weekly citation tracking reports showing your citation rate across platforms, competitive share of voice, and which content pieces are driving citations. You'll see exactly where progress is happening week over week.

This data advantage lets us operate with conviction rather than what's trending on LinkedIn. For example, our tracking showed the Reddit crisis was overblown because we spotted the flaw in other platforms' methodologies.

3. Content velocity that signals freshness and authority

AI models trust recent, frequently updated content more than static pages. One blog post per week doesn't create enough citation surface area.

We start our packages at 20 pieces of optimized content per month for smaller clients and scale to 2-3 pieces per day for larger accounts. Each piece is researched specifically to answer a buyer question, structured using the CITABLE framework for maximum citation potential, not generic blog content written for keyword rankings.

Daily publishing creates compounding citation authority. Each piece is a shot on target. Collectively, they signal to AI systems that you're an active, authoritative source worth citing.

4. Commercial flexibility and performance accountability

Long-term contracts protect agencies, not clients. If the methodology works, the agency should be confident offering month-to-month terms.

Ask about contract length and cancellation terms. Ask what metrics they guarantee or commit to improving. Be skeptical of 6 or 12 month minimum commitments, especially if the agency can't show case studies with timeline and results.

We offer month-to-month contracts with no long-term commitment, though we recommend a 3-4 month initial engagement to see full optimization impact before scaling. We have to earn your business every month based on measurable citation rate improvements and pipeline impact. If we don't deliver, you can walk away with 30 days notice.

5. B2B specialization and regulatory understanding

B2B buying cycles are longer, involve multiple stakeholders, and require verifiable claims. Consumer-focused agencies don't understand these nuances.

Ask for case studies in your industry or adjacent B2B verticals. Ask how they handle compliance review processes. Ask about their experience with third-party validation requirements.

We exclusively serve B2B & B2C SaaS. We understand content for regulated industries requires third-party validation and verifiable sources, which is why the T and A in CITABLE focus specifically on these requirements.

Top GEO agencies for B2B SaaS: A comparative analysis

The GEO agency market is nascent. Most players are traditional SEO agencies adding services. Here's how specialized firms compare:

Pricing sources: Quoleady packages and Omniscient Digital services as of January 2026.

The comparison reveals a pattern. Traditional agencies offer lower content volume and longer contracts because they're optimizing for Google rankings, which change slowly. GEO-specialized agencies offer higher volume and shorter contracts because we're optimizing for AI citations, which require continuous freshness signals and rapid iteration.

Most traditional content agencies excel at thought leadership and editorial quality but don't structure content for LLM retrieval. The result is beautifully written pieces that rank well in Google but never get cited by ChatGPT.

How Discovered Labs approaches Generative Engine Optimization

We start with an AI Visibility Audit that tests 50 to 100 high-intent buyer queries across ChatGPT, Claude, Perplexity, Google AI Overviews, and Microsoft Copilot. The audit reveals exactly where competitors are cited and where you're invisible.

Most companies discover they appear in fewer than 5% of relevant queries while competitors dominate 60% to 75%. That gap represents lost pipeline. Every query where a competitor is recommended instead of you is a buyer who shortlists them, not you.

The audit becomes your strategic roadmap. We prioritize content that targets your biggest gaps, then structure every piece using the CITABLE framework to maximize citation probability.

Our production process ships content daily:

1. Research and query mapping: We identify the exact questions buyers ask AI and map them to content topics
2. CITABLE structuring: Every piece opens with entity clarity, includes third-party validation, uses verifiable facts, and organizes information in 200-400 word blocks optimized for RAG
3. Schema implementation: We add structured data (Organization, Product, FAQ schemas) so AI systems can parse relationships
4. Citation tracking: We monitor which AI platforms cite the content, which specific queries trigger citations, and how citation rates trend over time

We track what works, analyze why, then adjust the next day's content based on that data. This velocity advantage means we learn faster than agencies shipping 10 pieces per month.

Beyond owned content, we help you build third-party validation through Reddit marketing campaigns, review generation on G2 and Capterra, and strategic mentions in industry forums. AI models trust external sources more than your own site. Consistent information across platforms increases citation confidence.

Measuring the ROI of AI visibility

The primary metric is citation rate. What percentage of your target buyer queries result in your brand being cited or recommended by AI systems?

A baseline audit typically shows 0% to 5% for companies with no GEO optimization. After 3-4 months of daily content production and third-party validation, citation rates should reach 40% to 50% of priority queries.

Citation rate directly impacts pipeline. AI-referred visitors are pre-qualified. The AI system already told them you're a good fit. That's why they convert at dramatically higher rates.

Ahrefs published data showing AI-referred traffic converts at 2.4x higher rates than traditional organic search visitors. For B2B companies with long sales cycles and high deal values, that conversion advantage translates directly to pipeline ROI.

We helped a B2B SaaS company improve ChatGPT referrals by 29% and close 5 new paying customers in the first month of working together. Another client went from 500 AI-referred trials per month to over 3,500 trials in around 7 weeks.

To track this in your CRM, we recommend creating a custom lead source field "AI Assistant Referral" and tagging landing pages with UTM parameters like utm_source=ai_search&utm_medium=chatgpt. We provide monthly executive reports showing AI-referred MQL volume, SQL conversion rates, and pipeline value compared to traditional organic search.

They store the recommendation, then visit your site days or weeks later through direct traffic. This attribution complexity means you're likely undercounting AI influence, which is why we focus on Share of Voice as the leading indicator.

If your citation rate is increasing, pipeline impact follows within 60-90 days. We recommend you track both metrics together to build the full ROI picture.

What to ask before hiring a GEO agency

"Can't our current SEO agency just add GEO services?"

Probably not. Traditional SEO agencies lack the tooling to track citations across AI platforms and the methodology to write for LLM retrieval. They optimize for crawlers, not reasoning engines.

Ask your current agency to show you:

• Citation tracking reports across ChatGPT, Claude, and Perplexity
• Examples of content structured specifically for RAG
• Case studies showing citation rate improvements with timeline and metrics

If they can't produce these, they're adapting SEO tactics rather than engineering for AI systems.

"How long until we see results?"

Initial citations typically appear within 3-4 weeks as fresh content gets indexed and retrieved. Full optimization takes 3-4 months to reach 40% to 50% citation rates.

The timeline depends on your starting point (completely invisible vs. already cited occasionally), competitive intensity in your category, and content velocity. Daily production accelerates results because it creates more citation opportunities and signals freshness to AI models.

"What if AI algorithms change and our optimization stops working?"

AI platforms update retrieval logic constantly. That's why continuous testing and optimization matter more than one-time content projects.

We build for durable principles (clarity, verifiability, entity structure) that work across models rather than gaming specific platforms. Our internal tools track citation patterns across multiple AI systems, so when one platform changes behavior, we spot it immediately and adjust.

We run original research to validate assumptions rather than following social media advice. That data advantage lets us adapt faster than agencies that wait for industry consensus.

Frequently asked questions about GEO agencies

How much does a GEO agency cost? Pricing ranges from $1,500 per month for basic packages to $25,000+ per month for enterprise clients. Discovered Labs starts at approximately €5,495 per month with month-to-month terms. Traditional SEO agencies charging $8,000 to $15,000 per month typically deliver 10-15 blog posts. We start at 20 pieces minimum with GEO-specific optimization.

Can we build GEO expertise in-house instead of hiring an agency? You can, but it requires hiring specialized talent, building citation tracking tools, and maintaining expertise across multiple AI platforms. Most companies find that distraction from core business outweighs the cost savings. Agencies offer data advantages from working across multiple clients and continuous platform testing.

Do we need to stop SEO to focus on GEO? No. GEO complements SEO. Content optimized for AI citations typically ranks well in traditional search too because the core principles (clarity, authority, verifiability) overlap. You're expanding distribution channels, not replacing one with another.

Key terminology for AI search optimization

Entity: A person, place, company, product, or concept with distinct, identifiable properties that AI systems can recognize and connect to other entities in knowledge graphs.

Knowledge graph: A structured database that maps relationships between entities, allowing AI systems to understand how concepts connect and retrieve relevant information for synthesis.

RAG (Retrieval-Augmented Generation): The technical architecture AI search systems use to retrieve external documents, chunk them into semantically relevant passages, then synthesize those passages into generated answers.

Citation rate: The percentage of relevant buyer-intent queries where an AI system mentions or recommends your brand in its generated answer.

Share of Voice: Your brand's citation rate compared to competitors' citation rates across a defined set of target queries, typically expressed as a percentage of total mentions.

Third-party validation: External confirmation of claims from sources beyond your own website, such as reviews, news articles, community discussions, or industry reports that AI systems use to verify accuracy.

See where you stand in AI search today

When your prospects use AI to research vendors and you're not cited, you miss opportunities to enter their consideration set. Buyers create shortlists of 3-5 options from ChatGPT recommendations before they contact anyone.

Traditional content marketing optimized for Google rankings can't fix this. AI systems retrieve and cite content based on different signals. You need a specialized partner who understands how LLMs make citation decisions and can track your visibility across platforms.

We offer month-to-month contracts and deliver citation tracking reports weekly so you can see exactly where progress is happening. Book a strategy call to discuss your AI visibility gaps and get a custom roadmap. Or request an AI Visibility Audit to see precisely where competitors are cited while you're invisible across 50-100 buyer-intent queries.

We help you start capturing AI-referred leads before your category's AI answer landscape gets competitive.