GEO Agency Selection Checklist: 25 Questions to Ask (2026)

Updated January 07, 2026

48% of B2B buyers use AI to find vendors, and most marketing leaders face a new problem: every SEO agency added "AI optimization" to their website in 2024, but most are repackaging keyword tactics for a fundamentally different system.

Traditional search engines rank lists of links. Generative engines synthesize single answers. The questions you used to vet SEO partners will lead you to hire the wrong agency for this shift, wasting budget on vendors who don't understand how LLMs decide what to cite.

This checklist gives you 25 specific questions to ask vendors, organized by methodology, measurement, execution, commercial terms, and strategic fit. For each question, I'll show you what good answers look like and the red flags that expose generalists posing as specialists.

Why traditional SEO questions fail in the AI era

Traditional search engines present a ranked list of 10 blue links, so SEO agencies optimized for position, domain authority, and backlink profiles to get you into that top 10. Generative engines work differently by synthesizing information from multiple sources and presenting a single, conversational answer. About 60% of searches now end without the user progressing to another destination site.

We've tracked a profound technical shift. Traditional systems use keyword matching and static databases to find information. Retrieval-augmented generation (RAG) enables LLMs to retrieve and incorporate new information from external data sources before generating responses. RAG doesn't just rank your page, it decides whether to quote it, paraphrase it, or ignore it entirely based on entity structure, verifiability, and third-party validation.

When you ask a potential agency "How will you get me to #1 on Google?" you're asking the wrong question. The new goal is "How will you get me cited in the consensus answer when buyers ask AI for recommendations?"

We see this shift confirmed in the data. ChatGPT dominates the US market with 59.5% share, followed by Copilot at 14%, Gemini at 13.4%, Perplexity at 6.2%, and Claude at 3.2%. Your buyers use these platforms to shortlist vendors, and AI search visitors convert at 4.4 times higher value compared to traditional organic search visitors.

The 25-question GEO agency evaluation framework

Use these questions in your vendor calls. The good answers align with how LLMs actually work. The red flags indicate an agency is guessing or simply rebranding SEO services without understanding retrieval mechanics.

Methodology and technical approach (Questions 1-5)

1. What is your proprietary methodology for getting brands cited by AI systems?

What to look for: A named framework with specific components addressing entity structure, answer format, and verification. For example, Discovered Labs uses the CITABLE framework with seven elements: Clear entity and structure, Intent architecture, Third-party validation, Answer grounding, Block-structured for RAG, Latest and consistent information, and Entity graph and schema.

Red flag: Vague answers like "we create high-quality content" or "we optimize for AI." If they can't name their methodology, they're improvising.

2. How do you handle entity optimization versus keyword optimization?

What to look for: The agency should explain that entity authority establishes the semantic authority generative engines require before citing your brand. They should discuss Knowledge Graph signals, structured data implementation (Organization and Product schemas), and explicit entity mentions in content.

Red flag: They focus exclusively on "long-tail keywords" or "search volume." Entity optimization is about making your brand a recognized, authoritative entity that AI systems understand in relation to problems and solutions.

3. How do you structure content for RAG (retrieval-augmented generation) specifically?

What to look for: Discussion of 200-400 word passage blocks, direct answer formats, FAQ schema, and tables. The agency should explain that LLMs extract passages, not entire pages, so block-structured content optimized for RAG creates clear extraction targets.

Red flag: "We write long-form blog posts with good structure." That's SEO thinking. RAG requires passage-level optimization with self-contained units that answer specific sub-questions.

4. What role does third-party validation play in your approach?

What to look for: The agency should emphasize external mentions on Reddit, G2, news sites, and Wikipedia as critical signals. AI models trust external sources more than your own site, and consistent information across sources increases citation confidence.

Red flag: "We focus on your owned content first and maybe do some PR later." Third-party validation should be a parallel workstream, not an afterthought.

5. How do you prevent or address AI hallucinations about our brand?

What to look for: Discussion of entity consistency across all platforms, disambiguation through structured data, and correcting conflicting information. AI models skip citing brands with conflicting data across sources.

Red flag: They've never considered this issue or say "AI just figures it out." Hallucinations happen when entity signals are weak or contradictory.

Measurement and attribution (Questions 6-10)

6. How do you measure citation rate, and what platforms do you track?

What to look for: Automated testing of your brand's mention rate across ChatGPT, Claude, Perplexity, Google AI Overviews, and Copilot using 50-100 buyer-intent queries. They should provide baseline citation rate and weekly trend reports. Citation rate is the percentage of relevant AI responses that mention your brand.

Red flag: "We manually check a few queries" or "We track your Google rankings as a proxy." Manual checking doesn't scale, and only 12% of sources cited across ChatGPT, Perplexity, and Google AI features match each other.

7. Can you show us a sample citation tracking dashboard or report?

What to look for: A visual dashboard showing citation rate over time, breakdown by platform, competitive share of voice (your mentions vs. top 3-5 competitors), and query-level detail. Discovered Labs provides weekly reports with these metrics.

Red flag: "We send monthly summaries in a PDF" or they can't produce a sample. If they don't have dashboards, they're not systematically measuring.

8. How do you attribute AI-referred traffic and pipeline to your efforts?

What to look for: UTM tagging strategies, traffic source analysis separating "AI-referred" sessions, CRM integration to track MQLs and SQLs from AI channels, and conversion rate comparison. The agency should explain that AI search visitors demonstrate 4.4 times higher value compared to traditional organic search visitors.

Red flag: "Attribution is hard, so we focus on visibility metrics." Attribution is challenging, but a sophisticated partner builds it into their reporting from day one.

9. What is a realistic citation rate target for our industry and timeline?

What to look for: Honesty about starting from low single digits for most companies, targeting 40-50% of priority buyer queries within 3-4 months, and acknowledging that initial citations appear within 2-4 weeks but measurable pipeline impact takes 90 days.

Red flag: "We'll get you to 80% in 30 days" or "We guarantee top placement." LLMs operate stochastically, meaning identical prompts can yield different responses up to 70% of the time, making guarantees impossible.

10. How do you benchmark our performance against competitors?

What to look for: Competitive share of voice reports showing what percentage of AI answers cite you vs. competitors across the same query set. Understanding why competitors are cited when you're not is the foundation of strategy.

Red flag: "We focus on your performance, not competitors." Competitive context is essential because you're competing for limited citation slots.

Content operations and velocity (Questions 11-15)

11. What is your content production velocity, and why does it matter?

What to look for: Daily or near-daily publishing (20-30 pieces per month minimum for serious impact). The agency should explain that freshness signals matter to LLMs, and high-frequency publishing creates more citation opportunities. We start our packages at 20 articles per month because volume creates topical authority faster than sporadic posting.

Red flag: "We produce 8-10 high-quality blog posts per month." That's traditional SEO cadence. For GEO, frequent targeted answer content outperforms fewer long-form pieces.

12. Do you write content specifically to answer buyer questions, and how do you identify those questions?

What to look for: A process for mapping buyer-intent queries (what prospects actually ask ChatGPT), clustering questions by topic, and creating direct-answer content for each. The agency should use tools like AnswerThePublic, Reddit mining, sales call analysis, and G2 review scraping.

Red flag: "We do keyword research and write SEO content around those keywords." That's backward. Start with buyer questions, not search volume.

13. Who creates the content, and what is their technical depth?

What to look for: A team that includes engineers or data specialists, not just writers. GEO requires implementing structured data, understanding entity graphs, and testing content variations across AI platforms. Discovered Labs was built by an AI researcher and a demand generation marketer, not adapted from an SEO agency.

Red flag: "Our writers are trained in SEO best practices." Writers alone can't implement schema, diagnose entity issues, or interpret citation patterns.

14. How do you implement structured data and schema markup?

What to look for: Automatic implementation of Organization, Product, FAQPage, and HowTo schemas on every relevant piece of content. The agency should explain that structured data feeds clear signals to AI about your company.

Red flag: "We can add schema if you want, but it's optional." It's not optional. Schema is foundational for entity clarity.

15. What content formats do you produce beyond blog posts?

What to look for: Original research studies, comparison pages, landing page optimization, glossaries, and FAQs. The agency should explain how different formats serve different parts of the buyer journey and create diverse citation opportunities.

Red flag: "We focus on blog articles." You need a portfolio of formats to maximize citations across query types.

Commercial terms and risk (Questions 16-20)

16. What is your contract length, and can I cancel if results don't materialize?

What to look for: Month-to-month terms with 30-day notice to cancel. This structure puts performance risk on the agency, not you. Discovered Labs offers rolling monthly contracts because we're confident in delivering measurable citation improvement within 90 days.

Red flag: "We require a 6-month or 12-month commitment to see results." Long lock-ins benefit the agency, not you. If they're confident in their methodology, they should accept month-to-month risk.

17. What is your pricing structure, and what's included?

What to look for: Transparent, flat-rate monthly pricing covering content production, citation tracking, competitive analysis, and third-party validation campaigns. GEO agency pricing ranges from $1,500 to $50,000+ per month based on business size and complexity. For B2B SaaS companies at $2M-$50M ARR, expect $5,000-$25,000/month for comprehensive service.

Red flag: Opaque pricing or "let's talk" responses signal they'll customize based on what they think you can pay, not value delivered.

18. Do you have setup fees or onboarding costs separate from the monthly retainer?

What to look for: Either no setup fees, or transparent one-time costs for audits and technical implementation. Some agencies charge $3,000-$5,000 for an initial AI visibility audit, which is reasonable if it includes competitive benchmarking.

Red flag: "Setup is $15,000-$20,000 before monthly work begins." High setup fees often pad revenue without delivering proportional value.

19. Do you work with our competitors or have exclusivity policies?

What to look for: Clear exclusivity within your specific niche (they won't simultaneously represent two direct competitors). The agency should disclose existing clients in adjacent categories.

Red flag: "We don't do exclusivity" while working with three of your competitors. Your strategy could inform their recommendations to rivals.

20. What happens to content and data if we part ways?

What to look for: You retain full ownership of all content created, and you can download citation tracking data and reports. The agency may retain their proprietary methodology and dashboards, but raw data should be exportable.

Red flag: "Content belongs to us" or "Data stays in our system." You're paying for the work, you should own the assets.

Strategic fit and expertise (Questions 21-25)

21. What specific experience do you have with B2B SaaS or our industry vertical?

What to look for: Case studies from companies in your category with specific metrics. For example, Discovered Labs helped a B2B SaaS company grow from 550 to 2,300+ AI-referred trials in four weeks, and improved ChatGPT referrals by 29% in month one for another client. The agency should understand long sales cycles, technical buyers, and multi-stakeholder decisions.

Red flag: "Our strategies work across all industries." B2B SaaS has unique needs (technical documentation, integration content, developer-focused answers) that generalists miss.

22. If we operate in healthcare, fintech, or another regulated industry, how do you ensure compliance?

What to look for: Experience with verifiable claims, HIPAA considerations (if healthcare), and third-party validation requirements. The agency should emphasize that answer grounding with verifiable facts and sources is even more critical in regulated industries.

Red flag: "We'll figure it out" or no mention of compliance concerns. Regulated industries require specialized content review.

23. How do you adapt strategy when AI platforms update their models or retrieval logic?

What to look for: Discussion of continuous testing, rapid iteration, and learning from multiple clients across industries. The agency should acknowledge that AI platforms change retrieval algorithms, so ongoing optimization is necessary.

Red flag: "Our approach is evergreen and doesn't need updating." AI systems evolve constantly. Static strategies fail.

24. Can you provide a reference client we can speak with?

What to look for: Willingness to connect you with a current client (with that client's permission) who can share their experience on citation growth, reporting quality, and commercial relationship.

Red flag: "All our clients are under NDA and can't be references." Some confidentiality is normal, but if no one will vouch for them, that's a warning sign.

25. What do you need from us to be successful, and what's the expected time commitment from our team?

What to look for: Realistic expectations: content review and approval (2-4 hours per week), access to subject-matter experts for technical content (2-3 hours per week), CRM integration for attribution tracking (one-time setup). Discovered Labs handles end-to-end content production, but we need your team's input for accuracy and brand voice.

Red flag: "We need full-time access to your entire marketing team." Agencies should reduce your workload, not add to it.

7 red flags that signal "fake" GEO expertise

Watch for these warning signs that indicate an agency is repackaging SEO rather than delivering true generative engine optimization:

1. They guarantee specific rankings or top positions. LLMs operate stochastically, meaning identical prompts can yield different responses up to 70% of the time, making guaranteed placements impossible. Legitimate agencies talk about improving citation rate percentages over time.
2. They focus only on Google AI Overviews or treat GEO as an "add-on" to PPC retainers. ChatGPT dominates with 59.5% of the US market, and only 12% of sources overlap across platforms. Optimizing for a single platform or bundling GEO with unrelated services means they're experimenting with your budget.
3. They claim to use "proprietary AI" to write all content without human review. AI-generated content without expert review, fact-checking, and entity verification creates the opposite of what you need. Third-party validation and answer grounding require human judgment.
4. They require 12-month contracts with no performance guarantees. Long lock-ins protect agencies from accountability. If their methodology works, they should accept month-to-month terms and earn your business every 30 days based on measurable citation growth.
5. They can't show you a citation tracking report or dashboard. Agencies without systematic measurement are guessing. Citation rate and share of voice are the core metrics for GEO. If they don't track them, they're not optimizing for them.
6. They use vague buzzwords without technical depth. If the pitch is full of "synergy" and "game-changing AI" without explaining RAG, entity graphs, or passage-level optimization, they're selling hype. Ask them to explain how retrieval-augmented generation differs from traditional indexing. If they can't, they don't understand the system.

Decision matrix: How to score your shortlist

Score each agency on a 1-10 scale for each criterion, multiply by the weight, then sum for a total score out of 100.

Example Calculation:
Agency A scores: Methodology 8/10 (×0.25 = 2.0), Reporting 9/10 (×0.25 = 2.25), Expertise 7/10 (×0.15 = 1.05), Terms 10/10 (×0.15 = 1.5), Experience 8/10 (×0.10 = 0.8), Coverage 9/10 (×0.10 = 0.9) = Total: 8.5/10 or 85/100

Any agency scoring below 60/100 lacks critical capabilities. Agencies scoring 70-80/100 are competent but may have gaps. Agencies above 80/100 demonstrate comprehensive GEO expertise and should advance to contract negotiations.

How we answer these 25 questions

We built this checklist based on the standards we set for ourselves. Here's how we approach each category:

Methodology: We use the CITABLE framework to ensure content is optimal for LLM retrieval: Clear entity and structure, Intent architecture, Third-party validation, Answer grounding, Block-structured for RAG, Latest and consistent information, and Entity graph and schema.

Measurement: We track citation rate across ChatGPT, Claude, Perplexity, Google AI Overviews, and Copilot using proprietary tools. You get weekly reports showing your citation percentage, competitive share of voice, and trending queries. Our AI visibility audits test 50-100 buyer-intent queries to show exactly where you're invisible and where competitors dominate.

Content velocity: Our packages start at 20 articles per month. High-velocity, high-frequency content signals freshness to LLMs and creates more citation opportunities than sporadic posting. We also handle content refreshes, landing pages, and original studies.

Commercial terms: We offer month-to-month contracts with no long-term lock-in. If we don't improve your citation rate and deliver measurable pipeline impact within 90 days, you can cancel.

Team structure: We were founded by an AI researcher who built systems using LLMs and a demand generation marketer who helped B2B companies scale to $20M+ ARR. We run our own research and development, which allowed us to spot that the Reddit crisis was overblown while others panicked.

Reddit and third-party validation: We operate a dedicated Reddit marketing service with aged, high-karma accounts that rank in any subreddit, and we orchestrate G2 reviews, industry forum mentions, and PR to build the external validation signals AI systems trust.

Results: We helped a B2B SaaS company grow from 550 to 2,300+ AI-referred trials in four weeks, and improved ChatGPT referrals by 29% in month one for another client.

Request an AI Visibility Audit to see where you currently stand. We'll test your brand against 50-100 buyer queries across all major AI platforms and show you the exact citation gaps costing you deals.

Frequently asked questions about GEO agencies

What is the core difference between an SEO agency and a GEO agency?
SEO agencies optimize for ranked lists of links using keyword density, backlinks, and domain authority. GEO agencies optimize for citation in synthesized answers using entity structure, passage-level extraction, and third-party validation.

How much does a GEO agency typically cost?
GEO agency pricing ranges from $1,500 to $50,000+ per month based on business size and complexity. Small businesses start at $1,500-$5,000 per month, while mid-market B2B SaaS companies typically invest $5,000-$25,000 per month for comprehensive service including daily content, multi-platform tracking, and third-party validation campaigns.

How long does it take to see results from GEO optimization?
Initial AI citations appear within 2-4 weeks, faster than traditional SEO's 3-6 month timeline. Measurable pipeline impact typically takes 90 days as citation rates climb to 40-50% of priority buyer queries.

Can I do GEO in-house instead of hiring an agency?
Yes, but it requires engineering resources for citation tracking, data specialists to analyze LLM behavior, and writers who understand entity optimization. Discovered Labs built proprietary tools to track citations across platforms because out-of-the-box software doesn't exist yet.

Should I stop investing in traditional SEO if I start GEO?
No. Around 40.58% of AI citations come from Google's top 10 results, so strong SEO foundations help GEO performance. Think of GEO as an evolution of SEO, not a replacement.

Key terminology for GEO agency evaluations

Citation rate: The percentage of relevant AI-generated responses that cite, mention, or reference a specific brand. This metric has become the new standard for measuring success in Answer Engine Optimization.

LLM (Large Language Model): Advanced AI systems trained on vast amounts of text data to understand and generate human-like language, powering platforms like ChatGPT, Claude, and Gemini.

RAG (Retrieval Augmented Generation): A technique that enables LLMs to retrieve and incorporate new information from external data sources before generating responses. Unlike static training data, RAG pulls relevant text from databases or web sources in real-time.

Entity authority: The semantic authority that brands must establish in order to appear in AI summaries and search results. It creates the structured data pathways AI systems follow.

Share of voice: The percentage of AI-generated responses in your category where your brand is mentioned compared to competitors. LLMs cite limited sources per response, making this a competitive metric.