What is Generative Engine Optimization (GEO)?

Generative Engine Optimization (GEO) is the practice of structuring your content, technical infrastructure, and brand presence so AI platforms like ChatGPT, Claude, Perplexity, and Gemini cite you as the trusted source, not your competitors.

How do you track AI citations?

We track AI mentions across ChatGPT, Claude, Perplexity, and Gemini in real-time, showing you exactly when you're recommended and when competitors win instead. You get monthly reports with citation metrics, prompt performance, and competitive analysis.

What industries do you serve?

We work with consumer & e-commerce brands, local & service businesses, B2B SaaS companies, and agencies & professional services where AI recommendations directly influence purchasing decisions.

How to Choose a GEO Agency in 2026

The best GEO agency is the one that measures real AI citations rather than vanity metrics, leads with strategy before content, owns the technical infrastructure, and can prove results. Generative Engine Optimization is a new category, so use these seven questions to separate genuine GEO specialists from traditional SEO agencies that have bolted AI onto an old playbook.

1. Do they actually measure AI citations?

Ask how they track visibility across ChatGPT, Claude, Perplexity, and Gemini. A real GEO agency reports citation rate, share of voice versus named competitors, and the source URLs being cited, not generic traffic charts. If they cannot show how they measure citations, they cannot improve them.

2. Do they start with strategy or content?

Strong agencies start by identifying which prompts drive your business and where competitors are cited instead of you, then prioritize high-impact work. Agencies that start by generating content volume without a prompt strategy are optimizing for activity, not citations.

3. Do they own the technical infrastructure?

GEO requires llms.txt, JSON-LD schema, AI-crawler configuration, and entity optimization. Ask whether they implement these directly or only advise. The technical layer is where many citations are won or lost.

4. Is it done-for-you or a tool?

Some vendors sell software that requires your team to figure it out. A done-for-you agency handles strategy, content, technical implementation, and tracking end to end. Decide which model fits your team's capacity.

5. Can they prove results?

Ask for a concrete example with a real outcome and timeline. As a benchmark, LLMReach moved NexumAutomations from 0% to 52% AI visibility in 20 days. Look for specific before-and-after citation data, not vague promises.

6. Are they transparent about what they do?

You should understand exactly what work is being done and why each item drives citations. Beware black-box engagements that cannot explain the connection between the work and AI visibility.

7. Do they specialize in GEO?

Citation logic is fundamentally different from ranking logic. An agency built specifically for Answer Engine and Generative Engine Optimization will usually outperform a generalist SEO shop that treats AI as an add-on.

Red flags to avoid

Guarantees of a specific number of citations (no one can guarantee AI output).
Only vanity metrics like impressions, with no citation tracking.
No technical implementation, advice only.
No clear reporting cadence.

Frequently Asked Questions

How much should a GEO agency cost?

Pricing depends on scope: how many prompts and platforms you target, your current authority, and how much content and technical work is required. A credible agency scopes the engagement after an AI visibility audit.

How fast should I expect results?

AI citations can move faster than traditional SEO. Expect the first 30 to 90 days to be the momentum window, with gains compounding as authority builds.

What makes LLMReach different?

LLMReach is built specifically for GEO and AEO, measures real citations across four platforms, leads with prompt strategy, and implements the technical infrastructure directly. Learn more on the industries page.

Evaluating agencies? Book a free AI Visibility Audit with LLMReach and see your baseline first.