What Is Generative Engine Optimization (GEO) and How to Implement It?

Are you wondering how to make your brand visible in a world where AI models like ChatGPT, Perplexity, and Google Gemini set the tone? Or would you like to know if these technologies are really relevant to you?

In this guide you will learn what the term Generative Engine Optimization (GEO) means, what different types of AI engines are available, and get practical tips on whether and how you should engage with this topic.

What are Generative AI Engines?

Generative AI engines or generative AI systems, process large amounts of data to provide accurate and comprehensive answers to user inquiries. They utilize advanced machine learning models that can understand and process natural language to deliver relevant and context-aware responses.

What is Generative Engine Optimization (GEO)?

GEO is the process of optimizing a digital brand, its content, and marketing strategies to maximize visibility in relevant responses from generative AI models such as ChatGPT, Perplexity, and Google Gemini. The goal is to help businesses prominently place their brand, services, and products in the outputs of leading Generative Engines like ChatGPT, Google Gemini, Perplexity, and Google SGE.

Here is an example response from Yazo AI in the B2B energy sector:

"Who can provide me a consistently low industrial electricity price?"

And, here is how Perplexity can respond for query in the B2B service sector:

What is the best SEO agency?

Combining LLM with RAG

Large language models (LLMs) like ChatGPT or Google Gemini sometimes provide precise answers, while at other times they offer confusing or incorrect information. They do not understand content but analyze how words relate to each other. Solution for this issue is RAG.

What is Retrieval Augmented Generation (RAG)?

RAG improves the quality of AI responses by accessing external sources. This way, the model combines its own knowledge with current information.

Advantages of RAG:

• Access to current, reliable facts.
• Transparency: Users can see the sources of the answers.
• Reduces the need to constantly retrain a model and ensures more trustworthy responses.

What RAG means to you?

Systems like ChatGPT-4 and Google Gemini use RAG to pull current content from search engine indexes.

Here’s how it works:

• Internal data: The LLM uses its training knowledge. This is largely beyond your influence.
• External sources: Current content from the web is added. Here, you can generate more visibility through SEO.

End result: A mix of relevant information and facts that are unique in their combination.

Here is a short list of top AI engines and search engines which they use:

• ChatGPT = Bing
• Gemini = Google
• Perplexity has its own search engine

The Three Types of Generative AI Engines

What types of generative AI engines exist?

Training-based systems (e.g., Claude, Llama)

These models are based solely on their training data.
Influence? Only through long-term measures like digital PR and an expanded digital footprint.

Search-based systems (e.g., Google AI Overviews, Perplexity)

These engines utilize real-time indexing of web pages.
Here you can excel with classic SEO: Ensure that your content is included in the referenced sources.

Hybrid systems (e.g., Google Gemini, ChatGPT Search)

Combine training data with current web content.
Example: foundational knowledge comes from the model, while current recommendations are sourced from the web.

Does generative AI change impact search traffic?

Many believe that tools like ChatGPT and Perplexity will replace traditional search. But what if they are just changing the market instead? After all, the demand remains the same; customers are just getting to their goals faster.

Traditional search queries were often simple and direct. However, AI tools like ChatGPT, Google Gemini, AI Overviews, and Perplexity open up entirely new possibilities for more complex questions—ones that couldn’t even be answered before.

Instead of simply searching for “best smartphones 2025,” one might ask generative engines: “Which smartphone under $500 are best suited for gaming and have a long battery life?” Now, thanks to AI-powered chatbots and search engines, a helpful answer can be provided—perhaps even curated from multiple sources.

Of course, AI could replace some traditional search queries. The big question is how valuable this superficial demand ever was for companies.

According to a Gartner forecast, the volume of traditional search engines is expected to decline by 25% by 2026, while AI engines gain market share. Major analysts, like Alan Antin, believe that GenAI solutions are becoming substitute answer engines, replacing user queries that previously have been executed by traditional search engines. This forces companies to rethink their marketing channels and adapt their marketing strategy to new trends.

As is often the case, significant behavior changes typically take longer than expected, especially when trust is low. Nevertheless, it is recommended to keep an eye on referral traffic and thoroughly assess the potential in your industry. More on this at the end of the guide.

Summary:

• Generative AI creates new opportunities for how people search – companies that adapt will benefit.
• Search queries are becoming more complex.
• Simply phrased search queries are likely to decline.

Should you optimize your brand for generative engines?

Yes, because while we are still at the beginning, this technology is already relevant today.

• ChatGPT has over 3.8 billion monthly visits (Source: SimilarWeb).
• Outgoing traffic is growing (Source: Growth Memo).
• Perplexity processes more than 100 million queries per week.

The significance of generative engines is rapidly increasing.

Here is our recommendation for budget allocation:

• If your SEO strategy is already strong, invest an additional 10-15% of your SEO budget in GEO.
• If SEO still needs to be developed, prioritize this area. GEO builds on these results.

According to a recent analysis by Seer Interactive, there is a strong correlation (approximately 0.64) between the Google page-1 rankings of a digital brand and mentions in LLMs. Note: Correlation does not imply causation!

Source: Seer Interactive

Conclusion

Generative engines will not make classic SEO, content marketing, and digital PR obsolete; rather, these measures are the foundation for success on these AI platforms. Another perspective is that generative engines are merely an improved interface for accessing information.