For nearly two decades, we have been used to a world dominated by traditional search engines.
However, as large language model (LLM) technology has evolved, we are now witnessing the rise of the answer engine.
Generative AI tools like ChatGPT, Perplexity, Claude and Google’s Gemini (and AI Overviews) are redefining how we approach organic search.
These technologies focus on delivering instant, conversational answers, leading to a decline in traditional SERP real estate and the growth of zero-click searches.
In a recent study, Gartner projected that traditional search volume could drop by 25% by 2026, with a 50% decline in organic search traffic as more consumers turn to AI-powered tools.
The implications of this shift are profound, especially for businesses that rely on organic search traffic.
The question is: How do we adapt to remain visible if we see a continued rise in the use of answer engines?
Another step toward zero-click search
The disruption we’ve witnessed due to generative search technology is yet another factor driving a rise in zero-click searches.
For years, we’ve seen declining SERP real estate on Google due to increased SERP features.
Brands that have consistently ranked atop Google’s search results will have witnessed a slight decline in traffic over time.
Over the years, Google’s SERPs have transformed significantly, prioritizing featured snippets, knowledge panels and now generative AI summaries, leaving little room for traditional organic listings.
Today, 60% of Google searches don’t result in a click, a trend that will likely increase with AI features.
Source: SparkToro
As AI platforms continue to deliver answers without directing users to external websites, brands that rely on SEO must diversify their approach to traffic acquisition.
Traditional search is shrinking. Brands are no longer just competing for rankings on Google; they are competing for visibility on AI-driven platforms where the rules are fundamentally different.
The rise of generative engine optimization (GEO)
Generative engine optimization is an evolving practice of optimizing an entity to be featured in the responses generated by AI applications, features and models like ChatGPT, Gemini, Google’s AI Overviews, Claude and Perplexity.
ChatGPT is already averaging around 3 billion sessions per month. While that’s still some way off Google’s 80 billion global sessions per month, it’s certainly worth your attention.
Data from SimilarWeb
Isn’t GEO just SEO?
If you’ve spent time comparing the results generated by platforms such as Perplexity and ChatGPT, you’ll notice that they differ vastly from the results from Google Search.
Many of our agency clients have asked whether the rise of AI-driven platforms requires a new approach or if traditional SEO techniques still apply.
While many elements of GEO are important for SEO, some key nuances to be aware of will impact your brand’s performance more on generative engines than standard search engines.
Based on the limited published research and our own testing to date, we know that the following signals are important for increasing visibility in answer engines such as ChatGPT and Perplexity:
Structured data: Focus on key entities (people, places, concepts). Use precise terminology and provide context to help AI understand their relevance. Link to authoritative sources and markup entities to enhance AI recognition.
Citations: ChatGPT prioritizes high-authority publications, meaning “being cited” is even more important here. To improve performance, target high-authority sources used by ChatGPT to enhance brand inclusion in its responses.
Natural language: Content strategies must evolve to answer complex, multifaceted questions – rather than simply targeting specific keywords.
Now, let’s break down each pillar with a bit more detail.
1. Structured data: Optimizing for entity recognition
AI tools generate answers based on patterns and context. As such, your content must be easy for these engines to understand.
Structured data plays a crucial role in this. By marking up your content with schema, you help AI platforms recognize entities – such as people, places, products and organizations – and connect them with relevant queries.
Entity optimization is particularly important for LLMs, which rely heavily on structured information to determine how to categorize and present your brand.
Building ontologies helps AI models deliver precise information by mapping relationships between entities and content.
Think of ontology as a structured map of meaning. Creating content connected to key entities within your site helps search engines and LLMs index your website accurately.