Generative Engine Optimization: All you need to know about Generative Engines

Generative Engine Optimization: In the past 3 years, the way we search for information has been evolving rapidly. Search Engines (SEs) are being supplemented or in some cases, replaced by Generative Engines (GEs). These AI engines perform not only information retrieval, but also human-like responses generation based on pre-trained knowledge and real-time web searches. 

As generative engines continue to advance, when it comes to digital marketing, we need to prepare ourselves for Generative Engines Optimization (GEO).  In this blog, we'll explore how GEs are reshaping search, how they function, how they compare to traditional search engines, and what content creators and marketers need to do to stay ahead.

Generative Engines in 2025 

GEs are set to redefine the search landscape. Major players like Claude, Llama, Perplexity, ChatGPT, Gemini, and Google AI are leading the charge with different approaches to search and information retrieval: 

Llama: Uses training data to interpret queries and generates responses directly from its internal knowledge base. (Source: Meta) 

Perplexity, Google AI Overviews (AIO): Use web search data to generate responses, ensuring that users receive up-to-date information with citations. (Source: Perplexity, Google) 

Claude, ChatGPT (SearchGPT), Gemini: Leverage both training data and search data, intelligently routing queries through their internal knowledge or live web searches, depending on the context. (Source: Claude, OpenAI, Google) 

How GEs Are Reshaping Search in 2025 

• More conversational search experiences: Users interact with AI in natural language rather than relying on keyword-based searches. 

• Faster access to summarized insights: Instead of combing through multiple sources, users get instant, synthesized responses. 

• Citation-backed responses: Unlike early generative models, newer GEs prioritize linking to credible sources, increasing trustworthiness. 

• Personalized results: AI models can adapt responses based on user preferences and context. 

Understanding How Generative Engines Work 

The Technology Behind GEs 

Generative Engines operate on a combination of AI, Large Language Models (LLMs), and Natural Language Processing (NLP). Generative Engines' core process includes: 

1. Query Interpretation: The model understands intent and context. 

2. Data Retrieval: Depending on the query, the model pulls information from either pre-trained data or a live web index. 

3. Response Generation: AI generates human-like answers, sometimes citing sources. 

4. User Interaction & Refinement: Users can refine queries, enabling more personalized results. 

Flowchart of Generative Engines From a GEO Research Article 

Why GEs Are Gaining Popularity 

Are GEs Becoming a Trend? 

We believe Generative Engines (GEs) are becoming a trend, and the numbers speak for themselves. According to Reuters, OpenAI reported that as of February 2025, ChatGPT now has over 400 million weekly active users, highlighting its explosive growth and widespread adoption. On the other hand, Google, the world's most widely used search engine, has introduced Google AI Overviews, signaling a major shift from traditional search engine results pages (SERPs) to AI-generated insights. As you can see, from both the consumer and business perspectives, it's clear that GEs are the trend. 

Why Are GEs Becoming a Trend? 

• No need for keyword hacks – Users can ask questions naturally. 

• Faster decision-making – Instead of browsing multiple links, users get concise, direct answers. 

• More interactive – Users can refine responses dynamically. 

• Multimodal capabilities – Some GEs can process images, videos, and even voice queries. 

GEO – The Future of Digital Marketing 

With GEs changing search behavior, Generative Engines Optimization (GEO) is emerging as a crucial strategy for content creators and marketers. A GEO study was conducted and concluded with an impactful statement. In the study, researchers studied nine factors to understand what correlated with the likelihood of impacting the AI's response. These factors were:  

• Keyword Stuffing 

• Unique Words 

• Easy-to-Understand 

• Authoritative 

• Technical Terms 

• Fluency Optimization 

• Cite Sources 

• Quotation Addition 

• Statistics Addition 

The result showed the top-performing optimizations for the GEO efforts included:  

• Quotation Additions 

• Statistic Additions 

• Fluency Optimization 

• Cited Sources 

• Technical Terms 

• Authoritative 

It shows that content that incorporated these top-performing strategies saw a more than 40% increase in visibility across various AI-generated responses. These findings highlight the critical importance of creating content that is not only accurate but also rich, well-sourced, and authoritative—key ingredients for standing out in generative search. 

Conclusion 

The rise of Generative Engines signals a shift in how people look up for information. While traditional SEO still matters, GEO is becoming increasingly important as more users rely on AI-driven responses. Content creators, marketers, and businesses need to adapt. Understanding how GEs work and optimizing your content accordingly will be crucial in staying relevant in the AI-driven search landscape of 2025 and beyond.