You wrote the content. You optimized the page. You got the backlinks.

But when users ask Google Gemini or ChatGPT, your brand doesn’t appear. That’s not a ranking problem. That’s a GEO problem.

The way people search for stuff online is changing…fast. 

Not incrementally, fundamentally. 

Now, instead of scanning through the top ranked links, users are getting real AI-powered generative engine answers from search. 

And it is breaking the traditional search playbook.

Gartner estimates that by 2028, organic search traffic to brand websites could drop by 50% because users are not clicking on simple links anymore. Generative AI is doing the answering. 

This is where GEO, or Generative Engine Optimization, comes in. It provides a first-principles approach to content strategy in a world where answers are generated, not listed.

GEO offers a structured, first-principles framework to make your content visible in large language model (LLM)-driven search engines. Instead of striving for a higher page rank, you’re now optimizing for inclusion in the answers to real questions.

We’re diving into this because GEO is the first tactical framework for optimizing visibility and staying relevant in LLM-powered search engines. 

This article breaks down “GEO: Generative Engine Optimization” a breakthrough paper published by a group of researchers from IIT Delhi, Princeton University, and independent colleagues, looking at content creators improving their discoverability in AI generated searches by upwards of 40%. 

This post provides a unique lens into the future of content and discovery online. Let’s get into it. 

Traditional SEO Is Breaking, and GEO Is Replacing It

For decades, the formula for being visible online was clear. Pick the right keywords. Build your page rank and win a click. But this traditional model is collapsing.

Generative engines are giving users pulled and synthesized answers from across the web, skipping over links entirely.

Stuffing keywords, optimizing metadata, building backlinks, etc, is no longer a favored approach. Unlike SEO, which focuses on ranking for search terms, GEO optimizes for inclusion in the AI-generated response itself by matching intent, context, and authority at the content level. 

“According to the research paper: Generative Engines remove the need to navigate to websites by directly providing a precise and comprehensive response.”

You might already have tasted the difference between SEO and GEO. Run a Google search on any topic, and you will see Generative AI results, with links, displayed on the top of the page as an “AI Overview.” 

This is a wake-up call for content creators and digital marketers. The future of visibility will be shifting from page rank to Gen AI Search inclusion. 

What Visibility Means in the GEO Context

In the SEO-rules era, everything was about a higher rank. Marketers tracked their position on Google and tweaked keywords as needed. 

“But as the research paper states, “Traditional metrics such as ranking and click-through rate are insufficient to capture visibility in generative engines.” Let’s unpack that.”

GEO will help cite and surface your content on LLMs like ChatGPT, Gemini, or Perplexity. 

But how does it work? 

Interestingly, GEO treats LLMs as black boxes but still finds ways to boost your citation rate from the outside in. It studies your website’s content and rephrases it, changing everything from tone and structure to presentation and preparing it for easy reference by generative engines.

 “GEO is a flexible black-box optimization framework for optimizing web content visibility for proprietary and closed-source generative engines. It ingests a source website and outputs an optimized version by tailoring and calibrating the presentation, text style, and content to increase visibility in generative engines.”

Basically, if you want LLM to easily ‘read’ your content, there are some things you need to consider:

• Optimize content for user questions or intent
• Context, citations, and authority are important, not backlinks
• Use engagement is a journey, not just a click

Your content needs to do more than appear on a webpage. It needs to earn its place in the generative engine’s response. And unless your content has been cited and has enough authority, you risk invisibility. 

That’s why understanding how generative engines build a response and how they select, prioritize, and synthesize content is vital.

The Mechanics of Generative Answers: How Generative Engines Choose What to Cite

Generative search engines create responses from an almost chaotic mix of inputs. And because all this happens with zero visibility into the algorithm, it’s hard for creators to control what shows up. 

Sometimes you don’t even get credit, even when your content was the foundation of the answer.

But here’s the upside. GEO works with the black box, allowing you to influence what the response to a query says. 

The research breaks this down into two categories:

• Objective Metrics – Measures whether you’re cited.
• Subjective Impression Score – Takes a more nuanced approach.

Though complex, the Subjective Impression Score is the real unlock. In addition to measuring if your content is showing up early in the response, it also evaluates how well it’s landing. 

• Are you cited near the top of the answer? 
• Is your excerpt distinctive, relevant, and click-worthy? 
• Does it stand out from other sources? 

These subjective factors are better at deciding if you’re getting not just enough, but also the right attention.

Now, in the world of the bard, here’s the rub. 

Even if your content contributes to an answer, you risk not being named. If your content gets used without attribution, your efforts disappear into the AI ether. So what do you do?

• Create content that’s simple, citeable, and paraphrase-resistant
• Anticipate questions and offer direct answers
• Include citations, multi-source summaries, and paraphrased content without credit (though avoidable)

The goal is to optimize for verifiability so the engine is compelled to credit you for the content it uses. If you’re not showing up early, you’re not showing up at all.

The likelihood of being cited decreases exponentially with lower position in the generated response. The Subjective Impression Score was evaluated using human annotators who consistently agreed on content relevance, clarity, and influence within AI responses.

What Content Structures Actually Work?

With generative AI engines like Google Gemini, ChatGPT, Perplexity, and others quickly rising to become the primary interface of user access to information, you need to think carefully about the way in which your content is structured.

The focus has changed entirely from using classic SEO tactics like keyword optimization to a new focus: citation-worthy. In the GEO world, you have succeeded when your content is easily parsed, cited, and used by generative engines to facilitate authoritative answers. 

Why is structure considered the priority?

Generative engines do not actually search and retrieve links. They synthesize the responses from multiple trusted sources to create a single unified response, which is often conversational. 

This means your content must be optimized to be cited and included in the AI-generated answers provided, not just shown in searches. It is critical that your content is laid out in a way that allows these systems to parse information and derive relevant insight.

Old SEO tricks like keyword stuffing are no longer just useless, they are damaging. A recent study shows that content with a lot of keywords is penalized, resulting in as much as a 6% reduction of visibility. Properly structured, data-backed, and well-referenced content has dramatically better visibility.

In contrast, structured, data-backed, and clearly referenced content enjoys significantly better visibility.

For example, content that includes citations shows a 132.4% increase in citation likelihood, while statistics increase visibility by 65.5%

Best Practices for GEO-Friendly Content

To be effectively cited by generative AI systems, your content must be built around structure, clarity, and precision. We recommend the following tactics:

• Bullet points and numbered lists: Make it easier for AI to find the information.
• Data tables: Provide facts and comparisons in a format that engines like to pull data from.
• Simple headings and subheadings: Help identify topical clusters.
• Schema markup: Be sure you use structured data types such as FAQ, HowTo, and Article, to show intent. This alone can increase citation rates by up to 12.8%.
• Multimedia: Charts and other visuals or infographics aid clarity and engagement.
• Conversational tone: Answer questions as if talking to your audience, in a way that is accessible. By mimicking natural language queries, you create frictionless opportunities for AI to surface and reuse your content.
• Reliable sources and citations: Referencing industry reports, government data, or academic research will improve credibility and visibility.
• Keep it simple: Research shows a 24.6% increase in citation frequency when content uses straightforward, declarative language.
• Skip the jargon: Avoid overly technical, jargon-heavy writing unless necessary, and always define any niche acronyms or terms.
• Be direct: Generalized or filler-heavy content can reduce citation potential by 2.1%. Use specific examples, precise figures, and authoritative terminology.
• Names matter: Enhance semantic richness by referencing named, high-authority entities and increase your chances of being cited by 6.8%. For example, instead of writing “more companies are using AI,” you could say, “According to a 2024 Gartner report, over 50% of Fortune 500 companies plan to invest in AI-powered marketing tools by 2028.”

Write for Multi-Turn Conversations

Generative engines are often based on multi-turn conversations, in which one answer leads to a following answer, and so on. In this multi-turn interaction, visibility early in the dialogue is very important. The first piece of content cited in a generative answer is often what keeps the generative engine going.

If your content is cited early, it can create a cadence of follow-up answers, creating brand impressions and perceived authority. For winning at this multi-turn game, here are some winning techniques:

Use headers that fit the way people ask questions.

Provide open-ended content that takes the reader deeper (i.e., frameworks, how-tos).

Provide the context and right background for your content.

Maintain precision in your data and wording to support reuse and synthesis.

Provide loosely navigable content by using internal links, consistent structure, and anchors for quicker retrieval.

Monitor, test, and optimize

Since AI engines are always changing, testing and monitoring are essential. Regularly run tests of how your content appears in different generative engines by running sample queries. 

Review performance measurement metrics that relate to citation frequency, position or placement in the answer, and domain authority, and measure results before and after implementation of GEO strategies. 

Creating a feedback loop, to continue to check if it is working and to adjust/tweak, and evolve your content, will allow for preservation of visibility over time.

By structuring your content for clarity, precision, and relevance, you position yourself at the top of the generative conversation, literally and figuratively.

To put it simply, write for structure, not search.

In GEO, clarity beats cleverness. If AI can’t quote you, it won’t show you.

Ranking in Perplexity vs. Gemini vs. ChatGPT

Why Small Brands Have an Advantage in GEO

GEO is a weapon for small brands in the battle for visibility.

It doesn’t reward keywords, domain authority, or ad spend. It values credibility, structure, and clarity. 

That’s a great opportunity for startups, smaller firms, and niche companies trying to punch above their weight.

Here’s why…

Generative engines don’t care how big you are. They value how clearly and contextually you answer a user’s question. And this is the big leveller. The good news is that smaller brands have an edge here. They’re more agile. 

They can go deep on niche topics, and they can build hyper-targeted, subject-matter-specific content that’s more citeable than broad, generic content posted by larger enterprises. 

According to the research study, lower ranked websites gained more visibility when using GEO tactics, such as citing sources more specifically.

Small brands will reap the largest advantages from GEO’s leveling effect. However, even dominant domains like Wikipedia can capitalise on this citation-boosting strategy, demonstrating that GEO is not a hack, but an upgrade to a structural system.

Here’s an example of how GEO can help a pizza shop in New York:

Instead of stuffing a page with “best pizza in New York,” the shop publishes:

• A breakdown of different pizza styles by borough
• A short FAQ on crust types, fermentation methods, and sourcing ingredients
• A story-driven piece on the history of their dough recipe
• A price comparison chart of artisanal vs. chain pizzerias in Manhattan
• Customer Q&A posts answering, “What’s the best slice at 2 am near Times Square?”

This kind of content helps you rank and also enables you to earn its way into the Generative AI search answers because it’s structured, specific, and deeply relevant.

Measuring Your Success with GEO

Typical SEO metrics, like backlinks or ranking on search engines, don’t help when your visibility depends on being cited or summarized by Generative AI.

So, what do you do to measure if all that effort you’re putting into your content is being rewarded by generative engines? 

Enter GEO-Bench, a benchmark dataset and framework to measure content visibility, relevancy, and authority in summaries of AI generated content.

GEO-Bench has 10,000 curated simulated real-world queries built to resemble user engagement with generative engines. Researchers from Stanford, Google DeepMind, and Hugging Face built this detailed dataset with queries that span multiple domains and categorize the user’s query by intent. For example:

• Exploratory: “How does X work?”
• Comparative: “X vs Y”
• Fact driven: “What is X?”

GEO-Bench has hyperlinked each query to five top Google search results, allowing for side-by-side comparison of your visibility in traditional search and generative engine inclusion datasets.

Generative engines like content that is obvious, semantically relevant, authoritative, and easily quotable. GEO-Bench now provides you with a framework to benchmark and optimize for the implications of these rules.

Key advantages

• Standardized testing across real-world user intents
• Cross-domain analysis
• Citation rate tracking
• Intention aligned optimization relative to different types of queries 

Understanding how GEO-Bench functions

Step 1 – Get Your Dataset

Access GEO-Bench on Hugging Face

Step 2 – Familiarize Yourself with The Structure

Each query has:

• Tags for Intent and Domain
• Matching sources from Google
• Quantitative measures on citations to measure citation behavior

Step 3 – Benchmark the Performance of Generative Engines

Run queries through different engines to record the inclusion, citation type (direct, footnote, summary), and frequency.

Step 4 – Record AI Citation Metrics

You can use:

• Google Analytics (GA4) for traffic tracking
• Brand24 or Mention to catch brand mentions of AI
• Custom scripts/ services that track AI generated responses

Step 5 – Conduct A/B Content Tests

This includes a test and iterate strategy:

• Test different headline formats
• Improve semantic depth (fact, stat, citation)
• Include clarifying visuals, source data, or quotes

Step 6 – Watch Your Competition

Keep a tab on who else is being included in the same queries why.

Key GEO metrics

Inside the GEO-Bench Dataset

Features include:

• 10,000 AI-adapted prompts simulating real user behavior
• Over 50 tags tracking query type, difficulty, and structure
• Benchmarking before/after optimization

As AI search becomes the default experience for users, the definition of visibility shifts. GEO-Bench enables data-driven experimentation, competitor analysis, and long-term strategy building that helps you get included in the answers that matter.

Conclusion: Preparing for the Future

Already, 79% of users are expected to switch to AI-based search on generative engines by 2026. CMOs who move fast will safeguard their brand’s visibility and gain first-mover advantages in a rapidly changing search landscape. 

This definitive shift points to a growing dependence on AI to give accurate, personalized, and relevant information. 

Brands must incorporate GEO into their marketing strategy to capture and retain user attention. Make GEO a part of your digital strategy for better control over your brand narrative and to build lasting connections with your customers. 

Generative engines are no longer emerging; they are here, transforming how we find, cite, and trust information. 

If you are a CXO or marketing leader, now is the time to take action. Go and look at your top 10 pages. If they are not citation-friendly for AI-based search, rewrite them or let us do it for you. 

GEO is an existential priority in an increasingly AI-first search world.