How Does SEO Work in the World of AI?

Why We Put Our GEO Engine to the Test on SEO

At IQRush.ai, our only goal is helping brands get more visible and monetize it. We started We live and breathe the science of getting brands surfaced in LLM-powered, AI-first discovery. But one question lingered: what if we pointed our math—built for next-gen GEO—at old-school SEO? Just a fast experiment. The answer: instant clarity and some real surprises.

Key Research Findings

• 62% ranking prediction accuracy - First mathematically validated SEO model

• Body content beats titles - 0.16 correlation vs high body content signals

• Hybrid similarity is #1 factor - Semantic + lexical matching drives rankings

• First 200 words critical - Early intent satisfaction matters most

Research Methodology

• Sample Size: Thousands of Google search results across diverse queries

• Features Analyzed: Thousands of measurable content features

• Approach: HTML scraping + feature engineering + machine learning model

• Result: 62% accuracy in predicting Google rankings (top 100 results)

Our Experiment: Predicting SEO Rankings with GEO Math

We took our answer prediction engine we use to predict GEO visibility, and turned it on thousands of Google search results across wildly diverse queries. We didn’t cherry-pick. We scraped the HTML, engineered thousands of measurable features, normalized results, and trained a robust model to track what really moved the needle.

Think of it as our own quick A/B test for legacy SEO but powered by GEO math.

What We Discovered: Real SEO Ranking Factors (and Myths Debunked)

The Model Actually Worked (and Why That’s Big)

In SEO, where advice is mostly expert guesswork, we proved what matters with actual math.

Our model explained 62% of what moves Google rankings; a level of clarity unheard of in an industry that usually just guesses. We predicted a page’s ranking across the top 100 results, separating real levers from background noise.

We didn’t just find one signal, we found several that turn a lot of expert professed, best practices upside down. A few callouts:

Body Copy Signals, Not Title Tweaks: Pages ranked for relevance and coverage, not because they nailed keywords in the title. Body content features like hybrid similarity (does it mean and sound like the query?), early placement of the best match (first 100–200 words), and comprehensive coverage beat out even domain authority.

Titles Are Overrated: Title keyword match? Just a 0.16 correlation with rank—almost meaningless compared to body signals. Cosmetic tricks don’t get the job done anymore.

Relevance is King: “Hybrid similarity”—our combined semantic + lexical match—was the #1 factor by far. If search engines see a page that both covers all topic needs and echoes the user’s natural phrasing, it wins.

What This Means for GEO, SEO, and Your Brand Strategy

This isn’t just an SEO lesson, it’s validation that AI and math that some are rumoring to take for GEO, also works for SEO. Our GEO methodology works because it measures what matters. no more guessing, just proof. The same factors that drive AI search (meaning, coverage, early intent satisfaction) are now dominating classic web rankings too. Marketers: stop wasting spend on legacy expert tricks. Invest in content relevance, intent coverage, and early, natural alignment.

A Simple Framework for Modern Marketers

Optimize for Hybrid Similarity: Make sure your body copy matches both the searcher’s meaning and their phrasing. We suggest two steps to validate – use math and then a human to assess. In fact, use math to inform how you build content in the first place.

• Frontload the Value: Put the best-aligned copy right at the top. Satisfy intent in the first 200 words or its diminishes.

• Expand Coverage: Cover all natural sub-intents users may have around the primary query. Use AI to “query fan” to identify sub-intents to inform copy development and placement.

• Don’t Overinvest in Titles: Use titles for engagement but win rankings with what’s in the body.

Final Thoughts: From SEO Guesswork to Generative Proof

What started as our quick “let’s try our GEO math on blue links” project was fun and it turned into new empirical proof of what matters. In the age of AI-driven visibility, you don’t need to rely on myth or outdated lists; with a AI-first approach, you can measure the “why” behind what gets brands found.

Next up: We’ll show you additional tactics that matter and how to design fast, low risk experiments to prove these insights and translate them into continuous search visibility. If GEO is the future, the best math wins today—whatever engine or algo is in charge.

Q&A

What is hybrid similarity in SEO?

Hybrid similarity is a metric that blends semantic and lexical similarity between a search query and page content—helping predict ranking in both classic SEO and generative AI search.

Does title tag optimization still matter?

Not as much. In IQRush’s analysis, title keyword match had only a 0.16 correlation with ranking—meaning body content relevance plays a much larger role in modern SEO and GEO.