SEO Vs LLMO: The Shift from SEO to LLMO

Search engine optimisation (SEO) is not dead, but it’s no longer the only game in the digital marketing landscape. With the rise of AI-powered platforms like ChatGPT, Perplexity, and voice assistants, visibility now spans more than just blue links on Google. If you want your content, brand, or product to stand out, you need to understand how to optimise across multiple types of engines—search, answer, and generative.

According to Built In, AI-driven search traffic is expected to surpass traditional SEO traffic by 2028. That means optimising for Large Language Models (LLMs) is no longer optional—it’s strategic.

According to SEMrush, websites using structured data are 30% more likely to appear in rich results. A 2023 BrightEdge report found that 68% of all online experiences begin with a search engine, reinforcing the importance of evolving traditional SEO.

Core Optimisation Types

AEO – Answer Engine Optimisation

What it is: Structuring content to directly answer user queries in search engine features like rich snippets.

Tactics:

• Use structured data (schema markup)

• Create FAQ-style content

• Match content to conversational queries

➕ With nearly 65% of searches ending in zero clicks (Similarweb, 2024), users are getting answers directly from the results page.

Source: https://www.similarweb.com/blog/marketing/seo/zero-click-searches/

GEO – Generative Engine Optimisation

What it is: Making content findable and quotable by generative engines like Perplexity, You.com, and Bing Copilot.

Tactics:

• Write authoritative, well-cited content

• Include semantically rich language

• Prioritise backlinks and domain authority

Grow & Convert found that 

77% of content mentioned in generative results ranks in the top 10 on search engines.

HubSpot (2024) reports 58% of marketers now create content with generative engines in mind.

LLMO – Large Language Model Optimisation

What it is: Optimising content to influence outputs from tools like ChatGPT, Claude, and Gemini.

Tactics:

• Publish expert-level content on trusted platforms

• Be mentioned in reliable sources

• Maintain consistent brand positioning

Gartner projects that by 2026, 30% of search traffic will come from AI-powered assistants—6x more than in 2023.

LLMs cite sources that are consistently mentioned across reputable domains and use structured formats (listicles, how-tos, FAQs).

McKinsey reports that companies using LLMs in content workflows saw 30–45% gains in content discovery and automation efficiency.

SXM – Search Experience Management

What it is: Managing how users experience your brand throughout the search journey.

Tactics:

• Map and personalise the user journey

• Improve content via analytics

• Align CRO and UX with SEO

Forrester says improving search UX can boost conversions by up to 20%.

Final Thoughts

Optimisation today requires a more expansive approach:

• Prioritise usefulness and clarity in your content

• Ensure discoverability across both traditional search engines and AI-powered platforms

• Structure your content to serve both human users and machine interpretation

In this new era, visibility is no longer confined to Google rankings. It's about positioning your brand where conversations, queries, and intelligent systems converge.

Frequently Asked Questions

1. What is the difference between SEO and LLMO?

Search Engine Optimisation (SEO) enhances visibility in traditional search engine results, primarily through keywords and backlinks. Large Language Model Optimisation (LLMO) focuses on influencing AI-generated responses by ensuring content is authoritative, structured, and frequently cited across reputable sources.

2. Why is LLMO becoming increasingly important?

With AI-powered platforms like ChatGPT and Perplexity gaining traction, user behavior is shifting away from traditional search. Industry projections show LLM-driven traffic will surpass SEO by 2028, making LLMO a strategic priority for digital visibility.

3. What are AEO, GEO, and LLMO, and how do they differ?

AEO (Answer Engine Optimisation) targets featured answers in search engines. GEO (Generative Engine Optimisation) ensures content is surfaced in AI-generated summaries. LLMO (Large Language Model Optimisation) focuses on shaping how LLMs interpret and cite your content.

4. How can content be optimised for LLMs?

To improve visibility in AI outputs, publish expert-level content, ensure it’s referenced by credible sources, and use structured formats such as listicles, FAQs, and how-to guides. Consistency in brand tone and semantic clarity also supports LLM discoverability.

5. Is traditional SEO still relevant in the current landscape?

Yes, SEO remains foundational to digital strategy. However, with the rise of AI-driven search tools, SEO must now be integrated with AEO, GEO, and LLMO practices for broader reach and sustained visibility.

6. How should brands prepare for this shift in search behaviour?

Brands should optimise content for both human users and machine interpretation. This includes using structured data, strengthening content authority, and ensuring discoverability across traditional search engines and AI-powered platforms.