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Michal Rogowski
Michal Rogowski

Posted on • Originally published at beyondsenior.engineering

Optimize your website to get more AI citations

#webdev #ai #seo #rag

Why should you care about AI Chatbots?

By 2026 25%[1] of users will migrate their regular Search experience to AI chatbots and agents. This creates new risks and opportunities for all companies, people and websites producing publicly available content to increase their organic growth.

In order for our business to stay relevant and be discovered by new audiences we have to understand how AI chatbots generate their responses.

How AI Chatbots generate their responses

The response from the AI Chatbot is created based on three different stages:

  1. LLM model Training: The foundational knowledge of the model.
  2. Scanning: AI bot’s crawling the internet for up-to-date information.
  3. Retrieval: Selecting the most relevant chunks from its database to answer the user query.

How to Optimize your website to get more AI citations?

Focus on Generative Engine Optimization (GEO). You do this by creating a website and content that demonstrates high E-E-A-T (Experience, Expertise, Authoritativeness, and Trust) [13] scores, which AI crawlers use to evaluate and select content to be cited in their responses.

Key principles for achieving this include:

  • Demonstrating E-E-A-T: Prove your credibility through first-hand experience, author expertise, brand authority, and building trust with verifiable claims and citations.
  • Clear Page and Content Structure: Use clear HTML tags, relevant metadata, and a logical content flow with headings and an "answers-first" approach.
  • Content Freshness: Ensure your content and metadata are up to date, as this has a significant impact on citation rates.

By following these rules, you increase the citation impact by AI chatbots, which boosts your organic traffic.

Deep Dive: How AI Chatbots Generate Responses

1. LLM model Training

The first way your data may become part of a chatbot answer is by being included in its training data. From a company perspective, there are no direct benefits if content is scraped for training, as the output doesn't contain citations, links, or author information. This has led to lawsuits over copyrighted data[3]. The training data allows LLMs to sound human and structure answers, but it's prone to hallucinations[6] and has a hard cut-off date. Companies with high-quality data are now making deals with AI firms, like Reddit with OpenAI[7] or Wikimedia Enterprise and Google[8]. The lesson: if you have valuable human generated data, sell it, don't give it away for free.

2. Scanning - AI bot’s crawling the internet

This is the most important step for website creators. In 2020, Meta’s research team introduced Retrieval-Augmented Generation (RAG)[9, 10]. RAG allows AI chatbots to access up-to-date, hallucination-free information. Before retrieval, AI companies use crawlers[11] to scan the internet, identify relevant pages, and store them as data chunks for their RAG pipelines. During this scan, they evaluate a page's E-E-A-T and its semantic meaning[12] for deep contextual understanding. To appear in AI chatbot citations, we must focus on Generative Engine Optimization (GEO).

3. Retrieval

Once your website has been scanned, chunked, associated with a high E-E-A-T score and stored in the vector DB, it can be retrieved to answer a user's query. The content is slightly changed when presented, but your page is credited and listed as a source. This is how we can grow organic traffic.

A flowchart of the RAG process. It shows a user prompt going to a retrieval system, which pulls data from a vector database. The prompt and data are then fed into an LLM to produce a final, context-aware answer.

How to Create GEO-optimized sites with high E-E-A-T scores

Defining the brand’s Experience, Expertise, Authoritativeness and Trust.

1. Experience[13]

The focus here is on demonstrating first-hand experience with the topic. For example: "while working with our clients, we noticed the exact pattern how our GEO strategy increases their traffic from AI Chatbots by 30%." The engine can detect that you have real-world experience on the topic at hand.

2. Expertise

The next parameter influencing Page Quality (PQ)[14] rating is expertise. This is about how qualified you are to express opinions. The page should include information about the author. For example, my professional profile[15] is linked, which connects to my LinkedIn, showing my expertise as a Senior Engineering Manager is relevant to topics like LLMs and AI.

3. Authoritativeness

This refers to the reputation of the brand or website. As Google's guidelines[16] state, the authority on getting French citizenship is the French government's website, giving it high authoritativeness on that specific process.

To illustrate the overlap:

  • Experience: Written by someone who has applied for citizenship, sharing their personal journey.
  • Expertise: Written by an immigration lawyer who specializes in the process.
  • Authoritativeness: The official government page that sets the rules for citizenship.

4. Trust

This is the most important parameter of E-E-A-T. If your brand is perceived as a scam, you can't make up for it with expertise or experience. Trust is built on what others write about you and whether you are referenced as a source of truth.

5. Can you use Generative AI?

According to Google's guidelines[16], if you use Generative AI to create high-value content that upholds all four aspects of E-E-A-T, it's acceptable. If you use it to generate low-quality content, your score will decrease.

Core Generative Engine Optimisation Principles

Authority & Trust

The core objective for AI Chatbots is to minimize hallucinations. You can increase your authority and trust by making claims verifiable and providing evidence from respectable sources. Research from Berkeley[17] introduces a 16-pillar auditing framework that converts page features into a normalized GEO score.

Page Structure

Ensure a clear code structure for machines. Use relevant HTML tags like <h1>, <h2>, internal OG tags, and JSON-LD. Following HTML accessibility guidelines[18] is a good start. An example of well-structured <head> content may look like this:

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</head>
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Content Structure

The more structured the content, with clear headers, sub-headers, questions, and answers, the easier it is for the RAG process to assign correct semantic meaning. Lead with an "answers-first" summary[17]. Use an active voice, as crawlers prefer trustworthy certainty over opinion[19]. Finally, ensure the content is fresh. Metadata and freshness have the biggest citation impact, at +47%[17].

To make this more actionable, you can inspect the code of this page and analyze its structure. You can see that this entire essay was optimized to increase E-E-A-T and GEO scores. I hope that helps!

Thanks,

Michal.

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