How you get mentioned and recommended in AI search

LLMs summarise answers directly, so if your brand isn’t cited, you’re invisible. 

Here is my guide of how to get quoted, recommended, or summarised by LLMs like ChatGPT, Perplexity, Gemini, and Claude.

Understand How LLMs "Learn"

LLMs usually pull information from high-quality, trusted, structured, and well-linked data sources.

To get large language models (LLMs) like ChatGPT, Claude, Perplexity, or Google Gemini to recommend your product or services, you need to understand how these models retrieve and rank information. They typically don’t index or remember everything on the web, but they pull from high-quality, trusted, structured, and well-linked data sources.

Here’s a breakdown of how to make your business more “recommendable” by LLMs:

Most LLMs have two modes of “knowing”:

1. Pretraining (static knowledge): Based on snapshots of public web content up to a certain date.

Getting your content into pretraining data used by large language models (LLMs) like GPT-4, Claude, or Gemini is difficult, but not impossible. While you can’t directly submit content for pretraining, you can increase the likelihood that your content is included in future training datasets by making it:

• Publicly available

• High-quality and link-worthy

• Located on domains commonly crawled for training (e.g. GitHub, Wikipedia, etc.)

2. Retrieval-Augmented Generation (RAG): Live access to search results, databases, or documents to answer questions. Examples: Perplexity, ChatGPT with web browsing.

So your goal is to:

• Be present in trusted, well-indexed public sources

• Show up in retrievals when users ask questions related to your category

Step 1: Appear in Trusted Data Sources LLMs Use

LLMs weigh content that comes from:

• Wikipedia (massively over-indexed and trusted)

• News outlets (The Guardian, ABC, TechCrunch, etc.)

• Directories and review platforms (e.g. Product Hunt, G2, Capterra, Crunchbase, GitHub)

• Schema-annotated websites (so Google and Bing can parse it semantically)

• Social proof (Reddit, Quora, Stack Overflow, LinkedIn, etc.)

  
  

✅ Actions:

• Publish your product/service to Product Hunt, G2, Capterra

• Create or contribute to a Wikipedia article (hard, but powerful)

• Add your business to Google Business, Crunchbase, and LinkedIn Company Pages

• Ensure your site has structured metadata (schema.org) for all services

• Get reviews and mentions in respected media or niche blogs (PR)

Step 2: Match User Intents with Clear Content

LLMs map user questions to solutions.

You need to help them associate "problem X" → "your solution" through:

• FAQs and explainer content ("How to automate client onboarding" → your SaaS)

• SEO pages matching queries like “best X for Y” or “alternatives to Z”

• Comparisons and ranking content. Be present in lists & comparisons in third-party publications

• Optimise for questions and conversational queries

• Use-case driven landing pages or blog posts that show how your product solves real problems

• Case studies and testimonials with keywords

• Encourage customers to review & recommend you in forums. LLMs pick up these UGC mentions heavily

✅ Actions:

• Create “intent-aligned” content: “Best [category] for [audience/problem]”

• Include clear product descriptions, target markets, and pricing

• Create comparison pages: “Why [Your Product] vs [Popular Competitor]”

• Include schema markup (FAQPage, Product, Review)

  
  

Step 3: Feed Your Content to LLMs (Directly and Indirectly)

Right now, some tools allow for direct submission of your business info, including:

Platform	Submission/ Indexing Option
Google Search	Submit sitemap / structured data
Perplexity Pages	Add a page via their contributor program
ChatGPT	Submit your business at OpenAI to be included in chatGPT’s product recommendations as part of search experience.
Anthropic Claude	Not open yet for crawling but uses Common Crawl

✅ Actions:

• Ensure your content is public, crawlable, and linked

• Add your site to Google Search Console and submit a sitemap

• Submit product pages to Perplexity's contributor portal (if available)

• Submit your business for product recommendations in OpenAI

Step 4: Be crawlable

As mentioned before, LLMs like Perplexity, Claude, and ChatGPT (with browsing) use retrieval-augmented generation (RAG) to pull live web content, not just their internal training data.

They access: Your public product pages, structured FAQ or comparison posts and high-ranking Google-indexed pages.

But here’s something some businesses forget:

If your site blocks ChatGPT’s crawler (OAI-SearchBot), it won’t appear in ChatGPT’s search results.

Just like search engines, ChatGPT uses a web crawler called OAI-SearchBot to find and surface public content. If your site blocks it via robots.txt, your content will be invisible to ChatGPT users.

✅ Actions:

• Ensure OAI-SearchBot (ChatGPT) and other AI crawlers are allowed in your robots.txt file

• Use this rule:User-agent: OAI-SearchBot

Allow: /

• You can track traffic from ChatGPT using UTM tags:ChatGPT adds utm_source=chatgpt.com to links, so you can monitor it in Google Analytics

Checklist: Add GEO/AI Optimisation to Your Marketing

✅ Activity

• Check if your site allows OAI-SearchBot (robots.txt)

• Submit your business at OpenAI to be included in chatGPT’s product recommendations as part of search experience

• Write LLM-friendly content that matches intend (FAQs, comparisons, summaries)

• Get your brand/business mentioned on Reddit, Quora, and blog lists

• Track ChatGPT traffic via utm_source=chatgpt.com

• Consider building a GPT (e.g., “Find My Perfect Bikini” for swimwear e-commerce brands) or Perplexity Page

• Add structured data/schema to your product + FAQ pages

• Google your category questions and check if ChatGPT/Perplexity recommends you