For two decades, SEO was the dominant game. Rank on page one of Google, and the traffic followed. That game hasn't ended — but a parallel, arguably more significant game has now begun.
When someone asks ChatGPT, Perplexity, or Gemini "What's the best tool for X?", they receive a direct answer. Not a list of ten blue links. One or two recommended options, stated with confidence. If your brand isn't one of them, you don't exist in that conversation.
Why LLMs Are the New Front Page
Traditional search engines are index-based: they crawl, rank, and surface pages. Large Language Models operate differently — they synthesize information from their training corpus and, increasingly, from real-time retrieval. Brands that appear prominently in high-authority, well-structured content get cited more. Brands that don't, simply don't.
This creates a fundamentally different optimization problem. You're no longer competing for a keyword position. You're competing to be woven into the model's understanding of a category.
What AEO Actually Means
Answer Engine Optimization (AEO) is the practice of shaping how AI systems perceive, describe, and recommend your brand. It involves three interlocking disciplines:
- Citation building: ensuring your brand appears in the authoritative sources LLMs draw from
- Sentiment monitoring: tracking whether models describe you positively, neutrally, or not at all
- Visibility benchmarking: comparing how often your brand surfaces versus competitors when relevant queries are posed
The Measurement Problem
The hardest part of AEO isn't strategy — it's measurement. You can't run a search query and see your ranking. You have to systematically probe AI models with realistic user prompts and analyse the responses at scale. This is non-trivial and, until recently, was something only large teams could attempt manually.
“Being invisible to AI is being invisible to your next customer. The question is no longer whether LLMs matter to discovery — it's whether your brand is ready.”
— Akash Srivastava, Founder of Alovalabs
What To Do About It
Start by auditing your current AI visibility. Pose realistic buyer-intent queries to ChatGPT, Perplexity, and Claude and see where your brand lands. Document what language the models use about you — and your competitors. Then build a content and PR strategy that feeds the sources these models trust: well-structured documentation, credible third-party coverage, and clear entity signals.
This is the core problem Citivise was built to solve: automated, systematic AI visibility tracking and AEO strategy guidance, so you always know where you stand in the model's mind.