Answer Engine Optimisation has become one of those disciplines where everyone has an opinion but very few people have a repeatable process. Most "AEO guides" rehash the same surface-level advice — add FAQ schema, write conversational content, structure your headings — without ever walking you through what to actually do, in what order, and how to measure whether it's working.

This post is different. It's a practical implementation guide, structured as a seven-step process you can work through systematically. Whether you're starting from zero or trying to improve an existing AI visibility position, this is the operational playbook.

What AEO Actually Requires

Before diving into steps, one clarification: AEO isn't a one-time optimisation task. It's an ongoing discipline, much like technical SEO. The goal is to make your brand, content, and entity signals so unambiguous to AI systems that when a user asks a relevant question, your brand is the natural citation.

The good news is that most of the signals AI tools favour — structured content, factual accuracy, topical depth, entity consistency — are the same signals that indicate genuinely high-quality content. AEO done properly doesn't involve tricks. It involves building the kind of content infrastructure that AI tools are trained to trust.

Step 1: Audit Your Current AI Visibility

You can't improve what you haven't measured. The first step is understanding where you currently stand.

Run a Manual AI Visibility Check

Open ChatGPT, Perplexity, Claude, and Gemini. Ask each one a series of queries relevant to your business:

"What is the best [product category] for [use case]?"
"Which [tool type] do [your target audience] use?"
"What are the top [your category] platforms?"
"Who are the leading providers of [your service]?"

Note which platforms mention your brand, how prominently, and in what context. Are you appearing as a first mention, a third mention, or not at all? Are the descriptions of your product accurate? Is your positioning aligned with how you'd describe yourself?

Use Surfaceable for Systematic Tracking

Manual checks give you a snapshot, but they don't scale. Surfaceable runs these queries automatically across platforms, tracking your presence rate, position within responses, and how citations change over time. Starting with a baseline score gives you a reference point for everything that follows.

Document Your Baseline

Record: which platforms mention you, on which query types, in what position, and with what context. This becomes your benchmark. Everything you do in steps 2–7 should move these numbers.

Step 2: Identify Your Target Queries

AI tools respond to prompts, not keyword searches. The query patterns your customers use with AI tools are different from how they'd phrase a Google search.

Think in "Best X for Y" Formats

The most citation-valuable queries follow patterns like:

"What is the best [product category] for [specific use case]?"
"Which [tool] should a [job title/company type] use?"
"How do I [solve problem] using [product type]?"
"What tools do [industry professionals] recommend for [task]?"

Interview Your Sales and Support Teams

Ask them what questions prospects are asking AI tools before they reach your sales process. This is increasingly common — buyers now use ChatGPT or Perplexity as a first-stage research tool before they visit your website. Your sales team will have heard the output of those AI queries in discovery calls.

Build a Target Prompt List

Create a list of 30–50 specific prompts you want to appear in. These become your measurement set and your content brief. Every subsequent step maps back to this list.

Step 3: Map Queries to Existing or New Content

Once you have your target prompt list, audit your existing content against it.

Content Mapping Process

For each target prompt, ask:

Does any existing page directly answer this query?
If yes — is the answer structured clearly enough for an AI to extract and cite?
If no — does this query warrant a new piece of content?

Be honest about gaps. A blog post that tangentially touches on a topic is not the same as a page that directly and comprehensively answers the underlying question. AI citation requires the latter.

Prioritise by Business Value

Not all queries are equally valuable. Prioritise queries that map to commercial intent — the questions your customers ask when they're evaluating solutions, not just learning about a topic. A citation in "what's the best project management tool for remote teams?" is worth far more than a citation in a general question about productivity.

Step 4: Restructure Content for Direct Answers

This is where most of the practical work happens. The way AI tools extract information from web pages favours a specific kind of content structure.

The Direct Answer Principle

Every piece of content targeting a specific query should answer that query directly, near the top of the page, in plain language. Don't make AI systems hunt through several paragraphs of preamble to find the answer. Lead with it.

A good structure for AEO-optimised content:

Opening paragraph — a direct, concise answer to the primary question (2–4 sentences)
Supporting sections — H2-structured content that expands on the answer with specifics
FAQ section — a set of Q&A pairs covering related questions, each with a direct one-paragraph answer
Evidence and context — statistics, examples, case studies that support the answers

Formatting Signals AI Tools Respond To

Numbered lists for processes and steps
Bullet points for feature comparisons and options
Bold terms for key concepts within paragraphs
Short paragraphs — three to four sentences maximum
Explicit question headings in H2 or H3 format ("What does [X] mean?", "How does [Y] work?")

The goal is not to make content that reads robotically. It's to make content where the answer to any given question is unambiguous and easily extractable.

Step 5: Add FAQPage Schema to Answer-Structured Content

Schema markup doesn't directly cause AI citations, but it does several things that support them: it signals to crawlers how to interpret your content, it increases the likelihood of rich results in traditional search (which indirectly builds authority), and it provides explicit structure that AI tools with web browsing capability can leverage.

How to Implement FAQPage Schema

For any page with a FAQ section, add JSON-LD FAQPage schema. A minimal implementation looks like this:

{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "What is AEO?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "AEO (Answer Engine Optimisation) is the practice of structuring content and brand signals to increase the likelihood of being cited by AI-powered answer engines such as ChatGPT, Perplexity, Claude, and Gemini."
      }
    }
  ]
}

Ensure each Q&A pair in the schema maps directly to visible content on the page. Schema that doesn't reflect actual page content is both ineffective and a potential violation of search engine guidelines.

Other Schema to Prioritise

Beyond FAQPage, implement:

Organisation schema — with a consistent name, URL, logo, description, and sameAs links to authoritative third-party profiles
WebSite schema — with a sitelinks searchbox if applicable
Product and Service schema — for your core offerings, including accurate descriptions

Step 6: Build Entity Authority

This is the strategic layer that separates brands with durable AI visibility from those that appear occasionally and inconsistently.

What Entity Authority Means

AI language models represent the world as a graph of entities — people, organisations, products, places, concepts — and the relationships between them. The more consistently and authoritatively your brand appears across the data sources these models were trained on, the more reliably you'll be recognised as a legitimate entity and cited appropriately.

Key Entity Signals to Build

Wikipedia and Wikidata presence. Wikipedia is disproportionately represented in AI training data. If your brand is notable enough to justify a Wikipedia article, having one (or contributing to existing articles that mention you accurately) significantly strengthens your entity recognition. A Wikidata entry with accurate information is even more directly machine-readable.

Consistent brand mentions on authoritative sites. Industry publications, partner directories, press coverage, and review platforms all contribute. The brand name, description, and key facts should be consistent across all of these.

Google Knowledge Panel. Claiming and verifying your Google Business Profile, and ensuring your Knowledge Panel (if one exists) accurately reflects your brand, strengthens your entity signals across the Google ecosystem — which matters particularly for Gemini.

Authoritative product descriptions. The way your product is described on third-party review sites (G2, Capterra, Product Hunt, etc.) feeds into AI training data and real-time web browsing. Ensure these descriptions are accurate, up to date, and consistent with how you'd describe yourself.

Step 7: Monitor and Iterate

AEO is not a project with an end date. It's a continuous cycle of measurement and improvement.

Metrics That Matter

Presence rate — the percentage of your target prompts in which your brand is mentioned. This is your headline number. Aim to increase it over time.

Position score — where in a response your brand appears. First mention carries more weight than fifth. Track average position across your prompt set.

Share of voice — how often you're cited relative to your competitors on the same prompts. If you're appearing in 40% of relevant prompts but your main competitor is in 70%, you have a clear gap to close.

Prompt coverage — how many of your 30–50 target prompts you're appearing in at all. Early on, you might only be present in 10. The goal is steady expansion.

The Iteration Loop

Each month, review your metrics and identify:

Which prompts have you improved on?
Which competitor is now appearing where you aren't?
Which content pieces drove the most improvement?
Where are you still absent that you shouldn't be?

Use these answers to prioritise the next round of content updates, entity-building activity, and schema improvements.

Surfaceable automates this monitoring layer — tracking your prompt presence across ChatGPT, Perplexity, Claude, and Gemini continuously, so you're not relying on manual spot checks to understand what's changing.

The Compounding Effect

One thing worth understanding about AEO: the results compound. Early work on entity authority and content structure tends to produce slow initial gains, followed by accelerating improvement as the signals reinforce each other. A brand with a strong Wikipedia presence, consistent entity mentions, well-structured content, and accurate schema builds a profile that AI tools find unambiguous and easy to cite.

The brands that will dominate AI search in three years are the ones doing this systematic work now. The process above is not complicated. It's just a matter of working through it deliberately, measuring the results, and iterating.

Start with the audit. Everything else follows from knowing where you are.

How to Do AEO: A Practical Answer Engine Optimisation Strategy