Schema Markup for AI Search: What It Does and How to Add It, Step by Step

What schema markup does for AI search, what it doesn't, and how to add it step by step: check crawlability, choose types, write JSON-LD, validate and track results.

When we walk clients through their AI visibility reports, schema markup often gets a shrug. It sounds like an old SEO chore, the kind of thing you set up once in a plugin and forget.

Sometimes that’s fair. In some industries, schema barely seems to matter. In others, nearly every page AI engines cite has it, and the brands without it are missing a basic layer.

The trouble is that most advice online sits at one of two extremes. Some guides promise schema is a shortcut to AI citations. Others say it does nothing at all. Neither helps you decide what to do on Monday morning.

This guide takes the middle path, with our own data. By the end, you’ll know:

• what schema markup is, in plain English
• what it can and can’t do for AI search
• how to check that AI crawlers can read your site first
• how to choose, write, validate and deploy schema, step by step
• how to tell whether it’s working

What is schema markup?

Schema markup is a small block of code on a web page that describes the page’s content in a standard, machine-readable format. It tells search engines and AI systems what things are: this is an organization, this is its logo, this is the author, this is a product, this is its price. Instead of leaving machines to guess, you label the facts.

The vocabulary comes from Schema.org, a shared standard backed by Google, Microsoft, Yahoo and Yandex. The most common format is JSON-LD, a short script that sits in the page’s code and doesn’t change what visitors see.

Here’s a tiny example. It tells machines that a company called SEOPulse exists, where its website is, and what it does:

{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "SEOPulse",
  "url": "https://www.seopulse.io",
  "description": "SEOPulse is an AI visibility and intelligence platform. It tracks how AI engines mention, cite and recommend brands in ChatGPT, Gemini, Perplexity, Google AI Overviews and Google AI Mode, across markets and languages."
}

You can think of schema as a labeled spreadsheet about your page. Each item has properties, and those properties can have their own properties. A product has an offer. The offer has a price. The price has a currency.

Schema, entities and the knowledge graph

To see why schema matters for AI, you need two more terms.

• Entity: a distinct, identifiable thing. A company, a person, a product, a place or a concept.
• Knowledge graph: the connected map of entities that search engines and AI systems use to understand how things relate. This author wrote this article. This company makes this product. This product is in this category.

Imagine 100 companies called “Apex.” When an AI engine reads about “Apex,” it has to work out which one you mean. Schema helps it decide. By stating your name, website, location and official profiles in one place, you make it easier for machines to connect your pages, your mentions and your reviews to the right business.

That’s the real job of schema in AI search. Schema doesn’t make AI pick you. It helps AI know it’s you.

Does schema markup help you get cited in AI search?

Schema markup helps AI systems understand your pages and your brand, but there’s no evidence it earns citations on its own. Google states that structured data isn’t required for its generative AI features. Our own data shows most cited pages do carry schema, which makes it a baseline worth having, not a shortcut.

Here’s what we know, and what we don’t.

What Google says

Google’s guide to optimizing for generative AI features, last updated July 2026, is direct:

• Structured data isn’t required for generative AI search, and there’s no special schema to add for it.
• Google still recommends structured data, because it helps pages qualify for rich results in regular search.
• You don’t need AI text files like llms.txt to appear in Google Search. Google Search ignores them.

In short, optimizing for Google’s AI features is still SEO.

What our data shows

In SEOPulse’s GEO & AI Search Benchmark (data collected August 2026), we analyzed 30,106 web pages cited by five AI engines: ChatGPT, Gemini, Perplexity, Google AI Overviews and Google AI Mode.

• 72.32% of cited pages carried JSON-LD schema.
• 77.2% carried some form of structured markup (JSON-LD, tables or charts).
• Only 21.7% were plain text pages with no structured elements.

So most of the pages AI engines choose to cite have schema.

But be careful how you read that. It doesn’t prove schema caused those citations. Cited pages also tend to come from larger, well-maintained sites that do many things well, schema included. Our dataset also grouped schema with other structured formats like tables and charts, so we can’t isolate the effect of schema alone.

The fair conclusion: schema is table stakes. Most of the pages you’re competing against already have it. Not having it won’t necessarily sink you, but it’s one fewer signal working in your favor.

Schema matters more in some industries

We also see big differences by industry. In some categories, the pages AI engines cite almost always carry structured data. In others, schema barely shows up as a pattern. That’s why we treat schema as industry-dependent, not a universal rule.

Some patterns from our benchmark:

Patterns observed in SEOPulse’s August 2026 benchmark sample. They describe what was cited, not what caused the citation.

How do you fix crawlability before adding schema?

Make sure AI crawlers are allowed to visit your site and can read your content without running JavaScript. Schema can’t help a page that AI systems can’t access. Check your robots.txt rules, your firewall, your page rendering and your indexing before you write a single line of markup. See the technical checks in the SEOPulse audit for ongoing monitoring.

This is the step most schema guides skip. It’s also where we see the biggest early wins.

The crawlability checklist

Why rendering matters so much

Google can render JavaScript. Many AI crawlers can’t. They read the HTML your server sends when the page first loads, and if your content is tucked inside JavaScript, they may only see a blank page.

That has two consequences:

1. 1
   If your page content loads with JavaScript, AI crawlers may see a blank page.
2. 2
   If your schema is added with JavaScript, for example through Google Tag Manager, AI crawlers may never see it.

A quick test: open your page, choose “View page source” (not “Inspect”), and search for a sentence from your main content and for application/ld+json. If you can’t find them in the source, AI crawlers probably can’t either.

Example: from 0% to 1% visibility with a technical fix alone

Tenfold AI is a legal technology brand targeting Taiwan in English and Traditional Chinese. When tracking started in SEOPulse, its AI visibility was 0%.

Read about Tenfold AI’s technical accessibility fixes; this example concerns rendering and crawlability, rather than a measured effect of schema alone.

SEOPulse’s technical audit found rendering issues that kept AI crawlers from reading the site’s content. Once the team fixed how pages were delivered, visibility moved to 1%. Targeted content work on 10 pages then lifted it to 7%, and average AI engine rank moved from #50 to #28.

The technical fix didn’t win the citations by itself. But nothing else could work until it was in place. (This fix was about rendering, not schema. It’s here because crawlability always comes first.)

How to add schema markup for AI search: step by step

Here’s the full process at a glance:

1. 1
   Build your entity kit
2. 2
   Choose schema types for each page template
3. 3
   Write connected JSON-LD
4. 4
   Match every value to visible content
5. 5
   Validate the code, then validate the live page
6. 6
   Deploy it in the page HTML
7. 7
   Log changes and keep schema up to date

Let’s go through each one.

Step 1: How do you prepare your brand facts for schema?

Before writing any code, collect one approved version of your core brand facts: your official name, a one-line description, your logo, contact details, and a list of every official profile. Schema only helps if it’s accurate and consistent with what the rest of the web says about you.

AI systems compare what you say about yourself with what other sites say. If your website, LinkedIn page and directory listings describe you in four different ways, schema can’t fix the confusion. It just adds a fifth version.

Create a simple entity kit:

Then check each profile against the kit. Look for:

• Hard conflicts: different headquarters, an outdated business category, old product names
• Drift: small differences like “nearly 10 years” vs “10+ years”

Fix the hard conflicts first. Those are the ones most likely to confuse an AI system about who you are.

The sameAs property is your “this is also us” list. It links your schema to your official profiles elsewhere, so machines can be confident that your LinkedIn page, your Crunchbase entry and your website all describe the same business.

Step 2: Which schema types should you use?

Choose schema types based on what each page actually is, not on a list of every type available. Most sites need a small set: Organization and WebSite site-wide, then Article for content, Product or Service for offers, and Person for authors.

Work by page template, not page by page. Your blog posts share one template, your product pages another.

Only use a type if the page really is that thing. A blog post isn’t a Product. A service page doesn’t need Recipe markup. Wrong types add noise rather than clarity.

Step 3: How do you write connected JSON-LD?

Write one JSON-LD block per page that links its entities together using @id identifiers. Your Organization, WebSite, WebPage, Article and author should reference each other, so machines see one connected picture rather than five separate facts.

The key is the @id. It’s a stable identifier, usually your URL plus a label like #organization. Define your organization once, then point to it from every page using the same @id.

Here’s a connected example for a blog post on the SEOPulse site:

{
  "@context": "https://schema.org",
  "@graph": [
    {
      "@type": "Organization",
      "@id": "https://www.seopulse.io/#organization",
      "name": "SEOPulse",
      "alternateName": "SEO Pulse",
      "url": "https://www.seopulse.io",
      "logo": "https://www.seopulse.io/[FILL: logo-file].png",
      "description": "SEOPulse is an AI visibility and intelligence platform. It tracks how AI engines mention, cite and recommend brands in ChatGPT, Gemini, Perplexity, Google AI Overviews and Google AI Mode, across markets and languages.",
      "sameAs": [
        "https://www.linkedin.com/company/[FILL]",
        "https://www.crunchbase.com/organization/[FILL]"
      ]
    },
    {
      "@type": "WebSite",
      "@id": "https://www.seopulse.io/#website",
      "url": "https://www.seopulse.io",
      "name": "SEOPulse",
      "publisher": { "@id": "https://www.seopulse.io/#organization" },
      "inLanguage": "en"
    },
    {
      "@type": "Person",
      "@id": "https://www.seopulse.io/#[FILL: author-slug]",
      "name": "[FILL: author name]",
      "jobTitle": "[FILL: job title]",
      "worksFor": { "@id": "https://www.seopulse.io/#organization" },
      "sameAs": [
        "https://www.linkedin.com/in/[FILL]"
      ]
    },
    {
      "@type": "BlogPosting",
      "@id": "https://www.seopulse.io/blog/schema-markup-for-ai-search/#article",
      "headline": "Schema Markup for AI Search: What It Does and How to Add It, Step by Step",
      "description": "What schema markup does for AI search, what it doesn't, and how to add it step by step.",
      "datePublished": "[FILL: YYYY-MM-DD]",
      "dateModified": "[FILL: YYYY-MM-DD]",
      "inLanguage": "en",
      "author": { "@id": "https://www.seopulse.io/#[FILL: author-slug]" },
      "publisher": { "@id": "https://www.seopulse.io/#organization" },
      "isPartOf": { "@id": "https://www.seopulse.io/#website" },
      "mainEntityOfPage": "https://www.seopulse.io/blog/schema-markup-for-ai-search/"
    }
  ]
}

What each part does:

• @graph holds several entities in one block.
• @id gives each entity a stable identifier that other entities can point to.
• publisher, author, worksFor and isPartOf connect the entities: this article belongs to this website, was written by this person, who works for this company.
• sameAs links the organization and author to their official profiles.
• dateModified gives a clear freshness signal. Keep it accurate.

Using AI to generate schema

You don’t have to write JSON-LD by hand. Claude, ChatGPT and Gemini can all draft it from a page’s content. The output is usually close to ready, but you still need to check it. Expect blanks where the AI couldn’t find something, most often a logo or image URL.

Copy this prompt and paste your page content (or URL, if your AI tool can browse) underneath:

You are a technical SEO specialist. Generate JSON-LD schema markup for the page below.

Rules:
1. Choose schema types based on what the page actually is. Explain your choices first.
2. Use a single @graph. Connect entities with @id values based on the site URL
   (e.g. https://example.com/#organization).
3. Only include facts that appear on the page or in the brand details I provide.
   Never invent ratings, reviews, prices, dates or awards.
4. FAQ questions and answers must match the visible page text word for word.
5. Where a value is missing, write [FILL: description] instead of guessing.
6. Use straight double quotes only, and return valid JSON.
7. After the code, list every [FILL] field and anything I should double-check.

Brand details:
- Official name:
- Website:
- Logo URL:
- One-line description:
- Official profiles (sameAs):
- Author name, title and profile links:

Page content or URL:
[PASTE HERE]

Step 4: Why must schema match the visible page?

Every value in your schema should match what a visitor can see on the page. If your schema says a service costs $3,000 and the page says $3,500, you’ve created a conflict. When structured data says one thing and the visible text says another, AI systems have less reason to trust either.

Follow three rules:

1. 1
   Mark up only what’s on the page. If it isn’t visible, leave it out of the schema.
2. 2
   Copy FAQ text exactly. Questions and answers in FAQPage markup should match the visible FAQ word for word.
3. 3
   Edit the page first, then the schema. Never change schema to say something the page doesn’t.

Never add fake reviews or ratings. Only mark up genuine reviews that are visible on the page.

Step 5: How do you validate schema markup?

Validate twice: once on the code before you publish, and again on the live URL after you publish. The first check catches errors in the code. The second confirms the schema actually made it onto the page.

Use two different tools, because they check different things:

How to fix errors:

• Missing fields: usually a blank logo or image URL. Add the full, absolute URL.
• Broken syntax: often caused by curly “smart” quotes or a missing comma. Replace curly quotes with straight ones.
• Stuck? Screenshot the error message and paste it back into the AI tool that generated the code. Ask it to fix only that error.

A clean result means your schema is valid. It doesn’t mean AI engines will use it. That’s what Step 7 is for.

Step 6: Where should you add schema on your site?

Add schema in the page’s HTML, ideally in the <head>, so it’s there when the page first loads. This is the safest option for AI crawlers, because they read the raw HTML and don’t run JavaScript.

Watch for duplicates. If your CMS plugin already adds Organization schema and you add your own, you may end up with two conflicting versions. Check the page source and keep one.

After you deploy, run the live URL through the Schema Markup Validator again. If the schema shows up there and in “View page source,” you’re done.

Step 7: How do you maintain schema over time?

Keep a simple change log and re-validate whenever facts, templates or products change. Schema goes stale quietly. A price change, a rebrand or a new CMS theme can break it without anyone noticing.

Log every change with the date, the pages affected and what changed:

This log matters later. When your AI visibility changes, you’ll want to know what else changed at the same time.

Set reminders to re-validate:

• after any theme, template or CMS update
• when prices, products, team members or contact details change
• at least once a quarter for your most important pages

Should you still use FAQ and HowTo schema?

Yes, if the page has a real FAQ or step-by-step section, but don’t expect special treatment in search results. Google no longer shows FAQ rich results. The markup is still valid Schema.org vocabulary and still describes your content clearly.

What changed is the display, not the value of the content itself:

• Keep visible FAQs. People read them, and they’re often written in the same question-and-answer shape AI engines use to build answers.
• FAQPage markup is cheap to add when the FAQ already exists. Just keep it word-for-word with the page.
• Don’t add FAQs only for the markup. A list of thin questions written to fill a schema block helps no one.

There’s no reliable evidence that FAQ or HowTo markup multiplies AI citations. Add it because it accurately describes the page.

How should you use schema for multilingual and Asian markets?

Use one consistent entity across every language version of your site, and tell machines which language each page is in. If your brand has an English name and a Chinese, Japanese or Thai name, list both. This helps AI systems connect mentions in different languages to the same business.

This matters a lot in Asia, where buyers often search in more than one language, and AI answers can change depending on the language of the question.

What to add:

• alternateName for local-language brand names, such as a Traditional Chinese or Japanese name
• inLanguage on every WebPage and Article, using codes like en, zh-Hant-TW, ja or th
• The same @id for your organization on every language version, so it’s one entity, not several
• sameAs links to regional profiles, such as local business directories or market-specific social accounts
• hreflang tags connecting each page to its translations (these sit in the HTML, outside your schema)

A short example for a brand that publishes in English and Traditional Chinese:

{
  "@context": "https://schema.org",
  "@type": "Organization",
  "@id": "https://www.example.com/#organization",
  "name": "Example Legal Tech",
  "alternateName": ["範例法律科技", "Example LT"],
  "url": "https://www.example.com",
  "areaServed": "TW",
  "sameAs": [
    "https://www.linkedin.com/company/example-legal-tech"
  ]
}

SEOPulse tracks AI answers by market and language, so you can see whether your brand is visible in English for Singapore, Traditional Chinese for Taiwan, or both. Treat each language as its own track when you measure. Include those markets in your GEO campaign plan.

What are the most common schema mistakes?

These are the issues that most often stop schema from doing its job.

Where does schema fit in your content workflow?

Add schema as a line in every content brief, so it’s planned with the page rather than patched on after. The writer handles the visible facts and FAQs. The developer or SEO lead handles the markup and validation.

When we review AI visibility reports with clients, the brief is where it all comes together. As one client put it while reading their report: “it serves as the guideline, and we write the content from there.” Schema belongs in that guideline. Use the tutorial to turn the findings into an AEO action plan.

Add these fields to your content brief:

Schema is one part of making a page easy for AI to use. The page also needs answer-first sections, clear headings, specific data and passages that make sense on their own. Schema reinforces good content. It can’t replace it. Learn how to optimize content for AI search alongside the markup.

How do you know if schema markup is working?

Track a fixed set of questions in AI engines before and after you add schema, but don’t credit schema alone for any change. AI visibility moves for many reasons: new content, new links, competitor changes and engine updates. Your change log helps you separate them. Before making changes, run an AI visibility audit.

Here’s a practical way to measure it:

1. 1
   Choose your questions. Pick the questions where you want to appear. Our guide to building a prompt tracking workflow explains how.
2. 2
   Record a baseline before you deploy schema: brand mentions, cited URLs and competing sources, by engine and market.
3. 3
   Deploy and log your schema changes with dates.
4. 4
   Compare after a few weeks. Look at the same questions, engines and markets.
5. 5
   Read the answers, not just the scores. Are AI engines now describing your brand correctly? Are they citing the right pages?

One sign schema and entity work are helping: AI answers start describing your brand more accurately, with the right category, location and products, even before your citation numbers move.

Can smaller sites win these questions?

Yes, but not every time. For the exact question “How to fix website crawlability and schema markup for AI search engines?”, SEOPulse recorded 156 citations in October 2026. 23.7% of them went to pages with a Domain Authority under 25 and fewer than five backlinks. Large, established sites took most citations, but smaller sites with clear, well-structured answers still earned a real share.

Where SEOPulse fits

SEOPulse shows how your brand appears across ChatGPT, Gemini, Perplexity, Google AI Overviews and Google AI Mode, in the markets and languages you care about. For every question you track, you see the full AI answer, the exact URLs cited and which competitors appeared.

That makes schema decisions easier:

• Technical audit. SEOPulse’s weekly technical audit (Pro and Agency plans) checks your own pages for blocked AI crawlers, missing schema and hard-to-extract structure.
• White-label content. If your team doesn’t have time to rebuild pages, SEOPulse’s content team can write them for you: answer-first structure, FAQ schema and internal links, localised into Asian languages, and delivered unbranded for agencies.
• Gap analysis. See which pages AI engines cite instead of yours, then check how those pages are built and what structured data they use.
• Before-and-after tracking. Track the same questions by engine, market and language, so you can see what changed after a technical or content update.

Frequently asked questions

Check what AI engines see

See where you stand first. Run SEOPulse’s free brand scan at app.seopulse.io/brand-scan to see your visibility across five AI engines and which competitors show up instead. It’s a one-off snapshot, not ongoing tracking.

Want to know what’s blocking you? Book an SEOPulse demo. We’ll show you the full AI answers, the pages being cited, and the technical and content gaps in the markets that matter to you.

Next, build your tracking set. Read our guide to building a prompt tracking workflow, or compare AI visibility tools.

Sources

• SEOPulse, GEO & AI Search Benchmark: 755 buyer prompts, 6,811 AI answers and 30,106 cited web pages across ChatGPT, Perplexity, Gemini, Google AI Overviews and Google AI Mode. Data collected 16 August 2026.
• SEOPulse, Citation Analysis, October 2026: query-level citation records, including domain authority and backlink data.
• SEOPulse, Tenfold AI case study (client-reported).
• SEOPulse conversations with clients and partners, 2026.
• Google Search Central: Optimizing for generative AI features in Google Search (last updated July 2026)
• OpenAI: Publishers and Developers FAQ
• Google Search Central: Documentation updates (FAQ rich results)
• Schema.org: Schema Markup Validator

How to Optimize Content for AI Search: What We Know After Analyzing 9,779 Citations

Learn how to optimize content for AI search in 8 steps. We analyzed 9,779 AI citations: 34% went to small sites. Here's what gets cited and how to win.

Your client has already seen it for themselves. They asked ChatGPT about their category, and a competitor came up. They didn’t.

Now they want three answers from you:

• What are you going to change?
• Why will that work?
• How will we know it was worth the money?

Most guides on how to optimize content for AI search give you the same checklist. Lead with the answer. Add schema. Use tables. Keep it fresh. It’s all reasonable advice. But a checklist doesn’t tell you which page to fix first, and it won’t convince a client to fund the work.

Every step in this guide is tied to evidence: what SEOPulse shows you in the dashboard, and what SEOPulse’s own research found in 9,779 AI citations from five AI engines. So when a client asks “why this page?” or “why a table?”, you’ll have an answer you can show them.

The workflow at a glance

What does optimizing content for AI search mean?

Optimizing content for AI search means making your pages easy for AI engines like ChatGPT, Gemini, Perplexity and Google’s AI features to find, understand and quote when they answer a question. It builds on SEO rather than replacing it. AI engines still search the web for sources. The difference is what happens next.

When an AI engine answers a question, it usually runs several searches, pulls in pages, and breaks those pages into smaller passages. It then picks the passages that best answer each part of the question and writes a response, often with links to its sources.

That has two big implications for your content:

1. 1
   Each section needs to stand on its own. The AI engine may only use one passage from your page, so that passage has to make sense without the rest.
2. 2
   Ranking on Google isn’t the whole picture. A page can rank well and still never be cited, if the answer is buried or vague.

AI engines rarely agree with each other. In SEOPulse’s August 2026 benchmark of 6,811 AI answers, the engines picked the same top vendor in just 1.5% of prompts where more than one engine named one. Being visible in ChatGPT tells you very little about Perplexity or Google AI Overviews. So track and optimize for each engine your client’s buyers actually use.

In Asia, that matters even more. ChatGPT isn’t officially available in Hong Kong, for example, so a Hong Kong client’s buyers may lean on Google AI Overviews, Gemini or Perplexity instead.

Step 1: Pick the prompts worth winning

Start with buyer prompts worth winning linked to services your client sells, then prioritize the ones where they have a realistic chance of being cited. Not every gap is worth chasing. The best first targets are prompts where the pages AI currently cites aren’t much stronger than your client’s.

In SEOPulse, the gap analysis view groups your prompts by category and highlights the high-opportunity ones: prompts where competitors appear and your client doesn’t.

Click into a prompt and you’ll see the Domain Authority and page backlinks of the pages being cited. SEOPulse calls this checking your permission to win.

Here’s an example from a demo report for a Singapore bank:

• “Which bank is best for a savings account?” The cited pages are long-established and well linked. It’s winnable over time, but not a quick win.
• “What is the best digital bank in Singapore?” The top cited page had a Domain Authority of 33 and four backlinks. An established bank with a DA of 50+ has a real shot here.

Start with the second kind.

Smaller sites get cited more than you’d think

In SEOPulse’s October 2026 analysis of 9,779 AI citations across 50 buyer and search queries, 34.2% went to pages with a Domain Authority under 25 and fewer than five page backlinks. Every one of the 50 queries had at least some citations from pages like this.

The share varied by engine:

Source: SEOPulse citation analysis, October 2026. Low-DA, low-backlink = DA under 25 and fewer than five page backlinks.

This doesn’t mean authority is irrelevant, or that any new page will get cited. It means a smaller brand with a relevant, well-built page can compete on the right prompts. That’s an important message for small and mid-sized clients.

If you need help choosing which prompts to track in the first place, see our guide to building a prompt tracking workflow.

What to show your client: a short list of prompts, grouped by the services they sell, with a note on which ones are realistic wins now and which are longer-term goals.

Run a free SEOPulse brand scan to check your client’s visibility before choosing which content to optimize.

Step 2: Inspect the pages AI already cites

Before you write anything, look at the specific pages AI engines cite for your target prompt: their structure, length, headings, media and schema. Look at pages, not just domains. Knowing that a competitor’s site gets cited is less useful than knowing which page, and why.

For each prompt in the gap analysis view (part of a Deep Dive, US$2 per prompt on any plan), SEOPulse shows you: Explore the AI visibility features behind these views.

• Top cited domains and URLs. You can copy these straight into a brief as reference pages.
• Keyword frequency across the cited pages.
• Rich media usage: the average use of tables, charts, images and video on cited pages.
• Schema markup usage: how common structured data is among the cited pages in that industry.

Then open the Queries view to read the actual AI answers for that prompt, by engine and market. This shows you how the AI engine structured its answer, which brands it named and which page each point came from. Answers change from one run to the next, so look at several.

The content benchmark puts your client’s page next to every cited page, comparing structure, word count, headings, metadata and Domain Authority.

What cited pages tend to look like

From SEOPulse’s October 2026 citation research:

• Blog posts and articles made up 51.2% of citations. Help center and documentation pages were 4.8%. Product and pricing pages were just 2.2%.
• 33.1% of cited pages contained data tables.
• 40.9% used bulleted lists to structure their answers.
• Pages with tables tended to be longer (about 3,250 words on average vs 2,150 without) and scored higher on relevance to the prompt.

Each engine has its own habits:

Source: SEOPulse citation analysis, October 2026. Engine patterns are from a sample of marketing and AI search queries. Check your own category before choosing targets.

These are patterns among cited pages, not proof that adding a table will get you cited. But they tell you what “good” looks like for your prompt, which is exactly what your writer needs.

What to show your client: a side-by-side of their current page and the pages AI cites instead. One agency partner put it well: “This is what you have now, this is what you could have.”

Step 3: Decide whether to refresh, create, add an FAQ or go off-site

If your client already has a page that serves the same reader and task, refresh it. If they don’t, create a new page. If the question is small, answer it in an FAQ. And if AI keeps citing a third-party site, the opportunity is off your client’s website.

This is the question agencies ask us most: do we refresh the content or create a new page?

The Optimization view in SEOPulse helps you answer it. It shows which of your client’s pages are already being cited, and for which prompts. If a page is getting cited for related prompts, it’s usually the best place to add the missing answer.

The Citations view helps with the off-site column. It surfaces sites that keep getting cited in your category, including smaller “hidden gems” you may never have heard of. If a niche comparison site keeps turning up in AI answers for your client’s market, that’s a lead for PR, partnership or paid placement.

One caution: a backlink, a brand mention and an AI citation are three different outcomes. Getting featured on a cited site doesn’t guarantee your client will be cited too. Track them separately.

What to show your client: a prioritized action list. Which pages to update, which to create, and which sites to approach, each linked to the prompts it targets.

Step 4: Turn the gap into a content brief

A good AI search brief tells the writer which question to answer, which pages to learn from, which sections to include, which formats to use and what proof to add. Most of it comes straight from the gap analysis. Follow our answer engine optimization workflow to turn the gap into a content brief.

What goes into the brief

Include snippets of the current AI answers. They show the writer how the answer is shaped, so the new page can be structured to be quoted easily.

How to structure H2s and H3s

Order your H2s by the decisions a buyer makes, not by keyword volume. A typical order is: understand the problem, compare the options, choose, then implement and measure.

A few rules that work well:

• Use question-style headings where they read naturally. “How much does managed IT support cost in Hong Kong?” is clearer than “Pricing”.
• One heading, one idea. If a section answers two questions, split it.
• Merge near-duplicates. “How much does it cost” and “What’s the price” belong in one section.
• Move small leftover questions into an FAQ at the end.
• Make each heading specific. “Our approach” tells an AI engine nothing. “How we migrate email to Microsoft 365 without downtime” does.

Example brief (excerpt)

1. 1
   What does managed IT support include for Hong Kong SMEs?
2. 2
   How much does managed IT support cost in Hong Kong?
3. 3
   How do you choose a managed IT provider? (comparison table)
4. 4
   How does onboarding work? (step-by-step)
5. 5
   Results from Hong Kong clients (case data)
6. 6
   FAQs

Proof needed: response time data, client count, one case study with numbers

Illustrative example written for this guide.

What to show your client: the brief itself. Every section has a reason behind it, so they can see exactly what they’re paying for and why.

View SEOPulse pricing and plans to choose the tracking and Deep Dive options for your client’s buyer questions.

Step 5: Write answer-first sections that stand on their own

Start each section with a direct answer to its heading in one or two sentences, then add the reasoning, evidence and examples. If an AI engine only uses the first lines of a section, it should still get a complete, accurate answer.

Three habits make the biggest difference:

1. Answer first. Put the answer right under the heading. Don’t warm up with background.

2. Name the subject. Replace “we”, “it” and “our solution” with the actual brand or product name, at least at the start of each section. A passage pulled out of context needs to say who it’s about.

3. Add proof to every section. A specific number, date, client result or named source makes a passage more useful, and more quotable, than a general claim. Research backs this up: the Princeton-led GEO study (Aggarwal et al., KDD 2024) found that adding statistics, quotations and cited sources can raise a page’s visibility in AI-generated answers by up to 40%.

Before and after

Before:

After:

Fictional example.

The second version answers who, what, for whom and with what evidence. Lifted out of the page, it still makes sense.

Connect the topic to the business

Every page should connect the topic to what your client actually offers. An article that explains a problem but never mentions the client’s service may help readers, but it won’t help AI engines connect your client’s brand with that problem. Take the reader from the problem, to the type of solution, to your client’s specific offer and proof.

This doesn’t mean stuffing in sales copy. One clear, factual paragraph is usually enough. And if the client’s team can’t write the page, SEOPulse’s white-label content service can turn your brief into a finished, AI-ready page, delivered under your agency’s brand.

Step 6: Add proof AI can lift: tables, original data and visuals

Use a table whenever you’re comparing options against the same criteria, add original data the client owns, and always pair charts and images with text. These are the formats AI engines can extract most easily.

When to use comparison tables

Use a table when the reader is comparing: plans, prices, features, providers, pros and cons. Keep column headers clear, use real HTML tables (not images of tables), and add a sentence above the table explaining what it shows.

In SEOPulse’s October 2026 analysis of 9,779 AI citations, Perplexity (38.4%) and ChatGPT (37.6%) were the engines most likely to cite pages containing tables.

What original data to add

Original data is the hardest thing for a competitor to copy, and the easiest for an AI engine to quote. Good sources inside a client’s business:

• pricing benchmarks or average project costs
• customer survey results
• response times, delivery times or success rates
• anonymized trends from their own sales or support data

Always state where the number came from, when it was collected and what it covers.

How to make charts, images and video citable

In SEOPulse’s citation data, charts on their own didn’t make a page more relevant to the prompt. AI engines read the text around them. So:

• Pair every chart with a short summary or an HTML table of the same data.
• Add descriptive captions and alt text to images.
• Add timestamps and chapters to YouTube videos. In SEOPulse’s research, 47% of video citations linked to a specific timestamp, and nearly all came from Google’s AI features.

What a B2B service page needs

For small B2B companies, the service page is often the page that should get cited. Make sure it covers: If you need help with content strategy and page production, see our AEO Services.

Vague service pages are one of the most common gaps SEOPulse sees in client audits. If an AI engine can’t tell exactly what a business does, who for and where, it has little reason to recommend it.

Step 7: Check internal links, crawlability and schema

Make sure AI crawlers can access the page, the important text is visible without JavaScript, relevant pages link to it, and any schema matches what’s on the page. None of these will get a page cited on their own. But any one of them can stop a good page from being found. Google’s guide to AI features in Search confirms the same technical basics apply: to appear as a supporting link in AI Overviews or AI Mode, a page must be indexed and eligible to show in Google Search with a snippet.

In SEOPulse, the weekly technical audit (Pro and Agency plans) flags blocked crawlers, missing schema and hard-to-extract structure on a client’s own pages, so you can see if technical issues need fixing before content work starts.

Your quick checklist:

• AI crawlers aren’t blocked. Check robots.txt and firewall rules for bots like GPTBot, OAI-SearchBot, PerplexityBot and Google’s crawlers.
• Key content loads without JavaScript. If your answers only appear after scripts run, some crawlers may see an empty page.
• Relevant pages link to the new or updated page with descriptive anchor text, such as “managed IT pricing for Hong Kong SMEs” rather than “click here”. Internal links help crawlers find the page and understand what it’s about.
• The page is indexed in Google. AI features that search the web still need to find it.
• Schema matches the visible content. FAQPage schema should repeat the on-page questions and answers word for word. Validate before and after publishing.
• There’s a visible publish or update date.

For the full walkthrough on structured data, see our guide to schema markup for AI search.

Step 8: Measure the change and report it to your client

Re-run the same prompts, on the same engines and in the same markets, then compare against your baseline. Report visibility, citations and share of voice by category, and connect them to business results the client already tracks.

First, baseline your AI visibility so you have a documented starting point.

Which AI search metrics to report

Report mentions and citations separately. In SEOPulse’s August 2026 benchmark of 6,811 AI answers, 53.4% mentioned a tracked brand, 34.2% cited that brand’s website, and only 10.0% did both. Being named and being linked are two different wins.

Report by category too. A single overall score can hide the fact that a client is strong on one service and missing from another.

Tie it back to the business

AI visibility isn’t revenue on its own, and clients know it. To make the case, put your AI search results next to the numbers they already care about:

• Leads and enquiries for the services you optimized
• Branded search trends in Google Search Console
• Google Search Console’s AI reports showing which pages appear in AI Overviews and AI Mode, where available
• “How did you hear about us?” responses. Add ChatGPT, Perplexity and other AI tools as answer options on the client’s enquiry form.

Then keep a simple change log: which page changed, what changed, when, and which prompts it targeted. It makes it much easier to explain why results moved.

Example: from 0% to 7% visibility

Tenfold AI is a legal technology brand targeting Taiwan in English and Traditional Chinese. When tracking started in SEOPulse, its AI visibility was 0%, with an average AI engine rank of #50.

See Tenfold AI’s content optimisation results for the full example.

1. 1
   Technical fix. An audit found rendering issues that stopped AI crawlers from reading the site. Once fixed, visibility moved to 1%.
2. 2
   Targeted content. Gap analysis identified prompts Tenfold had permission to win. The team created or updated 10 pages across both languages.
3. 3
   Result. Visibility reached 7%, and the average AI engine rank moved from #50 to #28.

It’s one brand, not a promise. But it shows the workflow in action: fix access first, target realistic prompts, then measure the change.

What to show your client: before-and-after visibility by category, the pages now being cited, share of voice against named competitors, and the business metrics alongside them.

How long does it take to see results?

There’s no fixed timeline, so set the client’s expectations around a re-measure window rather than a date. Once the page is crawlable and indexed, re-run the same target prompts about two weeks and again four weeks after publishing, on the same engines and in the same markets. AI answers change from one run to the next, so look for a trend across several runs before you report a win or a loss.

For a broader sequence of work and review milestones, use the 90-day GEO plan.

Common mistakes when optimizing content for AI search

Most failed AI search projects trip on the same five mistakes. Avoid these and your content work is far easier to defend to a client:

• Building a page for every prompt variant. Wording variants belong on one page, and separate pages end up competing with each other.
• Chasing high-authority prompts first. Start with prompts where the cited pages aren’t much stronger than your client’s.
• Adding schema that doesn’t match the page. Markup should only describe what readers can see on the page.
• Judging results from a single run. AI answers vary, so compare trends across several runs.
• Reporting one blended visibility score. Category results show clients where they’re strong and where they’re missing.

Frequently asked questions

See where your brand stands first

Before you optimize anything, find out where your client is visible today, and where they’re missing.

Run a free brand scan at app.seopulse.io/brand-scan. You’ll see how your brand shows up across five AI engines and which competitors appear instead. It’s free, with one scan per email address.

Ready to go deeper? Compare SEOPulse pricing and plans for your client’s prompts and markets.

Related reading: How to build a prompt tracking workflow · Schema markup for AI search · Best AI visibility tools

Sources

• SEOPulse, Citation Analysis, October 2026: 9,779 citations across 50 buyer and search queries, with engine-level, page-type and media analysis.
• SEOPulse, GEO & AI Search Benchmark: 755 buyer prompts and 6,811 AI answers across ChatGPT, Perplexity, Gemini, Google AI Overviews and Google AI Mode. Data collected 16 August 2026.
• SEOPulse, Tenfold AI case study (client-reported).
• SEOPulse conversations with agency partners and clients, 2026.
• Google Search Central: Optimizing for generative AI features in Google Search

Answer Engine Optimization Step by Step: From AI Visibility Report to Action

Follow this visual AEO tutorial to turn an AI visibility report into action: find content gaps, brief pages, pitch cited sites, and track results.

Whether you run an agency or your own business, you’ve probably asked it already, or had a client ask: “Are we showing up in ChatGPT?”

For most teams in Asia, the honest answer is “we’re not sure.” We hear it on almost every call. Brands are asking their agencies about AI search, and most agencies don’t have a solution yet.

You don’t need to be an SEO specialist to start. If you’ve ever planned a campaign, briefed content or checked how your brand looks on Google, you already have most of the skills.

Checking your AI visibility takes seven steps, from choosing buyer questions to rechecking results, and every one works without a dashboard. SEOPulse is an AI visibility and intelligence platform that tracks how ChatGPT, Perplexity, Gemini, Google AI Overviews and Google AI Mode answer your buyers’ questions. For each step, we show the matching SEOPulse screen and the work it saves. Explore the AI visibility platform features behind this workflow.

To keep it concrete, we’ll follow one real question all the way through, from the first check to the recheck.

What is the difference between AEO, GEO and SEO?

AEO and generative engine optimization (GEO) are overlapping terms for improving visibility in AI answers. SEO remains the foundation that makes your website discoverable in the first place.

You’ll see different definitions, but there’s no dependable boundary where GEO means ChatGPT and AEO means Google. Ahrefs describes AEO as covering Google AI Overviews as well as tools like ChatGPT and Claude. Most agencies use the terms interchangeably.

What matters more is the difference between three outcomes:

These rarely happen together. In August 2026, SEOPulse ran 755 buyer questions through five AI engines in Hong Kong and Singapore. Across 6,811 answers:

• 53.4% mentioned a tracked brand
• 34.2% included that brand’s website in their sources
• Only 10.0% did both
• Inside the answer text itself, 99.5% of brand mentions carried no link

So an AI answer can put your name in front of buyers without giving them a direct link to you.

Google AI Overviews and Google AI Mode also need separate checks. AI Overviews are summaries inside search results, while AI Mode is a more conversational search experience. Google says their answers and supporting links can differ.

Free scan or full report: what do you need?

You can follow every step in this guide without a dashboard. A tool earns its place when you’re checking more questions, markets and engines than a spreadsheet can handle. Start with a free AI search visibility audit to establish your first snapshot.

Compare AI citation tracking tools when choosing software for that ongoing workflow.

Run a free SEOPulse brand scan, then use this guide to turn the findings into your next action.

Here’s how SEOPulse’s two options compare, as of October 2026:

One thing to know: the free scan calculates its visibility score differently from the full report. It compares your brand’s mentions with the median of your competitors’. Don’t compare the two scores directly.

How the numbers are calculated

SEOPulse calculates visibility as the share of tracked answers that mention or cite your brand, and share of voice against your named competitors only. Before you trust any score, know what it counts, over which period, and against whom. This applies to every AI visibility tool, not just ours.

A quick example: if your brand appears for one question out of four in a category, that category shows 25%.

How close is this to what your buyers actually see? We collect answers by capturing live answers from each engine’s interface, as a user in the market you select, on the schedule you choose, rather than relying on API responses. That’s closer to real buyers than one person’s chat window. It can’t reproduce each buyer’s personal chat history, though, and answers vary from run to run. Read trends over several days, not one day’s result.

Step 1: Choose the buyer questions that matter

Start with one product or service, one market and one buyer need. Pick questions that would matter if your business showed up in the answer. Use our prompt tracking workflow to choose buyer questions you can compare over time.

How to choose buyer questions without a dashboard

A broad question like “What is accounting software?” introduces a topic. “Which accounting software works for a small agency with overseas clients?” is much closer to a purchase.

Collect questions from sales calls, customer emails, Search Console queries and Google’s “People also ask” boxes. Query fan-out (the sub-questions AI generates behind the scenes) is good for ideas, but it doesn’t prove anyone is searching for them.

Group your questions by what the buyer is trying to do:

For a first pass, choose five questions you can investigate properly. Write down the market, language and engines next to them.

How to choose buyer questions in SEOPulse

The overview puts your visibility trend, the competing brands and the category breakdown on one screen. You can see straight away which service is weakest, without building pivot tables first.

From our agency work: an influencer marketing agency we worked with was visible in 11% of answers across 22 Hong Kong questions. Filtered by category, they were strong on a broad “top agency” question and absent on the specific ones about nano, micro and lifestyle influencers. As they put it: “The overall average doesn’t mean much, but the category average is more meaningful.”

For a pitch, we recommend 25–30 questions on one product or service, split between early research and ready-to-buy questions. For ongoing tracking, our rule is simple: track what you can influence. And keep a core set of questions locked, so you always have a fair before-and-after comparison.

Step 2: Check what AI says, and which sources it uses

Read the answer before you interpret a score. Note whether your brand is named, whether your pages are cited, and whether the information is accurate.

How to check AI answers without a dashboard

Ask each question in ChatGPT and Perplexity using the exact same wording. Then search it on Google and note whether an AI Overview appears. If you test AI Mode, log it separately. Write down the date, so you know when each answer was collected.

Use a simple sheet:

Five questions in three places gives you 15 answers. That’s a snapshot, not the full picture. Engines also rarely agree: in SEOPulse’s August 2026 benchmark, they picked the same top vendor just 1.5% of the time (22 of 1,493 questions).

How to check AI answers in SEOPulse

Next to the answer, the panel shows whether your site was cited, how many times each brand was mentioned, and which competitors appeared. It brings together the answers and sources you’d otherwise need to log without a dashboard, automatically, for every engine, every day.

Opening the Google AI Overview answer showed something more useful. HSBC’s Revolution card was named six times, but the panel reads “Target brand cited? No.” The answer’s links went to comparison sites MoneySmart and SingSaver, plus Wise.

That’s a gap you’d never spot from a visibility score alone. HSBC scores well on this question, yet the comparison sites are the ones supplying the facts.

As you read any answer, ask three questions:

1. 1
   What information answers the buyer’s need?
2. 2
   Which source supplied it?
3. 3
   What’s missing or wrong?

A negative sentiment label is a reason to investigate, not a diagnosis. If the answer text doesn’t support the label, flag it to your tool provider rather than guessing at a cause.

Step 3: Check your pages can be found and read

Fix access problems before you commission more content. A better page can’t help if AI can’t reach it. Read our technical guide to schema markup for AI search and crawlability.

How to check your pages without a dashboard

For Google AI Overviews and AI Mode, Google’s requirements are clear: a page must be indexed and eligible to appear in Search with a snippet. Meeting them doesn’t guarantee inclusion.

Ask whoever manages the website to check that:

• Important pages load without a login
• Crawling isn’t blocked by robots.txt, hosting or security settings
• The pages are eligible for indexing
• Key answers exist as real text, not only inside images
• Internal links help people and crawlers find the pages
• Structured data matches what’s visible on the page

For other engines, check their published crawler guidance. Not every bot has the same purpose or permissions.

Do you need schema markup for AI search? Use structured data that fits the page type, but don’t treat it as a shortcut. Google says its AI features need no special schema or AI text file. FAQ markup won’t rescue a weak answer.

How to check your pages in SEOPulse

That gives you a page-by-page starting point: which pages AI already trusts, and which to inspect next.

From our agency work: an influencer marketing agency we worked with asked, “Do I understand correctly that only four of our URLs are cited?” They’d understood correctly. Across 22 questions, four pages were doing all the work.

A lesson from Tenfold AI

This legal tech company selling in Taiwan started at 0% AI visibility, because AI crawlers couldn’t read its content properly. Fixing access moved it to 1%. Ten targeted pages then took it to 7%, and its average position in AI answers moved from #50 to #28. The lesson is the order: check access first, then judge the content.

Read the Tenfold AI case study for the full sequence of technical and content changes.

Step 4: Find and diagnose the gaps

A missing mention is a finding, not a writing brief. First work out what kind of gap you have, and whether the fix belongs on an existing page, a new page or another website.

How to diagnose the gaps without a dashboard

Go back to your sheet and sort each question into one of these:

Don’t create a page for every wording variation. Group questions that serve the same buyer need.

How to diagnose the gaps in SEOPulse

Instead of reading dozens of answers to find your blind spots, you start from a grouped shortlist.

Where to click next: open one question to see what the pages AI cites have in common: the top keywords, how many images, videos, charts and tables they use, and how many use schema markup.

Use these signals to judge how realistic a question is to win, not as a pass or fail test. In the HSBC Singapore demo report, the cited pages for “What is the best digital bank in Singapore?” had just 4 backlinks and DA 33. For an established bank, that makes it a more accessible opportunity to test than a question dominated by heavily linked pages.

That fits a wider pattern. In SEOPulse’s October 2026 citation analysis of 9,779 citations, 34.2% went to pages with Domain Authority under 25 and fewer than five backlinks. It’s an observation from that sample, not a promise that a small site will be cited.

From our agency work: an influencer marketing agency we worked with asked, “Do we need to refresh the content to create a new one?” For them, it was both. Much of their Xiaohongshu content dated from 2018–19, which made it an easy refresh. And they had nothing on Xiaohongshu advertising, which needed a new page.

Step 5: Turn the gap into a brief worth writing

Build the brief around the buyer’s decision. Use the cited pages to see what information is needed, then add the evidence only your business can provide. Follow our content guide to optimize content for AI search.

How to build the brief without a dashboard

A good brief includes:

• The target question and its close variants
• The action: refresh or new page
• The reference pages to study (not copy)
• Snippets from the current AI answers
• The headings
• An evidence request

Paste in the answer snippets so your writer can see the structure AI likes to quote.

How to build the brief in SEOPulse

What used to take an afternoon of tab-switching becomes a ten-minute job. Your writer can then spend their time on what matters: the missing answer and the original evidence. No writers to spare? SEOPulse’s white-label content team can turn the brief into a finished, AI-ready page, delivered unbranded so agencies can hand it to clients as their own.

Worked example: the brief

An illustrative brief built from the demo report data. It isn’t an HSBC assignment or a reported result.

A useful answer starts with the answer, then gives the explanation and the evidence.

Weak: “We offer innovative solutions tailored to your needs.”

More useful: “[Card name] earns [verified rate] on online and contactless spend, with [fee terms]. It suits [buyer type] who spend mainly [category].”

A few habits help AI quote you:

• Answer first, then explain
• Make each section stand on its own
• Use tables and lists for comparisons. In SEOPulse’s August 2026 benchmark, pages with structured content were extracted about 3.8x more often than plain text
• Name the brand instead of “we” or “it”

Before publishing, have someone with subject expertise check the facts, limits and claims.

Step 6: Build presence beyond your website

Some opportunities are on other websites. Look at the pages AI already cites for your topic before you decide where to spend outreach time.

How to find outside sources without a dashboard

Go back to the “Other sources quoted” column in your sheet. The sites that keep coming up are the ones AI treats as credible for your category.

Check that your name, services, locations and product details match everywhere.

For ad agencies, this list is also a media plan

We think of it as a new way to pitch media: these are the sites AI trusts for your client’s category. One caution: a site being cited doesn’t mean its paid placements will be cited too. Treat sponsored content as a separate test, and measure it separately.

How to find outside sources in SEOPulse

That turns a pile of links into a ranked, labelled shortlist. You can drop the competitors and start with the third parties.

Where to click next: Content home → Benchmark distribution shows which sources appear most, from premium publishers to lesser-known “hidden gems” you might never have found yourself.

Which sites matter depends on the industry. In SEOPulse’s August 2026 benchmark, software answers leaned on YouTube, LinkedIn, Reddit and Zapier, while hotel answers leaned on Tripadvisor, Reddit and curated rankings. Build your list from your own citation data, not a generic list of big publishers.

From our agency work: a regional marketing publication kept appearing in the citations of an influencer marketing agency we worked with. Their reaction: “Maybe the opportunity is not on your own website. But it’s outside, right?” They’d worked with the publication before, so it became their first pitch.

How do I fix missing or incorrect brand citations in AI answers?

Identify the problem and the source behind it before choosing a fix.

You control what you publish and the corrections you request. No tool, ours included, can edit another platform’s AI answer.

Step 7: Recheck and connect results to the business

Rerun the same questions, in the same market and on the same engines, and keep visibility separate from traffic and enquiries. Put the updates into a 90-day GEO campaign plan so you can review them in sequence.

How to recheck results without a dashboard

Keep a change log: what changed (a page or an outside source), who did it, and the date it went live. Then rerun your locked question set and compare it with your baseline.

When to recheck

Answers change from day to day, so judge results over several checks, not one. In our proof-of-concept projects, the first gap map arrives in week four, the client updates its target pages within two months, and we review the lift from there. In the Tenfold case, results were measured two weeks after the pages went live.

What counts as progress: read the answers alongside the scores.

• Is your updated page now cited?
• Is the information about you more accurate?
• Are you included for the buyer need you targeted?

A change that holds across several checks matters more than a one-day spike.

For Google, AI feature traffic is included in Search Console’s Web reporting, so don’t present it as a separate AI Overview number. Use your analytics and enquiry records alongside visibility tracking.

If nothing changes, go back through the steps:

1. 1
   Was the page accessible?
2. 2
   Did it answer the actual buyer need?
3. 3
   Did it add something new?
4. 4
   Was the opportunity on another site all along?

If visibility rises but enquiries don’t, check three things:

• Are you being recommended, or only mentioned? A mention alone may not drive action.
• Are the questions close enough to a purchase? Visibility on early research questions often comes first. Shift some effort to ready-to-buy questions.
• What happens when people arrive? Check that the landing page answers the same question the AI answer did.

How to recheck results in SEOPulse

Your change log and analytics explain why. The dashboard shows what changed, engine by engine, without you having to rerun each question yourself.

SEOPulse demo. What to notice: visibility over time next to the dates your changes went live. On its own, the chart doesn’t prove that a particular edit caused the change.

We’ll admit the visibility score is a vanity metric on its own. But it’s usually the first sign the work is landing, and it moves before revenue does.

5 mistakes to avoid

1. 1
   Trusting the overall average. Filter by category and market first.
2. 2
   Reading the score without reading the answer. The answer is the evidence.
3. 3
   Reporting share of voice against the wrong competitors. Fix the list before you report.
4. 4
   Copying the winning page. Borrow the structure, then add what only you know.
5. 5
   Changing the question set mid-campaign. You lose your before-and-after.

Frequently asked questions

Start with one question and one useful change

Pick one buyer question that matters to your business. Read the answers and the sources, choose the right action, and publish something you’d stand behind. Then recheck, and do it again with the next question.

Ready to track changes over time? View SEOPulse pricing and plans for your buyer questions and reporting needs.

For a full campaign plan, read our companion guide, Generative Engine Optimization: A 90-Day Plan for Agencies.

Sources

• SEOPulse, GEO & AI Search Benchmark: 755 buyer prompts and 6,811 AI answers across ChatGPT, Perplexity, Gemini, Google AI Overviews and Google AI Mode; Hong Kong and Singapore; data collected 16 August 2026 (SEOPulse research)
• SEOPulse, Citation Analysis, October 2026: 9,779 citations across 50 buyer and search queries (SEOPulse research)
• SEOPulse demo report, HSBC Singapore (public data), 2026
• SEOPulse, Tenfold AI case study (client-reported)
• Google Search Central: AI features and your website
• Ahrefs: What is Answer Engine Optimization?
• Quotes from SEOPulse conversations with agency partners, 2026