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Modern websites, ranked in AI search✦Cited by ChatGPT, Perplexity & Google AI Overviews✦32% of our own traffic comes from AI search✦Modern websites, ranked in AI search✦Cited by ChatGPT, Perplexity & Google AI Overviews✦32% of our own traffic comes from AI search✦Modern websites, ranked in AI search✦Cited by ChatGPT, Perplexity & Google AI Overviews✦32% of our own traffic comes from AI search✦Modern websites, ranked in AI search✦Cited by ChatGPT, Perplexity & Google AI Overviews✦32% of our own traffic comes from AI search✦
Creative & Conversion Design

Content designed for both humans and the AI engines that cite them.

The same insights, built in two structural layers: the human layer reads well, and the AI layer underneath ships clean schema, definitional opening paragraphs, and citation-ready claim-evidence pairs.

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The challenge
Your content might be good across the service pages, the blog posts, the FAQ pages, and the case studies. But the AI engines keep citing competitors instead of you, whether that is ChatGPT or Perplexity or Claude, and the issue is structure, not the writing. AI engines look for clear entity definitions, claims paired with evidence, short authoritative statements they can lift, and the links between concepts. Most content was written for human readers, with narrative flow and persuasive build, so it reads well but is hard for the retrieval layer to use. The competitors getting cited worked out that designing content for AI is a parallel job, the same insights arranged a different way.
How we solve it
On Story, Engine, and Studio builds, every page we ship is designed in two layers. The human layer is real content, with a narrative that holds attention, a clear visual hierarchy, and a flow that persuades. The AI layer adds structured signals (FAQPage and HowTo schema generated at build time, definitional first paragraphs, claim-evidence pairs the retrieval engines can pull verbatim, BreadcrumbList for context, semantic HTML rather than div soup). On the Local, Growth, and Authority retainers we apply the same dual-layer approach to monthly content. We train your team on the patterns and provide templates so AI-native structure becomes standard, not extra. The work shows up in your AI-traffic data on cite-met.com within 30 to 60 days.

Key benefits

Dual-Layer Content Architecture

Content built to hold a human reader and earn an AI citation at the same time: a persuasive narrative on top, with structured data and citable statements underneath for the answer engines. One asset that performs on two fronts.

Citation Pattern Matching

Content structures designed to match the patterns AI systems use when they pick a citation. We study the way ChatGPT and Perplexity, along with Gemini, phrase answers in your category, then build content that fits.

Scalable Template Systems

AEO content templates, structured-data generators, and quality scorecards your team can run without us. We are not building a dependency, we are building a capability your content team owns and scales on its own.

Measurable Citation Growth

Every content piece is tracked for AI citation performance. Monthly reports show which content gets cited, by which platforms, for which queries, and how citation rates change as you apply AEO design principles.

Our process

  1. 01

    Citation Landscape Analysis

    We analyze how AI systems currently answer questions in your category, which competitors get cited, and what structural patterns the most-cited content shares. This reveals the specific design opportunities for your content.

  2. 02

    AEO Template & Framework Design

    We create content templates, structured-data schemas, and design guidelines built for your content types. Each template bakes in the patterns that earn citations, from definition blocks and claim-evidence pairs to FAQ structures that map the relationships between entities.

  3. 03

    Content Production & Optimization

    We produce or restructure your priority content using the AEO frameworks, retrofitting your existing high-value pages with AI-native structure and designing new pages from the ground up to work on both layers.

  4. 04

    Team Training & Capability Transfer

    Your content team learns the AEO design principles, how to use the templates, and how to score quality. We stay on as advisors while the team makes the practice its own and scales AEO production without us.

Proof you can check

4 → 30

pages for Starlit Homes, a NetZero builder whose self-built site became a page per model plus a building-science blog.

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6 → 190+

pages for Zebra Home Cinema, rebuilt from a 6-page WordPress site with 22 city pages and 96 posts.

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90 days

for Lotso Travel's blog to rank one slot under Rogers and Telus on Canadian roaming-versus-eSIM searches.

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Explore related solutions

Answer Engine Optimization

Answer Engine Optimization is the actual technical work that gets your business mentioned by name when ChatGPT, Perplexity, Claude, and Google AI Overviews answer the questions your customers ask.

Entity Authority Building

ChatGPT, Perplexity, and Claude build internal maps of who is an authority on what. If your business is a weak entity in those maps, no amount of on-page keyword work will get you cited.

Conversion UX Design

We design for the action that pays you, a booking or a quote request, using behavioral data and steady testing rather than design by committee, so every section on the page has to earn its place.

Industries that ship this

Professionals

Professional practices sites with ProfessionalService schema.

Accountants and CPAs

Accounting firms sites with AccountingService schema.

Real Estate

Real estate agents and developers sites with RealEstateAgent schema.

Construction

Builders and contractors sites with HomeAndConstructionBusiness schema.

Custom AV Installers

AV installers sites with LocalBusiness schema.

Want to verify?

Industry sources we cite.

3 links · External

Quick answers

Frequently asked.

AEO (Answer Engine Optimization) content design is the practice of structuring content specifically for citation by AI answer engines like ChatGPT, Gemini, and Perplexity. While traditional content strategy focuses on keyword rankings and human readability, AEO content design adds a structural layer: clear entity definitions, citable claim-evidence pairs, and semantic markup that machines parse for citation selection.

No. AEO content design adds to the writing rather than replacing it. Your content still has to engage a human reader and move them to act. The AEO layer adds the structure, the formatted statements, and the semantic markup that let an AI system read the same page. Think of it as adding machine-readable subtitles to a film: the movie is unchanged, but a new audience can follow it.

Most clients see initial citations within 30-60 days of publishing AEO-optimized content, depending on the topic's competitive landscape and the frequency of AI crawler visits. Citation rates typically build progressively as AI systems re-index your content and recognize consistent structural patterns across your site.

Existing high-performing content is often the best candidate for AEO retrofitting. Content that already ranks well in traditional search has demonstrated topical authority; adding AEO structure amplifies that authority into AI platforms. We typically start by retrofitting your top 20 pages and measure citation impact before scaling to the full content library.
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We rebuild small business websites for AI search and keep them ranked monthly. The audit is free, every price is published, and every site in the portfolio is live for you to open.

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