Structuring Content for AEO: Frevana’s Step-by-Step Playbook

16 min read · Feb 13, 2026

Executive Summary

AI Engine Optimization (AEO) isn’t some shiny “future trend” anymore. It’s the new front door to your brand.

When someone opens ChatGPT, Gemini, Perplexity, or Amazon Rufus and asks for recommendations, those AI answers are the new search results page. That’s where first impressions are happening.

This guide walks you through a practical, end-to-end playbook for structuring content specifically for AEO—using Frevana’s approach as a real-world model. You’ll see how to:

Figure out what real users actually ask AI models in your category
Turn those prompts into content structures AI loves to surface
Fix your site’s foundation so LLMs can easily read, understand, and trust you
Spot and close content gaps vs. your competitors
Launch, measure, and iterate based on real AI visibility data

By the end, you’ll have a concrete blueprint you can put into action right away—whether you’re a solo marketer or running a full growth team—and a sense of where a platform like Frevana can automate the heavy, repetitive work.

Introduction: When “Ranking #1 on Google” Isn’t Enough

Picture this. It’s 2026, and someone wants a new productivity app for their remote team.

They don’t open a search tab and type a keyword.
They open ChatGPT and say:

“What are the best productivity apps for remote teams with AI features and strong security?”

A few seconds later, they get a neat answer: a short list of products, clear pros and cons, rough pricing, and notes on who each one is best for—with maybe one or two links if they feel like clicking through.

If your brand isn’t mentioned in that tight little list, you’re out of the running before the “search” even hits a browser.

That’s the world AEO is built for. The game has shifted from asking:

“How do I rank this page on Google?”

to:

“How do I become one of the default brands AI recommends when people ask questions like this?”

Frevana lives in this new reality. It’s an end-to-end AEO platform designed to help brands show up in AI answers across ChatGPT, Perplexity, Gemini, Amazon Rufus, and more. But tools alone won’t save you—you need a clear, repeatable way to structure your content so AI systems recognize, trust, and recommend you.

This is that strategy.

Market Insights: What AEO Really Means in 2026

Before we jump into tactics, let’s zoom out and talk about how AI answers actually work in practice.

1. AI answers are intent-first, not keyword-first

Old-school SEO was obsessed with keywords. AI assistants care about what the person is really trying to do.

If someone asks:

“Is [Brand A] good for small law firms?”

the AI isn’t just hunting for that exact phrase on a web page. It’s trying to understand:

The user’s context (small law firm, compliance-heavy, budget-aware)
The decision they’re making (can I trust and buy this?)
Their constraints (features, price range, security, support)

Content that wins in this world is built around real-life scenarios, questions, and decisions—not just strings of keywords.

2. AI assistants pull from everywhere

AI engines don’t just read your site and call it a day. They’re pulling signals from:

Your website and blog
Third-party sites (reviews, marketplaces, media, forums)
Public knowledge graphs and databases
Competitors’ content
User behavior and past queries

When your information is messy, inconsistent, or incomplete, the AI doesn’t shrug and give up—it fills in the blanks with someone else’s narrative.

3. Visibility is no longer a total black box

Not long ago, AI answers felt impossible to analyze. Now, platforms like Frevana have processed more than 60 million AI user queries, tracking:

Which brands get mentioned (and how often)
In what types of questions and contexts
Which competitors are preferred—and what seems to drive that preference

So AEO isn’t a mysterious art. You can treat it like any serious growth channel: data-driven, testable, and measurable.

4. Speed matters more than ever

Here’s the fun part: results don’t take half a year anymore. Frevana’s customers commonly see traction in a few weeks, not in the 6–12 month window we’re used to with traditional SEO.

In a channel this young and fast-moving, being early in your category isn’t a vanity metric—it’s a serious advantage.

With that in mind, let’s walk through the step-by-step content playbook.

Frevana’s AEO Content Playbook: From Prompt to Published

Think of AEO as a simple four-stage loop:

Discover what people ask AI (and who’s winning those answers)
Design the content structures that best serve those questions
Deploy content in a way that AI can easily read, trust, and recommend
Diagnose & iterate using real AI visibility data

We’ll map each stage to specific Frevana agents and workflows, but the logic works even if you’re doing this with spreadsheets and elbow grease.

Step 1: Discover – Start With Real AI User Prompts

1.1 Mine the questions people actually ask

Instead of guessing what your audience might type, look at what they already say to AI assistants. Frevana’s User Prompt Research agent does this at scale, pulling from millions of questions users ask when they’re:

Comparing brands
Evaluating use cases
Searching for alternatives
Asking for “best” or “top” picks in a category

If you’re doing this without Frevana, you can rough it by:

Asking ChatGPT or Gemini:
- “What questions do people usually ask before buying [product category]?”
Browsing Reddit, niche forums, Amazon reviews, G2, Capterra
Talking to sales and support:
- “What do prospects ask over and over again?”

You’re hunting for patterns like:

“Best X for [niche use case]”
“X vs Y for [specific scenario]”
“Is X good for [industry / team size]?”
“Affordable / budget / enterprise options in [category]”

These aren’t just “keywords”—they’re the raw material for your AEO content strategy.

1.2 Classify search intent so you don’t mix apples and oranges

Not every prompt means the same thing. Someone asking:

“What is AI Engine Optimization?”

is clearly just trying to learn. Someone asking:

“Best AEO tool for e-commerce brands under $300/month”

is halfway to pulling out a credit card.

Frevana’s Search Intent Classifier automatically buckets prompts as:

Informational
Commercial
Transactional
Navigational

Why this matters: the structure of your content should match the intent. For example:

Informational → guides, explainers, “what is / how it works”
Commercial → comparisons, “best of” lists, solution overviews
Transactional → pricing pages, focused landing pages, strong CTAs
Navigational → branded pages, product overviews, how-to-start content

In other words: don’t treat “What is AEO?” and “Which AEO platform should I buy?” like the same query. AI doesn’t—and you shouldn’t either.

Step 2: Design – Structure Content Around Scenarios & Decisions

2.1 Shift from “topics” to “customer scenarios”

This is where we move away from generic blog topics and into how your customers actually live their lives. Frevana’s Customer Scenario Strategist agent looks at prompts and pulls out:

Trigger moments (“Our ad CAC spiked”, “We stopped showing up in AI answers”)
Buyer limits (budget, team size, regulations, region)
Competitive context (“We’re choosing between [you] and [competitor]”)

From there, you can design pages or sections like:

“Best [product category] for [specific industry]”
“How [role] teams use [your brand] to [achieve result]”
“Is [your brand] a good fit for [company size / use case]?”

Each scenario should grow into a little content “ecosystem”:

One flagship page that thoroughly answers the scenario
Supporting content—articles, FAQs, case studies—that back it up and explore angles in more depth

Instead of a random pile of blog posts, you’re building clear pathways that match how real people research and decide.

2.2 Use a consistent, AI-friendly content skeleton

AI assistants love structure. It helps them quickly scan, understand, and quote your content in their answers. For any page you want appearing in AI recommendations, try a skeleton like this:

Plain-language summary
- A short, jargon-free overview of who this is for and what it helps them do in that scenario.
Who this is best for
- Industries
- Company sizes
- Roles or teams
Key benefits framed as outcomes
- Less “We have Feature X” and more “Feature X helps you cut churn / save time / reduce costs.”
Clear pros and trade-offs
- Be honest and specific. AI tends to trust balanced, nuanced content over hype.
Comparison context
- “Best for X users who value Y, versus competitors better suited for Z.”
Evidence & proof
- Real metrics, concise case studies, short customer quotes.
Frequently asked questions
- Lift these straight from the AI prompts and sales questions you discovered earlier.

Frevana’s AEO Article Writer follows this exact kind of logic—pulling from your product data, prompt research, and brand guidelines to create structured, AI-friendly content at scale.

2.3 Blend human-friendly and AI-friendly (you need both)

It’s tempting to write “robot food” and call it a day. Resist that. The best AEO content:

Feels natural and helpful to a human reading it on your site
Is cleanly structured with clear headings and tight summaries so AI can parse it instantly
Uses consistent names and terms for your products, plans, and features across every page

Imagine an AI as a hyper-speed reader skimming your site in a single heartbeat. Your job is to remove confusion and highlight the essentials.

Step 3: Deploy – Make Your Site LLM-Readable

You can have beautifully structured content and still lose if AI engines can’t properly crawl or interpret your site.

3.1 Audit your technical foundation

Frevana’s LLMs inc. Sitemap & Robots.txt Auditor agent looks for the unglamorous but critical stuff:

Can AI crawlers easily find and follow your sitemaps?
Are robots.txt or similar files accidentally blocking important pages?
Are your key pages indexable and linked from other parts of your site?
Do you have “orphan” pages or crawl loops that confuse bots?

Doing this manually? Focus on:

A clean, current sitemap.xml (plus separate sitemaps for blogs/products if needed)
A robots.txt that lets major crawlers access your important public content
Canonical tags so duplicates don’t muddy the waters
Simple, human-readable URLs (think /aeo-platform-for-ecommerce, not /p=123?x=9)

You’re basically tidying the house before inviting AI in.

3.2 Make your product landing pages AI-first

If you sell via Amazon, marketplaces, or e-commerce, AI assistants often rely heavily on your product detail pages to decide what to recommend.

Frevana’s Product Landing Page Maker takes core product info (for example, from Amazon listings) and turns it into landing pages optimized for AEO bot indexing, emphasizing:

Your core value proposition
Real-world use cases and scenarios
Pros, differentiators, and ideal customer profiles

Doing this yourself? Make sure:

Product pages have strong, descriptive text—not just photos and icons
You clearly answer the “who/what/why/when/how much” questions in words
Those pages are linked to relevant blog posts, FAQs, and case studies for extra context

3.3 Standardize how you talk about your brand

AI engines try to build a mental “model” of your brand: what you do, who you help, and where you fit in your space. You can make that job easy or hard.

Help them out by:

Using consistent names for products, features, and plans across your entire site
Keeping pricing and plan details synced wherever they’re mentioned
Maintaining a clear, up-to-date “About” or “Overview” page that lays out who you are and what you offer

Frevana taps into these building blocks across its AEO Article Writer, AEO PR Strategist, and Brand Preference Analyst so your positioning shows up consistently wherever AI is learning about you.

Step 4: Diagnose & Iterate – Treat AEO Like a Growth Channel

Once your structured content is live, the real game begins.

4.1 Monitor your AI visibility like you monitor SEO

Frevana’s AI Visibility Monitoring and AEO Full-Stack Data Scientist agents track things like:

How often you appear in AI answers for your target prompts
Which brands are recommended alongside—or instead of—you
How visibility shifts over time and across platforms (ChatGPT, Gemini, Perplexity, Amazon Rufus, etc.)

Think of it as AEO’s version of rank tracking and share of voice.

Every month, ask yourself:

For which prompts did our visibility improve or drop?
Which categories or use cases are we completely missing from?
Which competitor names keep popping up next to ours in AI answers?

This turns AI from a black box into a channel you can actually coach and optimize.

4.2 Dig into brand preference dynamics

The Brand Preference Analyst goes a layer deeper and uncovers:

Which brands AI engines favor in your category
What content patterns those favored brands share (deeper use cases, better social proof, clearer pricing, niche positioning, etc.)

If you’re scrappy and doing this by hand, you can ask AI directly:

“Which brands are best for [your category/use case] and why?”
“Why might someone pick [competitor] over [your brand]?”
“What information is missing about [your brand] that would help people decide?”

Look for themes like:

Competitors with richer comparison pages
Sharper “this is who we’re for” messaging
More specific, relevant case studies in your niche

Those patterns become your next content sprints.

4.3 Close content gaps with purpose-built assets

Once you know where you’re weak or invisible, you can plug those holes quickly with:

New AEO articles (via the AEO Article Writer) tailored to missed prompts
PR and thought leadership via the AEO PR Strategist to secure high-authority mentions
Expanded FAQ sections driven by emerging user questions

Because Frevana can automate the loop from diagnosis → content plan → content creation, brands typically see measurable lift in a week or two, rather than months of trial and error.

Practical Examples: Turning Prompts Into Structured Content

Let’s make this more concrete with two simple scenarios.

Example 1: SaaS tool for local businesses

Prompts surfaced by User Prompt Research:

“Best scheduling software for local service businesses”
“Affordable appointment tool for salons and spas”
“Alternative to [competitor] for small gyms”

How to turn that into content:

Scenario page:
- Title: “Best Scheduling Software for Local Salons and Spas”
- Sections:
  - Who this is for (salons, spas, independent stylists)
  - Key outcomes (fewer no-shows, online booking, SMS reminders)
  - Clear pricing overview
  - Pros and trade-offs (simple vs advanced features, learning curve)
  - FAQs like “Does this integrate with Instagram?” or “Can clients book from their phones?”
Comparison content:
- “Top 5 Alternatives to [competitor] for Local Service Businesses”
- Honest breakdown of when you’re a better fit and when the competitor might win.
Proof:
- A snackable case study:
  - “How [Salon Name] cut no-shows by about a third in two months.”

Now, when AI assistants get those prompts, they have a clear, structured, highly relevant story about your product to pull from.

Example 2: E-commerce brand selling on Amazon

Prompts identified:

“Best ergonomic office chair under $300 on Amazon”
“Office chair with good back support for tall people”

How to structure content:

Product-specific landing page (via Product Landing Page Maker):
- Straightforward headline
- Price range
- Who it’s for (height range, weight, work style)
- Key benefits (better posture, long-session comfort)
- Pros and trade-offs (firm vs soft, assembly time, style)
Buying guide article:
- “How to Choose an Ergonomic Office Chair Under $300 (Using Real Customer Data)”
- Include your chair as one of several options and explain clearly why and for whom it’s a good pick.
FAQ tuned to prompts:
- “Is this chair comfortable for tall people?”
- “Can I use this chair 8+ hours a day?”
- “Does it work on hardwood floors?”

You’ve just given AI models everything they need to confidently recommend your product with context and nuance.

Product Relevance: Where Frevana Fits in This Playbook

You can execute this playbook manually. Many teams do, at least at the beginning. But the reality is: AEO is data-heavy and always-on. It’s not something you “set and forget.”

This is where Frevana becomes less of a nice-to-have and more of a multiplier:

Real AI prompt data – pulled from real user questions, not made-up guesses
End-to-end automation – from diagnosing your visibility to creating and launching new content
Cross-platform tracking – ChatGPT, Gemini, Perplexity, Amazon Rufus, and more
Specialized agents aligned with every step of this article:
- User Prompt Research
- Customer Scenario Strategist
- LLMs.txt, Sitemap & Robots.txt Auditor
- AEO Full-Stack Data Scientist
- AEO Content Advisor
- AEO Article Writer
- Product Landing Page Maker
- AEO PR Strategist
- Search Intent Classifier
- Brand Preference Analyst

Backed by investors like Andreessen Horowitz, Craft Ventures, and supported by OpenAI, Frevana is built for one clear outcome:

Make your brand show up where AI is making the recommendations.

Actionable AEO Checklist You Can Start This Week

Ready to actually do this? Here’s a simple, time-boxed game plan.

Day 1–3: Discovery
- List your top 5–10 products or core offers
- Brain-dump 20–50 likely AI prompts customers might ask about them
- Use AI tools (or Frevana’s User Prompt Research) to validate and expand that list
- Label each prompt’s intent: informational, commercial, or transactional
Day 4–7: Design
- Group prompts into 5–10 core customer scenarios
- For each scenario, sketch:
  - One flagship “scenario” page
  - Supporting pieces (FAQs, blog posts, case studies)
- Decide on a standard content skeleton for all scenario pages
Week 2: Deploy
- Audit your sitemap and robots.txt for basic crawlability
- Publish or refresh at least 2–3 key scenario pages with clear structure
- Update product pages so they spell out who they’re for and what outcomes they deliver
Week 3–4: Diagnose & Iterate
- Start tracking your AI visibility on major AI platforms
- Identify prompts where you’re missing or weak
- Create or refine content to directly address those gaps
- Repeat this loop monthly

If you’d rather move in days instead of weeks, this is exactly the workflow Frevana’s automated agent team is designed to run for you.

Conclusion: AEO Isn’t the Future—It’s the Present

Right now, millions of people are asking AI assistants:

“What should I buy?”
“Which tool is best for my situation?”
“What’s the best option for my budget and needs?”

AEO is about making sure your brand shows up in those answers—consistently, credibly, and in a way that actually drives revenue.

By:

Starting from real AI user prompts
Structuring content around true customer scenarios and intent
Making your site technically friendly for LLMs
Monitoring and iterating based on AI visibility data

…you turn AI recommendations from a mystery into a repeatable growth channel.

If you’re ready to stop guessing and start showing up where decisions are actually made, explore how Frevana can launch your end-to-end AEO agent team in minutes, with:

A 7-day free trial
No credit card required
Tangible improvements in as little as 2–4 weeks

Start structuring your content for AI answers today—before your competitors become the default recommendation your customers see first.