How to Build a Strategy for AEO and GEO
AEO and GEO strategy implementation guide: audit AI visibility, structure content for citations, and build 12-month authority across ChatGPT, Perplexity, and Google AI Overviews.
Most marketing teams are still treating AI search as something to watch rather than something to act on. That's a mistake. ChatGPT, Perplexity, Google AI Overviews, and Claude are already answering questions your customers are asking right now. If your brand isn't being cited, a competitor is. Building a proper strategy for AEO and GEO isn't optional anymore. It's the next channel, and the window to build early authority is still open, but not indefinitely.
This article walks through how to structure an AEO and GEO strategy implementation that's practical, measurable, and designed to compound over time.
Understanding the Difference (and Why Both Matter)
Answer Engine Optimisation (AEO) focuses on getting your content selected as a direct answer by AI models and voice assistants. Generative Engine Optimisation (GEO) is broader: it's about ensuring your brand appears as a cited, trusted source within AI-generated responses across platforms like ChatGPT, Perplexity, and Google's AI Overviews.
They overlap significantly, but they're not identical. AEO tends to prioritise structured, question-and-answer formatted content. GEO requires you to think about how AI models evaluate source authority, content freshness, and topical depth when generating their outputs. Harvard Business Review has noted how generative AI is reshaping how content is discovered and consumed, and the implications for search visibility are significant.
Where They Converge
Both disciplines demand the same foundational work:
Clear, factual content that directly answers specific questions
Structured data and schema markup so AI models can parse your pages accurately
Consistent brand signals across your website, third-party mentions, and backlink profile
Topical authority built through depth, not just breadth
If you're already doing solid SEO, you're not starting from zero. But optimising for both AEO and GEO requires deliberate additions to your existing programme, not just a rebrand of what you're already doing.
Building Your Dual Visibility Strategy: A Practical Framework
A dual visibility strategy for AEO and GEO doesn't have to be complex. What it does have to be is structured. Vague intentions don't produce citations. Here's how to build something that actually executes.
Step 1: Audit Your Current AI Visibility
Before you build anything, you need a baseline. Run your brand through the major AI platforms and ask the questions your customers actually ask. Are you appearing? In what context? Are competitors being cited instead of you?
This isn't a one-off exercise. Visibility across answer engine and generative search platforms shifts as models are updated, as competitors publish new content, and as your own site changes. Tracking needs to be ongoing.
At Lua Rank, we assess websites across 13 optimisation layers to identify exactly where visibility is being lost and why. That kind of structured audit is the starting point for any serious implementation.
Step 2: Map Your Content to AI-Answerable Queries
AI models are built to answer questions. Your content needs to match that intent explicitly. The most effective way to do this is to map your existing content library against the specific questions your target audience is asking across different stages of their journey.
For each priority topic, you want:
A clear, direct answer in the first 100 words of the page
Supporting context that demonstrates expertise and depth
FAQ sections that anticipate follow-up questions
Schema markup (FAQ, HowTo, Article) that makes the content machine-readable
Don't try to cover everything at once. Start with your five highest-traffic topics and build depth there before expanding. McKinsey's research on generative AI's economic potential points to structured, high-quality content as a core driver of AI-mediated value creation, which applies directly to how brands earn citations.
Step 3: Build a 12-Month Execution Calendar
This is where most teams fall down. They understand what needs to happen but they don't schedule it, assign it, or track it. A strategy sitting in a deck achieves nothing.
Your execution calendar should break down into monthly themes with weekly tasks. The first 90 days typically focus on technical fixes and content restructuring. Months four through six shift toward topical authority building. The back half of the year is about scaling what's working and tracking competitive movement.
Phase | Timeframe | Primary Focus | Key Outputs |
|---|---|---|---|
Foundation | Months 1-3 | Technical audit, schema, content restructuring | AI-readable pages, structured data in place |
Authority Build | Months 4-6 | Topical depth, citations, entity coverage | Increased citation frequency across platforms |
Scale and Optimise | Months 7-12 | Competitive tracking, content expansion | Measurable visibility gains vs. competitors |
Step 4: Track Visibility, Not Just Traffic
Traditional SEO metrics (rankings, organic traffic) don't tell you whether you're being cited by AI models. You need to track visibility directly: how often your brand appears in AI-generated responses, which platforms are citing you, and how that's changing over time relative to competitors.
This matters because global search advertising spend continues to shift toward AI-mediated discovery, which means the brands that build AI citation authority now are the ones that will benefit most as the channel matures.
Common Mistakes That Undermine AEO and GEO Implementation
A counterargument worth addressing: some teams argue that AI search is too unpredictable to invest in systematically. Models update frequently. Citation logic isn't fully transparent. Why build a programme around something that could change tomorrow?
It's a fair concern, but it applies equally to Google, which has changed its algorithm thousands of times and yet the fundamentals of good SEO have remained consistent for two decades. The same is true here. Strong content, clear structure, genuine authority, and technical hygiene are not going to stop working. What changes is the weighting, not the direction.
The Mistakes We See Most Often
Starting with tools before strategy. Buying an AI visibility tool without a plan produces data you don't know how to act on.
Treating AEO and GEO as a one-time project. This is a programme, not a campaign. It compounds over months, not days.
Ignoring competitor benchmarking. You don't just need to improve. You need to improve faster than the brands competing for the same citations.
Skipping the technical layer. Schema markup, crawlability, and page structure affect how AI models parse your content. Getting these wrong undermines everything else.
Where This is Heading
The trajectory is clear. AI-generated responses are becoming the default interface for information discovery across global markets. Brands that build citation authority now, while the field is still relatively open, will find it significantly harder to displace once competitors have established themselves. The window isn't closing tomorrow, but it is closing. Teams that treat this as a 2025 priority rather than a 2026 review item will be glad they did.
If you want a structured way to start, Lua builds a complete 12-month AI visibility programme tailored to your brand, schedules every task, and tracks your progress across ChatGPT, Perplexity, Google AI Overviews, and Claude. It's designed specifically for marketing teams who want to move fast without the cost of a full-service agency. You can see how it works at luarank.com.
Frequently Asked Questions
How long does it take to see results from an AEO and GEO strategy?
Results vary depending on your starting point, your industry's competitive landscape, and how consistently you execute. That said, we've seen brands achieve first-page ChatGPT citations in under 40 days when the foundational technical work is done correctly and content is structured for AI extraction. Sustained, compound visibility growth typically becomes measurable between months two and four of a structured programme.
Do I need a separate strategy for each AI platform?
Not entirely, but platform-specific adjustments matter. ChatGPT, Perplexity, and Google AI Overviews each have different content processing behaviours and citation logic. A good AEO and GEO strategy starts with a strong universal foundation (clear content, structured data, technical hygiene) and then layers in platform-specific optimisations. Treating every platform identically will leave visibility on the table.
Can smaller marketing teams realistically execute an AI visibility programme?
Yes, with the right structure. The key is prioritisation and a clear task schedule. Teams with one person dedicating three to five hours per week can make meaningful progress if they're following a well-structured plan rather than trying to figure out what to do next each week. The biggest barrier isn't resources; it's the absence of a clear, day-by-day execution framework.
