The complete GEO guide: How to rank better on AI platforms in 2025
Senior SEO & AI consultant
July 18, 2025
ChatGPT now handles over 1 billion searches per week. Let that sink in. That’s not monthly or yearly searches – it’s every single week. And although it still doesn’t come close to Google’s volume, we must remember that ChatGPT is still relatively new. The growth is exponential, and experts predict that organic traffic may decline by up to 25% in the near future as more consumers shift toward AI-powered platforms.
Companies already optimizing for AI platforms aren’t just seeing traffic – they’re seeing high-quality traffic with better engagement rates and longer time on site than traditional Google traffic. And if you think you can wait this out, think again – your competitors might soon overtake you.
In this guide, we’ll give you actionable strategies to rank better on AI platforms, based on practical experience and measurable results.
Generative Engine Optimization (GEO) is about being cited and recommended in AI-generated responses from platforms like ChatGPT, Perplexity, Google’s AI Overview, and others. It doesn’t replace SEO – it complements it. But it requires a different approach to content optimization than traditional SEO.
The difference between SEO and GEO is fundamental and critical to understand. SEO has always been about ranking high on Google to generate traffic and clicks. You optimize for specific keywords, build links, and measure success through rankings and organic traffic.
GEO, on the other hand, is about being cited and recommended within AI-generated responses. You can achieve massive visibility without necessarily getting clicks, because users receive answers directly within the AI interface.
Here’s a real-world example:
If you search for “best computer in 2025” on Google, you’ll often see an AI Overview at the top of the results. Interestingly, it’s not always the top 1–3 results on Google that appear in the AI Overview. Sometimes a page from position 17 will jump to the top of the AI Overview because it answers the question more effectively than position 1. That changes the game and creates new opportunities for companies who understand how to optimize for AI interpretation.
Why focus on SEO if AI is the future?
Because AI still crawls websites and generates its responses based on organic results. It’s an extension of what you’re already doing – not a replacement. But it does require a different way of structuring and presenting your content. Think of AI as an additional reader of your content – a reader that needs structure, context, and clarity in order to understand and pass along your information.
One of the most dramatic changes brought by widespread AI adoption isn’t technological – it’s behavioral. The way people search for information is undergoing a fundamental transformation, and if you don’t understand this shift, you’ll be left behind.
For decades, we’ve learned to “speak Google’s language.” We’ve reduced our complex information needs to simple terms like “best smartphone 2025,” “iPhone vs Samsung,” or “cheap laptops.” We adapted to the limitations of search engines and learned to think in keywords instead of natural questions.
But AI platforms have eliminated those limitations. Now people can ask the real questions they have:
“Can you recommend a smartphone under 6,000 DKK with an excellent camera for photography enthusiasts who travel a lot?”
This kind of query doesn’t just contain the product category – it includes budget, specific features, use cases, and personal preferences. It’s a revolution in how we communicate our needs.
Let’s give you a concrete example:
If you search for “juice cleanse” on Google, you’ll get lots of webshops offering juice cleanse products. But if you just type “juice cleanse” into ChatGPT, it won’t know your intent. It might ask whether you’re looking for recipes or what a juice cleanse includes. It doesn’t know your goal – so you need to be more specific.
This illustrates a critical difference:
AI platforms require context to deliver valuable answers. But when they have that context, they can deliver incredibly precise and personalized recommendations.
A particularly interesting development is sequential prompting. Instead of trying to formulate the perfect query all at once, users now engage in ongoing conversations with AI systems. They might start with “Best headphones 2025” follow up with “They need the best noise cancellation,” then “Should also have a mic,” then “Find prices and reviews,” and finally “Check if they have good battery life for workouts.”
This conversational approach allows AI systems to understand the user’s needs in more depth and deliver more accurate recommendations. And if you’ve been part of that journey with the user and they end up clicking your product, that’s extremely high-quality traffic.
That’s why traffic from AI platforms often has higher engagement rates and longer time on page than traditional Google traffic. These users are better pre-qualified because the AI has already helped them define their needs.
Schema markup is perhaps the most important technical element for ranking on AI platforms. It’s the easiest way for AI platforms to read the data on your site. AI starts by reading what’s in your code – not what’s displayed on the frontend.
Schema markup is a type of structured data, a code you embed in your HTML, typically in the header section. It helps search engines and AI understand your content and categorize it correctly.
You can also add extra information that isn’t visible on the frontend but can be read and understood by Google’s algorithms and AI systems.
Most important schema types:
FAQ schema – AI prioritizes Q&A formats highly. Implementing FAQ schema on your pages significantly increases your chances of being cited in AI answers.
Product schema – Essential for ecommerce businesses and should include not just basic info like name and price but also detailed descriptions, reviews, availability, and technical specs.
Article schema – Critical for informational content and blog posts.
Practical implementation:
Use TechnicalSEO.com’s schema markup generator to create precise markup. You can choose the exact schema type you need and fill in only the relevant fields. Always test with Google’s Rich Results Test to ensure correct implementation. Just paste your landing page into the tool, and it will show if there are any critical errors in your schema markup. We recommend avoiding automatic plugins and instead creating the markup manually for full control.
AI systems prioritize sources that demonstrate high levels of Experience, Expertise, Authoritativeness, and Trustworthiness (E-E-A-T). These principles were originally developed by Google but have become even more important in the AI era, as AI systems actively seek out trustworthy, authoritative sources.
To rank well in AI-generated responses, all four components must be in place on your website. It’s not enough to focus on just two out of four.
Experience: AI systems prioritize content from sources that show real experience with the products or services being described. This means not just theoretical knowledge but actual hands-on usage. For ecommerce, this could include detailed product descriptions based on real usage, customer stories, and case studies.
Expertise: Your expertise must be clear and verifiable. AI looks for indicators like author bios, certifications, industry experience, and deep technical insight. It’s about establishing yourself as a go-to source within your niche.
Authoritativeness: You build authority by being recognized by other experts and institutions. This includes backlinks from respected sources, mentions in industry publications, and partnerships with credible organizations.
Trustworthiness: Perhaps the most important factor. AI systems look for transparency, accurate contact details, clear privacy policies, and positive customer reviews. They’ll also check for factual errors and inconsistencies.
Reviews in particular are heavily weighted in ChatGPT’s product recommendations. When the platform compares products, it uses available reviews – so reviews are more important than ever, not just for conversions but to be selected by AI systems.
One of the most critical changes you need to make in transitioning from traditional SEO to GEO is shifting from feature-focused descriptions to real-life use scenarios. AI systems don’t understand classic feature lists. They need context about what, who, when, and how.
Example – Backpack description:
Before (traditional):
Modern design
Spacious interior
High-quality materials
Multiple compartments
Durable construction
Comfortable straps
This doesn’t answer key user questions: What is it for? Who is it for? When is it relevant?
After (AI-optimized):
22L Business Travel Backpack
What: Fits under the seat on most airlines, holds laptops up to 15.6 inches
Who: Designed for business travelers needing quick access to tech gear and essentials
When: Perfect for 1–3 day business trips or daily commuting
How: Eliminates the need for overhead bin space and gives organized access to work essentials
This gives AI the context it needs to match the product to specific queries like “Can you recommend a bag for short business trips that fits under the airplane seat?”.
Pro tip: Personas will be extremely important going forward. If you can describe your target persona in detail, AI systems can match your products to them with precision.
As mentioned earlier, users no longer just search with keywords like “best smartphone 2025.” They ask full, complex questions like:
“Can you recommend a smartphone under 6,000 DKK with a great camera for travel photography?”
This evolution means your content must align with natural search behavior.
Optimize for natural language:
Write like you’re speaking to a friend
Answer specific, nuanced questions
Include context and scenarios
Focus on solving problems, not listing features
This approach gives AI systems the context they need to understand when your product is relevant.
AI Overview currently focuses more on informational searches than product searches. This means you need to think strategically about how you build content around your core products.
Instead of focusing only on product pages, create comprehensive informational content that answers your audience’s questions.
Examples include:
Buying guides and comparison articles
How-to guides and problem-solving content
FAQ sections with common questions
Detailed product guides with use cases
This approach gives AI systems the context they need to understand when your product is relevant.
ChatGPT is no longer just an informational platform – it’s becoming a sales channel. With the introduction of shopping features, businesses will soon be able to upload product feeds directly to the platform.
Even now, ChatGPT has begun crawling websites and showing products when users search for things like clothing or shoes. But in the near future, when the full rollout happens, we’ll be able to upload product feeds just like we do in Google Merchant Center or Facebook.
Sign up now at: https://openai.com/chatgpt/search-product-discovery to be ready and get notified when product feed uploads become available.
We also don’t expect it will take long before commercial opportunities like ads and promotional campaigns appear on ChatGPT – they need to finance their development somehow. Right now, the platform has massive and growing traffic, so expect advertising opportunities soon.
Almost simultaneously with ChatGPT’s rollout of shopping functionality, Google AI Overview was launched in Denmark and the rest of the Nordics (coincidence? We doubt it), and it’s fundamentally changing how search results look.
Currently, it’s mostly informational searches that trigger AI Overview, not product queries – but that’s coming.
The fascinating thing is that you may get fewer clicks because users receive answers directly on Google without clicking any links. But you can also get massive visibility and brand mentions.
And if you use Ahrefs, you can see which searches trigger AI Overviews. Go into your Rank Tracker and look at your informational searches – if you see a small Gemini icon, that indicates that the search appears in AI Overview.
Interestingly, you can jump from position 17 to the top of the AI Overview if your content answers the query better than the current position 1. That means it’s no longer just the top 3 positions that drive value.
The first thing you need to do is check whether AI crawlers can access your site. Go to your website and add /robots.txt to the end of your URL. Then look for whether chatbots like CCBot or GPTBot are blocked.
Look for lines such as:
User-agent: CCBot
Disallow: /
or
User-agent: GPTBot
Disallow: /
If you see these lines, it means AI crawlers are blocked from accessing your site.
You’ll need to remove these blocks so that AI platforms can crawl your content. If you don’t see such lines, everything is fine.
Before implementing new schema markup, check what’s already on your site. If you use WordPress with Yoast Pro or similar plugins, you might already have some auto-generated schema markup.
Use Google’s Rich Results Test to analyze your site and see what structured data is currently present.
Start with the most important schema types for your business:
Product schema – For all product pages
Article schema – For blog posts and informational content
Organization schema – For your homepage and about pages
Example FAQ schema:
{
“@context”: “https://schema.org”,
“@type”: “FAQPage”,
“mainEntity”: [{
“@type”: “Question”,
“name”: “How do I choose the right smartphone for travel photography?”,
“acceptedAnswer”: {
“@type”: “Answer”,
“text”: “For travel photography, focus on camera quality, battery life, and durability. Look for phones with optical image stabilization, a large sensor, and strong low-light performance.”
}
}]
}
Once your technical foundation (like schema markup and crawler access) is in place, turn your attention to the content you already have on your site.
Many forget that older content can be a goldmine – especially when adapted to how AI reads and interprets information.
Start by reviewing your most important blog posts and product pages. Here’s what you can do:
Add FAQ sections so both users and AI can easily find answers to key questions
Rewrite product descriptions using the what/who/when/how model to make them more useful and user-friendly
Ensure your pages comply with E-E-A-T principles (Experience, Expertise, Authority, Trustworthiness), which are becoming more important in both classic SEO and AI-powered search
Sometimes just a few adjustments can dramatically improve your visibility – not only in traditional search results but also in AI-generated answers.
Now that your content is more AI-friendly, it’s important to monitor how it’s being found and used.
Several AI assistants generate traffic to websites – but detecting it requires a bit of extra setup in your analytics.
In Google Analytics, you can begin filtering traffic from known AI sources such as:
chatgpt.com
perplexity.ai
Other AI-related domains and user agents
Once you’ve isolated this traffic, compare engagement metrics (e.g., time on page and bounce rate) with traffic from traditional Google search. This will help you see whether your AI optimization is working – and where further improvements may be needed.
When working with GEO, it’s not enough to just monitor classic SEO metrics like rankings and organic traffic. GEO requires an expanded approach to measurement, because visibility often happens without a click – and the traffic you do get behaves differently.
Traditional KPIs still matter:
Organic rankings
Organic traffic
Backlinks and domain authority
But you should also track:
Brand mentions and citations in AI-generated answers
Recommendations in AI assistants (e.g., “Top 5 products” lists)
Visibility without clicks
Engagement rate and time on page from AI traffic
Early data shows that AI-sourced traffic often has higher engagement because users already have context and are more motivated when they do click through. That makes it even more important to measure quality, not just quantity.
How to track GEO in practice:
Use Google Analytics to filter traffic from AI sources like chatgpt.com and perplexity.ai
Use Ahrefs Rank Tracker to monitor which pages trigger AI Overview
Monitor brand mentions in AI-generated responses and content
Compare engagement metrics between AI traffic and traditional search traffic
It’s all about understanding how users find you – not just how many do.
To help you get started with your GEO efforts, we’ve created a 30-day action plan to ensure you hit the ground running.
GEO is not the future – it’s the present. With over 1 billion weekly searches on ChatGPT and increasing adoption of AI platforms, you can no longer ignore this shift. Businesses are already seeing measurable traffic from AI platforms – with higher engagement than traditional Google search. Those who implement GEO strategies now will have significant competitive advantages.
But remember: GEO complements SEO – it does not replace it. AI systems still crawl websites and build responses from organic results. But they require a different approach to content structure and presentation. Businesses that master both disciplines won’t just rank high in traditional search – they’ll also be cited and recommended by AI systems.
Most important takeaways:
Optimize using E-E-A-T principles
Rewrite product descriptions using use-case scenarios
Create informational content around your products
Monitor and measure AI traffic
The key message: Lay your foundation now. Implement schema markup, optimize for E-E-A-T, and create content that answers the real questions your audience is asking. Start with the technical groundwork, then improve your content. The earlier you begin, the better positioned you’ll be when AI search becomes fully mainstream.
SEO focuses on ranking high in traditional search results to generate clicks and traffic. GEO focuses on being cited and recommended in AI-generated answers. You can gain visibility without getting clicks, since users get answers directly in the AI platform.
Absolutely not. GEO supplements SEO – it doesn’t replace it. AI systems still crawl websites and build their answers on organic results. You need to master both.
Start with schema markup – especially FAQ schema – because AI systems prioritize Q&A formats heavily. Also, check your robots.txt file to ensure AI crawlers can access your site.
Go to your homepage and add /robots.txt at the end of the URL. Look for lines like User-agent: CCBot or GPTBot with Disallow: /. If present, remove them.
Schema markup is structured data in JSON-LD format that helps AI systems understand and categorize your content. It’s critical for GEO because AI reads the code first to build a structured understanding of your site.
Not yet – but you can sign up to be notified when it becomes available:
https://openai.com/chatgpt/search-product-discovery
Track brand mentions in AI responses, the quality of AI-generated traffic (engagement rate, time on page), and your visibility on AI platforms. Use Google Analytics for tracking AI traffic and Ahrefs for spotting AI Overview triggers.
GEO is especially effective for ecommerce, B2B services, and information-based businesses – but all types of businesses can benefit from AI optimization.
Some businesses see improvements within weeks, others in a few months. Consistent implementation of schema markup and high-quality content is the key.
Feel free to call or message us – we’re happy to have an informal chat about how we can support you.
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