The complete guide to Generative Engine Optimization (GEO)
AI search engines like ChatGPT, Perplexity, Claude, and Grok are becoming default entry points for information and decision-making. But here's the challenge: in AI search, users often get their answer before they ever click a link.
Malte Landwehr, CPO & CMO of Peec AI, recently shared his industry insights in a webinar with Search Engine Journal about this change we’re seeing. His experience helping idealo outrank Amazon in ChatGPT traffic proves that traffic from AI search is possible and it's already happening at scale.
Use this guide to implement GEO strategies that capture valuable traffic from AI search engines for your business.
The search shift that affects your business
Your potential customers are increasingly getting answers from AI before they ever see your website. Here's what that means in practice:
With Google's traditional search, about 60 out of every 100 searches end without someone clicking to a website. Instead, they get their answer directly from Google or search again. With AI search engines, this number jumps dramatically.
Early data suggests that for Google’s AI Mode, 95 out of 100 queries end without a click. For ChatGPT, between 78-99 queries out of 100 never send traffic to any website.
But traffic is still happening. In Germany alone, ChatGPT sends 12 million clicks per month to websites. Malte’s former company, idealo, captured 2% of those clicks, and was the most visible e-commerce destination in ChatGPT in the first half of 2025 - ahead of giants like Amazon and ebay (Source: SimilarWeb).
Your traffic potential isn't disappearing but it's simply shifting to fewer, higher-intent visitors. You need a new framework to capture it: Generative Engine Optimization (GEO).
It won’t replace SEO traffic, but you can build meaningful visibility in AI search if you approach it strategically.
Client success: One Peec AI client generated two new leads from ChatGPT in a single week using these methods.
What you'll accomplish with this guide
This guide gives you the complete implementation framework, tools, and strategies you need to succeed in GEO.
You'll discover how to measure and shape your brand's presence in AI answers, optimize your content for machine readability, and build the external presence that drives citations and visibility to your business.
Where your GEO efforts will actually work
Two AI systems that matter: Foundation Models vs RAG
To make AI search work for you, you need to know where you can actually make a difference. There are two distinct systems at work:
Foundation models like GPT-4, Claude model family, or LLaMA are trained on massive datasets and then fixed. They have knowledge cutoffs and can't learn new information after training. For current models, it's too late — they've already been trained. Your influence here is limited to shaping future training data.
Retrieval-augmented generation (RAG) is where your opportunity exists. When LLMs can't answer from their training data alone, they perform live searches (sometimes called grounding) to pull in current information. AI Overviews and ChatGPT's web search work this way.
This distinction changes your strategy completely.
Foundation models require long-term thinking about your brand presence in training data.
RAG systems offer immediate optimization opportunities you can act on today.
Query fanout adds another layer you need to understand. LLMs generate multiple related searches, not just search for your exact prompt.
When asked "What is the latest Google patent discussed by SEOs?", ChatGPT performed two searches: "latest Google patent discussed by SEOs patent 2025 SEO forum" and "latest Google patent SEOs 2025 discussed".
Understanding these patterns helps you optimize for the actual searches happening behind the scenes.
New success metrics you need to track
AI search creates two distinct types of success that your traditional SEO doesn't capture:
Brand visibility means your company name appears in generated answers. This builds awareness and influences purchase decisions even without clicks.
Website citations mean your content is used as a source. This drives traffic and reinforces your authority.
You could have your brand frequently mentioned in answer but never cited as a source, and you could have your website heavily cited but never mentioned by name. You need both, but they require different strategies.
For example, a financial services client that came to us had zero brand visibility. Their brand was not mentioned in a single answer for many of the prompts that they defined. But a single change in their approach led to their visibility jumping to 10–15%.
Why your external presence matters more than ever
In GEO, what others say about you often matters more than what you say about yourself.
When LLMs perform RAG, they retrieve sources, rank them, extract chunks, and feed them into the model. Your own website becomes less important than your presence across the sources that get selected.
The key is identifying which sources AI engines cite most for your topics, then ensuring your brand is present in them.
In short:
Foundation models are already trained — focus on RAG systems for immediate results
Track both brand mentions and website citations as separate metrics
Your external presence across cited sources matters more than your own website
LLMs search using multiple related queries, not just your exact prompt
Strategic framework to succeed with GEO
The four-phase approach that works
Source analysis: Identify where LLMs pull information for your topics.
Optimization: Improve your content and external presence based on findings.
Assessment: Measure your brand visibility and citation frequency.
Refinement: Iterate based on your performance data.
This framework scales from small businesses to enterprises, but your starting point depends on your current maturity.
Content strategy that actually gets results
Format matters as much as substance. LLMs are more likely to cite content with:
Clear H1/H2 hierarchy
Lists and bullet points
FAQ schema
One H1 per page
Multiple schema types
Summaries at the top of sections
Equally important is chunking. LLMs don't quote entire articles; they extract fragments. That means long paragraphs get ignored. Well-structured summaries, tables, and concise explanations are more likely to be pulled in.
Freshness also plays a major role. Research shows that content cited by ChatGPT averages 1,000 days old, while Google's average is 1,400. Perplexity cites content that is often less than a year old. In some verticals, half of its sources are from the current year.
Write like machines read: Use declarative language ("96% of buyers reported satisfaction") rather than opinions ("We think this is good"). Turn subheadings into questions. In numbered lists, put your brand first.
Brand consistency across platforms amplifies these efforts. Maintain identical descriptions on X, LinkedIn, Crunchbase, and GitHub. Some companies see ChatGPT visibility improvements within days of implementing consistent branding.
Implementation playbook: Your step-by-step GEO roadmap
Phase 1: Foundation and discovery
In the first month of your GEO strategy, you'll get a clear picture of your current AI search landscape. This phase is about finding out how AI platforms see and interact with your brand online.
You might discover surprising insights about how AI platforms reference your brand — and how that differs from what you've seen in traditional SEO.
Key activities:
Check your current AI search visibility
Configure your web analytics solution to segment out LLM traffic (for example via a customs segment with a regular expression in Google Analytics)
Find key prompts and map your source landscape
Tool like Peec AI support you throughout these key activities.
Milestones to track:
Complete your prompt set analysis
Map where your brand shows up across AI platforms
Identify which sources get cited most in your industry
Set up your initial reporting
Understanding your source landscape matters because AI platforms don't pull information from just one place. Instead, they gather content from different platforms, each with varying levels of credibility:
Editorial websites (news, industry publications)
Social platforms (Reddit, LinkedIn, YouTube)
Corporate websites (partner directories)
Reference sites (Wikipedia, Crunchbase, G2)
By mapping these sources, you'll understand:
Where AI platforms typically find information in your industry
Which sources carry the most weight in AI-generated answers
Opportunities to improve your brand's visibility
Practical example: B2B SaaS company noticed they weren't showing up in AI answers about cloud security. By targeting YouTube tutorials and LinkedIn thought leadership content, they increased how often their brand appeared in AI answers.
Getting your tracking set up
To track AI traffic properly, you'll need to set up tracking in your analytics platform to identify visits coming from various AI platforms. Work with your analytics team to create a segment that captures traffic from common AI search engines like ChatGPT, Claude, Perplexity, and others.
Figuring out your prompt strategy
Start with what's already working. Export your top Google Search Console queries and turn them into conversational prompts.
Try this approach: Begin with 25 real questions your users might ask AI about your business or industry. Test each prompt multiple times to see what searches the AI actually performs behind the scenes. This shows you optimization opportunities you might have missed.
Making sure LLM crawlers can crawl and render your content
Most AI crawlers struggle with JavaScript. If your main content needs JavaScript to display, you might be invisible to many AI systems.
Check your important pages for JavaScript dependencies and consider server-side rendering where it matters most.
Work with your IT team to make sure AI crawlers can access your content. Many aggressive crawlers might trigger DDoS prevention, so double-check that important bots aren't being blocked.
Phase 2: Optimization and content strategy
Now that you know where you stand, this phase is about turning insights into action. You'll reshape your content to become more AI-friendly and expand your presence on external sites.
Content optimization for AI platforms goes beyond traditional SEO. AI platforms tend to prioritize comprehensive, authoritative content that's easy to extract and reference. This means creating content that's structured, concise, and directly answers questions.
Key activities:
Develop your content optimization approach
Start improving your external presence
Analyze which sources get cited and why
Milestones to track:
Create AI-optimized content guidelines
Develop consistent messaging across platforms
Make technical improvements for better crawling
Start creating content specifically for AI citations
Practical example: A SaaS company might find their technical documentation gets cited more often when they restructure it with clear headings, short summaries, and FAQ schema.
Getting a clear view of your source landscape
Track 25-100 relevant prompts daily for at least a week. Look at which domains and URLs get cited most often. Group them into:
Editorial websites (news, industry publications)
Social platforms (Reddit, LinkedIn, YouTube)
Corporate websites (partner directories)
Reference sites (Wikipedia, Crunchbase, G2)
Something you might not know: Media citations often matter more than traditional backlinks for AI rankings.
Tactics that work for different sources
Editorial websites: Digital PR plus advertorial strategies can work well. We've seen cases where advertorials were cited as legitimate sources by AI. Try targeting commercial content teams, not just editorial.
Social platforms: Each platform needs its own approach. X/Twitter is particularly important for Grok, with almost immediate impact. LinkedIn publishing builds authority for professional topics. For Reddit, a genuine community participation is required. Don't spam, but become part of discussions authentically. In general, consider influencer partnerships targeting relevant keywords.
Corporate websites: Partnership directories and commerce sites (e.g. retail media) can provide structured placement opportunities. If you work with affiliates, consider higher commission strategies to increase coverage.
Reference sites: Complete your profiles thoroughly on sites like Crunchbase and G2. Premium features often improve your citation likelihood. Gather reviews where relevant.
Try Malte's competitor discovery workflow: Regularly check which competitors show up in AI answers for your key topics. When surprised by a competitor's inclusion, look at what sources are driving their mentions and make sure you have proper representation there too.
Phase 3: Advanced implementation
The final phase focuses on refining what works, tracking competitors, and setting up ongoing processes. This is where teams need to collaborate — content, marketing, PR, and technical teams all play a part.
As AI search evolves, visibility requires a smarter approach. Now it is about making your brand show up as an authority across different platforms and content types.
Advanced implementation goes beyond basic tracking. You'll start seeing how AI platforms interpret and reference your brand across different sources and conversations.
Key activities:
Track and measure results continuously
Make your brand messaging consistent everywhere
Watch what competitors are doing (and what's working)
Milestones to track:
Set up a dashboard (like Peec AI) that shows competitor performance
Track sentiment in AI answers about your brand
Create processes that keep optimization going
Get all teams aligned on GEO goals
As AI platforms get smarter, your strategy needs to adapt too. The goal isn't just appearing in answers but also creating a narrative that positions your brand as trustworthy and authoritative across platforms.
See how AI platforms feel about your brand
Build out author profiles with expertise details
Create content that AI can easily reference
Watch for trends in how your brand shows up
Practical example: A financial services company might track brand mentions across different AI platforms to spot sentiment patterns and see how they stack up against competitors.
Track sentiment, not just mentions
Look at how AI platforms talk about your brand compared to competitors. If you notice negative sentiment, find where that information comes from and address it directly.
Build authority beyond your website
Optimize author profiles across platforms with credentials and experience. Include trust elements like previous companies, education, certificates, and awards. Link these profiles together to create a stronger presence.
Focus on making all your content AI-friendly
Don't forget about your non-text content. Make sure your images and videos are accessible to AI crawlers. Create transcripts for video and podcast content. Use descriptive alt text that adds context for both accessibility and AI understanding.
Team and organizational considerations
Most organizations start by expanding SEO team responsibilities to include GEO. This makes sense since the skills overlap quite a bit — understanding search behavior, optimizing content, and handling technical aspects.
Working with your existing teams is crucial for success. Different departments need to understand GEO in ways relevant to their work:
Content teams might need new formatting guidelines that prioritize machine readability
PR teams should understand citation objectives beyond traditional media mentions
Social media teams might need to coordinate on platform-specific strategies
Technical teams need to ensure AI crawlers can access your important content
Getting buy-in across your company
Getting executive support for GEO typically starts with competitive insights, for example, showing real examples where your competitors are visible in AI answers while your brand is missing out. Consider running a small pilot program to demonstrate early wins before scaling your GEO efforts.
Teams working together is more effective than siloed approaches. Regular check-ins help make sure everyone understands how their work contributes to your overall GEO goals.
Measurement framework and next steps
Measuring AI search requires a different approach than traditional SEO. Knowing what to track and how to make sense of the data helps you make smarter decisions about where to focus your efforts.
Setting up proper analytics
Beyond basic traffic tracking, consider creating custom segments within your web analytics solution (like GA4) for each AI platform. Set up goal tracking for AI-driven conversions to understand the true business impact.
For prompt monitoring, build dashboards or use tools like Peec AI that track both brand visibility (mentions in answers) and citation frequency (used as sources). The frequency of monitoring might depend on your resources, but tracking trends over time is more valuable than focusing on daily fluctuations.
Common measurement challenges
AI search is probabilistic by nature, so results might vary between users and sessions.
Attribution between AI and traditional search can be difficult to untangle. While the attribution to ChatGPT can be differentiated from a traditional Google Search, AI Overviews and AI Mode is a lot harder to untangle.
Small sample sizes might lead to misleading conclusions.
Moving forward with your GEO strategy
AI search is still changing, and what works today might need tweaking tomorrow. That's just the nature of new technology. Start by figuring out where you stand today, then focus on the changes that will make the biggest difference.
The most important thing to remember is that both your website optimization and your presence across the web matter. Neither one alone is enough – you need both working together to really succeed with GEO.
Want to see how your brand is performing in AI search engines? Book a demo with our lovely team to discover your current visibility and find your biggest opportunities for improvement.
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