Generative Engine Optimization (GEO) in 2025: The Complete 10-Step Framework for AI Search Visibility
Generative Engine Optimization (GEO) helps brands secure visibility inside AI-generated answers by ensuring their content is discoverable, relevant, and cited by leading models. As AI search becomes the default discovery method across industries, brands must understand how visibility works inside LLM-generated answers. This 10-step framework outlines how to measure citations, optimize content for LLM retrieval, and future-proof your brand for AI-powered search. In 2025, brands can no longer rely on keyword-driven SEO alone. GEO is now essential to secure citations in AI-powered answers and drive greater visibility, revenue, and market share from LLMs.
Search behavior is shifting quickly as systems like ChatGPT and Perplexity redefine how users find information. In this new environment, GEO isn’t optional. It’s how brands ensure they appear, are cited, and trusted inside AI responses.
What is Generative Engine Optimization?
Generative Engine Optimization is the natural evolution of SEO in the world of ChatGPT. GEO focuses on optimizing brand content for AI engines like ChatGPT, Google Gemini, Google AI Mode, and Perplexity. Unlike generative SEO, GEO is a comprehensive strategy to improve AI visibility, answer engine optimization, and citation authority across every customer touchpoint.
At Superlines, we have preferred the term GEO vs AEO (Answer Engine Optimization) but right now the discourse is split between these two terms even though the market is starting to adopt GEO as the main term (depending who you ask from). Regardless of the term, since both are focusing on the same thing, Superlines is still the tool used by the best marketing teams in the world to improve their AI Search visibility.
What are the Key Differences Between GEO and Traditional SEO
Source of answers: AI engines synthesize information while search engines list URLs.
Ranking factors: Citation authority replaces backlinks; structured data outweighs SERP snippets.
User intent: Conversational queries surpass rigid keyword phrases. Measurement: Visibility score becomes more critical than organic ranking. LLMs only cite 2-7 domains on average per response, far fewer than Google's 10 blue links.
How AI Engines Evaluate Content and Citations
AI engines rely on Retrieval-Augmented Generation (RAG), the process of augmenting a generative model with external documents retrieved in real time to produce more accurate answers. This retrieval logic prioritizes relevance, recency, and trust.
This means that ChatGPT, Perplexity, Mistral and other leading models now conduct web searches for most questions instead of relying on their existing training data.
E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness), a core metric from SEO, remains critical for GEO. For example, content with transparent author bios, reputable citations, and consistent updates often outranks shallow material.
You can read Google's View on AEO/GEO and these metrics as Robby Stein, VP of Product explains AI Search and Query Fan-Out in this article.
Why GEO Is Mission-Critical for Brands
Every day, over 1 billion prompts are sent to ChatGPT which is a permanent shift in how customers seek answers.
At Superlines, we analyze thousands of LLM-generated responses monthly — and the brands investing early in GEO are already capturing measurable leads and citations.
More than 71% of Americans already use AI search to research purchases or evaluate brands.
Waiting to adapt means falling behind your competitors. Based on the hundreds of sales calls that we've had from February to october 2025, everyone is trying to figure out how to get ranked in ChatGPT.
Market Adoption and Visibility Statistics
Forrester reports that 89% of B2B buyers have adopted generative AI as a key source of self-guided information throughout their purchasing journey.
Adobe found that 87% of people are more likely to use AI for larger or more complex purchase.
Cost of not taking action in an AI-First Search future
Traffic to ChatGPT is rapidly increasing, with the latest projections by SEO industry veteran Kevin Indig showing ChatGPT surpassing Google traffic by October 2030 in his Linkedin post.
Picture this: seven months from now, your top competitor dominates AI search results while your brand is nowhere to be seen anymore.
Risks to not adopting GEO
Lost share of voice: Competitors capture AI answers and drive significant revenue from an untapped channel.
Brand misrepresentation: Hallucinations and out of date information distort your messaging.
They control the narrative: Do you really want your competitors defining how ChatGPT talks about your brand?
Ten-Step GEO Framework With Benchmarks
Step 1: Align GEO Objectives With Business KPIs
- Map AI visibility to real business impact.
- Start by identifying which business outcomes, such as leads, revenue, or signups are the primary metric to measure success.
- Consider adding a "How did you hear about us" question to your new lead or sign-up form or ask this in your client meetings. This will reveal a good amount of information
Here's some GEO KPIs you can track:
Step 2: Audit Current AI Visibility and Sentiment
- Use a tool like Superlines Answer Engine Insights to benchmark your visibility score, share of voice, and sentiment trends.
- Analyze which AI platforms mention your brand, how often, and in what context.
- Look for both positive and negative sentiment to understand how your brand is perceived by AI engines even though LLMs are most of the time positive or neutral. This audit will reveal your current standing and highlight areas for improvement.
Step 3: Map Real-User Prompts Across the Funnel
- Collect prompts and questions from sales calls, current customers, and social listening on Reddit.
- Document the actual questions and phrases your customers use at each stage of their journey. This helps you understand intent and ensures your content addresses real user needs.
- Mapping prompts across the funnel allows you to optimize for both awareness and conversion queries.
- Superlines helps you estimate LLM search volume based on our large dataset of real user prompts, updated weekly.
Here's an example of how to map prompts to funnel stages:
Step 4: Structure Content for AI-Friendly Summaries
- Incorporate TL;DR blocks, bullet lists, and schema markup (FAQPage, HowTo).
- Use concise, well-organized summaries to make it easy for AI engines to extract key information.
- Structured content increases the likelihood of being cited in AI answers.
- Prioritize clarity and brevity to improve your chances of being referenced.
- Use tables to organize information
- Prioritize comparative articles (Best X Thing, Comparing A to B Solutions )
For a deeper explanation of how this works, see our how to optimize content for Generative AI guide.
Step 5: Optimize Technical Signals and Schema Markup
Prioritize:
- HTTPS everywhere
- Mobile speed under 1.8 seconds
- Complete structured data coverage
- Track AI bot traffic with the help of Superlines server side tracking (Available for Enterprises), you can see exact AI bot traffic to your site over time to identify any gaps. This is technical GEO, just like technical SEO.
- Extra tip: Add LLMs.txt
Technical signals like site speed, mobile optimization, and schema markup help AI engines crawl and understand your content.
Ensure your site is accessible and well-structured for both users and bots. Regularly audit your technical setup to maintain high visibility in AI search results.
For developers: Treat GEO like an API design problem. AI crawlers parse your HTML, build embeddings, and extract structured facts the same way an API client consumes JSON. Clean semantic markup, valid JSON-LD, and consistent entity tagging are your “type safety” for AI readability. If your schema breaks, so does your visibility.
Step 6: Elevate Citation Authority Through Thought Leadership
- Publish original research, whitepapers, and expert commentary.
- Focus on creating unique, data-driven content that positions your brand as an industry authority.
- Earning citations from respected domains increases your trustworthiness in the eyes of AI engines.
- The more authoritative your content, the more likely it is to be referenced in AI-generated answers. This is hard to do and that's exactly why it works.
Benchmark: Earn citations from ≥20 high-authority domains per quarter. Measure this with Superlines’ citation analysis data.
Step 7: Strengthen E-E-A-T and Brand Trust Signals
- Develop detailed author bios, transparent sourcing, and review schemas.
- Regularly audit your site for outdated or low-trust content and remove or update as needed. Hubspot did this recently with great success.
- Trust signals like third-party reviews, certifications, and clear contact information help reinforce your brand's credibility.
- Strong E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) is essential for GEO success.
Step 8: Integrate Multimedia and Data Assets for Rich Answers
- Embed charts, infographics, and video transcripts with descriptive captions, but keep in mind most AI crawlers cannot parse javascript.
- Use a variety of media types to appeal to different AI models and user preferences.
- Well-labeled multimedia assets (alt tags!) can boost your visibility and engagement.
Step 9: Scale Prompt Testing and Conversation Workflows
- Build a library of iterative prompts, monitor their responses, and adapt your prompts to ongoing product and market changes.
- Experiment with different question formats and content structures to see what resonates with AI engines.
Metric: Target 20-30 unique prompts per core topic. Make sure these are run once daily. You're measuring long-term visibility so tracking it over time is key.
Step 10: Benchmark, Report, and Iterate Every Four Months
- Follow a consistent reporting cadence to track visibility, citation authority, and sentiment.
- Build your own reporting, or use something like Superlines to automate this for you.
- Regular benchmarking ensures your GEO strategy adapts to changes in the AI Search landscape.
- Share results internally to communicate the value of optimizing for AI search.
Measuring Success and Iterating
Continuous testing and optimization are essential as engines evolve in addition to using a tool like Superlines to manage your long-term AI visibility.
Core GEO Metrics and Dashboard Design
- Visibility percentage
- Citation count and citation score
- Sentiment index
- Share of voice
Superlines is purpose built for brands to dominate in AI search and supports all of this natively.
Use Superlines' Insights for Competitive Benchmarking Set up competitive asset groups in your category. Export CSV data or use Superlines’ API to do even more granular analysis and pattern identification.
Governance, Budgeting, and Cross-Team Alignment
Based on our hundreds of active users, here's the most common roles for high-performing GEO teams:
Budget Range: Mid-market brands typically invest €50k–€130k annually in all tools and resources that go into creating a high-performing GEO program.
Review results quarterly and share among your marketing team and the broader leadership team.
The Future of GEO and AI Visibility
Expect deeper personalization, more multimodal answers, and real-time data integration across AI engines. Proactively updating your schema and metadata will be critical to staying visible. Emerging tools and open standards for AI citation tracking are rapidly advancing. Superlines helps marketers and enterprises measure, benchmark, and improve their AI visibility more effectively across engines like ChatGPT, Perplexity, Gemini, and Mistral.
To see how these principles connect in practice, explore What Are the Key Metrics for Measuring Success in Generative Search.
GEO is how brands stay visible when answers replace search results.
See how your brand performs across AI engines. Get a free demo of Superlines and start measuring your AI visibility today!