How to Improve Brand Visibility in AI Responses: What SEO, GEO and AEO Have to Do With It

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If you still think SEO is only about appearing on Google, this article will be a good wake-up call.

What is changing is not the optimization logic — it’s who asks the questions and where the answers appear. ChatGPT, Perplexity, Claude, Gemini and Copilot already answer questions that, until recently, only reached Google. And when one of these AIs responds “what is the best B2B prospecting platform for SMBs,” it cites a few brands and ignores the majority.

The question is not whether your company will appear in those responses. It’s what you need to do for it to appear.

Why Organic Traffic Is Changing and What It Means for B2B Companies

For years, the logic was simple: appear on Google, appear to the customer. Page 1, position 1, goal achieved.

That logic still works. But it is becoming incomplete.

According to 2024 data from Sparktoro and Datos, approximately 58.5% of Google searches end without any click. The user reads the answer within the result itself — via AI Overview, featured snippet or Knowledge Panel — and leaves. For informational B2B searches, where the decision-maker is researching a problem or solution category, that number is even higher.

At the same time, the volume of questions asked directly to generative AIs grows month by month. ChatGPT registered more than 3.5 billion searches in December 2024, according to Datos.live. Perplexity grew 858% in search volume throughout 2024. Gemini is integrated into the Google ecosystem and Workspace. Copilot is in Windows and Edge.

The B2B decision-maker who used to open 10 comparison tabs now asks an AI: “What is the best prospecting automation platform for B2B sales teams?” And receives a response with 3 to 5 cited brands, context about each one, and in some cases a direct link to the demo page.

The market is looking at this with increasing attention, but still with a lot of confusion about what to do. Most marketing teams are treating SEO, GEO and AEO as if they were three separate strategies competing for budget and priority. In practice, the three are part of the same visibility system that needs to work together.

What Traditional SEO No Longer Captures, and Where GEO and AEO Come In

Before getting into tactics, it is worth aligning the vocabulary — because the three terms are being used in very different ways depending on who is speaking.

SEO (Search Engine Optimization) is the oldest of the three disciplines. Optimization for traditional search engines, primarily Google and Bing. It involves keywords, domain authority, backlinks, page speed, technical structure and search intent. SEO remains relevant and remains the foundation. But it was built for a world where the user clicks on links and arrives at your site.

GEO (Generative Engine Optimization) is optimization for generative search engines — the AIs that generate natural language responses instead of lists of links. ChatGPT, Perplexity, Claude, Gemini and Copilot are generative engines. GEO is about making your brand’s content be used as a source when these AIs build responses. It is not about appearing in a ranking. It is about being cited as a reliable reference in the middle of a prose response.

AEO (Answer Engine Optimization) is optimization for answer engines, focusing on structuring content so it answers questions directly and completely enough to be extracted by any system seeking answers — whether Google’s AI Overview, Perplexity, or a mobile voice assistant. AEO is largely about structural clarity: content needs explicit questions, direct answers, verifiable data and language that a system can interpret without ambiguity.

What Changes in Practice for a B2B Company

For a B2B company that wants to attract new clients through content, the implications are concrete.

SEO still resolves the top of the funnel on Google, especially for transactional searches with high purchase intent, such as “B2B prospecting platform with AI pricing” or “CRM for SMB sales teams.” In these cases, the user wants to click, evaluate and buy. Classic SEO is still the most effective channel.

GEO resolves the reputation and reference layer. When the decision-maker asks ChatGPT “what are the best B2B sales automation tools,” they do not want a list of links. They want a well-founded opinion from a source that has already processed a lot of content on the subject. If AVPIA appears cited in that response with positive and specific context, this is equivalent to a recommendation from a trusted colleague — and that recommendation happens without the decision-maker ever having visited the AVPIA website before.

AEO resolves the clarity and extraction layer. A blog article with a clear question in the H2 and a direct answer in the first two paragraphs has a much greater chance of being extracted by any AI as a source of response than a 3,000-word article with a long introduction and conclusion at the end. Content structure is what separates content that AIs use from content they ignore.

The research Generative Engine Optimization by Aggarwal et al. (2023) from Columbia University identified that citations of external sources, verifiable statistics and persuasive language are the three factors that most increase a brand’s presence in AI-generated responses. In other words: content that seems reliable to a human tends to also seem reliable to the AI that will cite it.

What Question Is Your Marketing Team Still Not Asking?

If ChatGPT received a question today about the category in which your company competes, what would it say about your brand?

This is not a rhetorical question. It is a question you can test right now, by opening ChatGPT, Perplexity or Gemini and typing something like: “What are the best [your product category] for [your customer profile]?”

The result will be revealing. Some brands will appear with rich context, specific use cases and a clear positioning. Others will be completely ignored. And some will appear with an incorrect context — which the AI constructed from imprecise or outdated content that was available about them.

This question matters because generative AIs do not search for information in real time in most situations. They were trained on a content corpus that has a cutoff date. What appears in today’s responses reflects what was published, indexed and well-structured months or years ago. This means that your brand’s absence from AI responses may be the result of a content gap that existed in the past — and that continues to influence the present.

How a B2B Company Disappears from AI Responses Without Realizing It

A B2B software company with a solid product, established client base and good market reputation decides to understand why it is not generating leads through organic content at the same rate as competitors.

The SEO analysis looks good: domain with reasonable authority, indexed articles, some keywords positioned on the first page. But organic traffic is stagnant and the leads that arrive via content are few and low quality.

When they test the main AIs with questions about the category, they discover the following: competitors appear cited frequently, with specific context about use cases and benefits. The company itself appears in fewer than 20% of responses, almost always without relevant context — only the name mentioned in a generic list.

The diagnosis is clear when analyzed calmly.

The company’s blog has articles about product features, releases and version updates. Useful content for current clients, but which does not answer the questions decision-makers ask before buying. When ChatGPT goes to build a response about “how to choose a B2B sales automation platform,” it finds no content from this company that answers that question directly and completely.

Competitors, on the other hand, published guides, comparisons, FAQ articles and content that structures the category rather than just describing the product. That content was trained into the AIs and becomes a reference source when questions arrive.

The problem was not the product. It was the content strategy built for Google in 2018, not for the AIs of 2025.

This pattern appears in many B2B companies that invested in traditional SEO for years without updating the strategy for an environment where content needs to answer questions, not just rank for keywords. The article on generative AI applied to B2B content marketing explores how AIs are changing what content needs to do to generate results.

What to Do to Improve Brand Visibility in AI Responses

Before getting into the AVPIA solution, it is worth detailing what a B2B company needs to do from a content and strategy perspective to build presence in AIs.

Producing Content That Answers Real Buying Journey Questions

Generative AIs are trained on content that answers questions. Blog articles that describe product features do not answer questions from decision-makers in evaluation.

Articles that answer “how to choose a platform for X,” “what is the difference between X and Y,” “what are the most common mistakes when implementing X” are the ones AIs use as sources.

The question mapping should cover the entire journey: problem awareness questions, solution evaluation questions and supplier comparison questions. Each of these questions deserves a structured article with a direct answer, verifiable data and specific context.

Structuring Content for Extraction

Content well-structured for AEO has some specific characteristics: H2s and H3s formulated as real questions, direct answer blocks immediately below each section title, data with source and link, FAQ at the end of the article and unambiguous language.

According to a 2024 Search Engine Land study, content with a question-and-answer structure is 2.7 times more likely to be extracted by Google’s AI Overview than content in traditional article format. Structure is not a technical detail. It is what determines whether the content will appear or not.

Building External Citations and References

AIs give more weight to brands that appear cited in multiple different sources. Content in specialized publications, interviews, participation in market research and presence in independent comparisons build the external reputation that AIs use to validate whether a brand deserves to be recommended.

Maintaining Information Consistency Across Channels

If the website says one thing about the product, LinkedIn says another and press articles say a third, the AI will have difficulty building a coherent brand profile. Message consistency across all channels where the company has a presence is one of the factors that most influences the quality of the context with which the brand appears in AI responses.

Updating Content Regularly

Language models have training cutoff dates, but AIs that operate with real-time search — such as Perplexity and ChatGPT with active browsing — seek recent information to complement. Content updated regularly, with visible dates and relevant current information, has an advantage over content that has been stagnant for years.

How AVPIA Helps B2B Companies Build Visibility That AI Recommends

The AVPIA Platform and the AVPIA Virtual SDR operate in a context that connects directly to the topic of AI visibility: outbound prospecting that uses AI to identify, qualify and approach leads.

When a B2B company builds visibility in AIs, it changes the nature of the lead that arrives. The decision-maker who was recommended by ChatGPT arrives with context about the brand, with a prior perception of credibility and with a different disposition for the initial conversation. They do not need to be convinced that the company exists or that the problem it solves is real. They have already gone through that stage before arriving.

The AVPIA Virtual SDR receives that lead at a different stage. Qualification is faster because the lead arrives with context. The conversation goes deeper from the first contact because the prospect already has a formed perception. And the sales cycle tends to be shorter because it starts from a foundation of trust that the content built before the commercial approach.

For B2B companies that are building this strategy, the AVPIA Platform offers the prospecting and qualification infrastructure that captures the leads generated by organic visibility and works them with the same consistency that the content built. It does not make sense to invest in GEO and AEO to generate awareness if the sales operation cannot convert that awareness into pipeline with speed.

Want to see how the platform works for the lead profile that your content strategy is generating? Schedule a demo and understand how prospecting and visibility work as an integrated system.

Why Visibility in AI Is a Long-Term Asset, Not a Short-Term Tactic

There is a temptation to treat GEO and AEO as yet another series of technical tricks to game the algorithm. Add FAQ at the end of the article, put a direct answer in the first paragraph, mention a few statistics with links. Done, next.

That approach does not work for a simple reason: AIs learn from the total corpus of what is published about a brand, not from a single well-structured article.

Visibility in AI is built over time, from a consistent set of content that positions the brand as a reference on a specific topic. A company that publishes 40 articles about B2B prospecting with AI, with verifiable data, its own perspective and clear structure, will appear in AI responses much more frequently than a company that published one definitive guide and stopped.

The compound effect here is real. Each well-structured article increases the probability of citation. Each citation in an external outlet increases perceived authority. Each verifiable data point with source strengthens credibility. And this set, built over 12 to 24 months, creates a presence in AIs that is much harder to replicate quickly than an SEO position.

According to the Content Marketing Institute’s 2024 B2B Content Marketing report, 72% of high-performance B2B marketing teams report that publication consistency is more determinant for results than the isolated quality of a single piece of content. Frequency creates the corpus. The corpus creates the reference. The reference creates the citation.

For B2B companies that are starting this construction now, the good news is that most competitors are still optimizing for Google 2020. The space in AI responses still has far less competition than the space in Google’s top positions. The window of opportunity exists, but it will not last forever.

The article on B2B demand generation strategy in 2025 shows how lead attraction strategies are evolving and why content structured for AI is already changing the demand generation metrics of companies that got ahead.

How to Measure Whether Your GEO Strategy Is Working

Measuring AI visibility is more complex than measuring position on Google. Some metrics that are already possible to track:

Citation Frequency in Major AI Systems

Periodically testing the most relevant buying journey questions from your customer in ChatGPT, Perplexity, Claude and Gemini and documenting how often and with what context the brand appears. This manual test can be done monthly and serves as a trend indicator.

Traffic Referred by AI Systems

Tools like Google Analytics 4 already allow you to identify sessions originating from domains like chat.openai.com, perplexity.ai and gemini.google.com. This number is still small for most companies, but growing rapidly and worth monitoring.

Quality of Leads That Arrive with Prior Context

Leads that arrive mentioning that they “saw the company recommended by ChatGPT” or that “Perplexity suggested evaluating” generally have a shorter sales cycle and higher conversion rate. Recording this data in the CRM creates a line of evidence about the impact of the GEO strategy.

Volume of backlinks from content that cites your brand as a reference is also a useful proxy. SEO tools like Ahrefs and Semrush already allow you to monitor mentions and backlinks. Growth in this number, especially from specialized outlets, indicates that the content is building external authority that AIs also capture.

Final Reflection

SEO remains relevant. GEO and AEO did not come to replace it. They came to make it insufficient when used alone.

The B2B company that wants to attract new clients and be recommended by AIs needs to build content that answers real buying journey questions, with clear structure, verifiable data and publication consistency over time. It is not a list of technical tricks. It is a content strategy that respects both the human reader and the system that will interpret that content.

The window of opportunity in AI responses is still open. And unlike SEO, where the top positions were secured years ago by brands with high-authority domains, the space in ChatGPT and Perplexity responses is still being contested by those who publish relevant content consistently, regardless of domain size.

That is the real opportunity. And it does not require an enterprise budget. It requires strategy, criteria and consistency.