The way users search for information has changed profoundly and structurally. We've moved from searches based on isolated keywords to much more natural, longer, and contextual queries, where the user not only asks questions but also engages in a dialogue with the search engine. Today, searches include nuance, conditions, and follow-up: the user formulates an initial question, receives an answer, and then refines it. This behavior defines the conversational search and marks a turning point in the way SEO is understood, which stops focusing exclusively on terms to focus on solving real needs with precision and depth.
This shift is further compounded by the evolution of search engines toward AI-powered experiences, such as AI Overviews and AI Mode. In these environments, Google doesn't simply display links; it synthesizes complete answers and selects sources it deems reliable to support them. This means that content no longer competes solely for a ranking position, but rather to be understood, summarized, and cited. Google It makes this clear in its official documentation: content must be accessible, well-structured, and useful. In this new scenario, optimizing for conversational search becomes a critical factor for maintaining organic visibility and relevance.
Traditional SEO remains an essential foundation, but it's no longer enough on its own. To compete in search engine results and generative search, brands must adapt their content strategy and website architecture. At ARTIC, we approach this change from two complementary perspectives. Answer Engine Optimization (AEO) It focuses on turning each piece of content into the best possible answer to a specific question. Generative Engine Optimization (GEO) The goal is for that content to have a presence, mentions, and citations in AI-generated responses. Both approaches are integrated within an AI SEO strategy designed for conversational search environments.
What is conversational search and why is it changing SEO?
The conversational search It is based on queries formulated as natural, complete, and contextual questions. Users no longer search for "CRM software," but rather ask much more specific questions such as "which CRM is best for a B2B company with a small sales team" or "which CRM integrates best with HubSpot and has good support in Spain." This type of search reveals a clearer and more advanced intent, and demands content capable of interpreting that context and providing precise answers.
This change forces us to rethink how content is planned. It's no longer enough to rank for a single keyword; it's necessary to address the full range of questions, objections, and scenarios surrounding a given intent. conversational search It opens the door to more useful, deeper content that is better aligned with the user's actual decision-making process, resulting in greater trust and better conversion.
How to move from keywords to real conversational search intent
Optimize for conversational search This implies a change in mindset. Beyond search volume, it's crucial to understand what problem the user is trying to solve, what context they're in, and how their decision-making process evolves. In B2B environments, this process typically progresses through very clear phases, each of which generates different questions.
Examples of conversational intentions in B2B environments
- Exploration phase, where the user tries to understand their problem and possible solutions.
Frequently asked questions:
“What kind of solution do I need for this problem?”
“Are there any alternatives to what I’m using now?” - Validation phase, in which it evaluates whether an option fits its context.
Frequently asked questions:
“"Does it integrate with my current tools?"”
“"Is it suitable for a company of my size or sector?"” - Decision phase, focused on scope and cost.
Frequently asked questions:
“How much does it really cost and what does it include?”
“What is the difference between this option and the competition?” - Risk reduction phase, where she seeks security before deciding.
Frequently asked questions:
“"What mistakes do other companies make when choosing this?"”
“"What problems might I encounter in the medium term?"”
Mapping these questions by funnel stage and professional profile allows for building a web architecture aligned with the conversational search and define an editorial calendar with real impact. This approach doesn't replace traditional SEO, but rather reinforces it, relying on a solid foundation of architecture, internal linking, and technical performance.
Why answer-first content is key for AEO and conversational search
To stand out in conversational search, The content must prioritize the answer from the outset. Search engines and artificial intelligence systems need to quickly identify the main solution a page offers and in what context it applies. For this reason, content designed with an answer-first approach works particularly well for both users and AI systems.
How to structure content geared towards AEO
- Begin with a clear and direct answer to the main question
- Example:
- Main question: “Does SEO work for B2B companies?”
- Initial direct answer: “Yes, SEO works in B2B when it focuses on business intent and not just traffic volume, prioritizing content that attracts decision-makers and not just informational users.”
- Further development: Explanation of why B2B SEO requires more depth, how long sales cycles influence it, and what type of content generates qualified leads.
- Include real-world examples or application scenarios
For example: how does an SEO strategy change when the user searches for "best SEO agency" versus "which SEO agency is right for my industry"?. - Add frequently asked questions aligned with search intent
Questions like:
“"Does it work the same in B2B as in B2C?"”
“"Does it replace traditional SEO?"”
This format improves the user experience and increases the chances of appearing in featured snippets, direct answers, and generative results, reinforcing visibility in conversational searches.
How to make your content citable in generative search results (GEO)
Generative search engines not only index information, but also synthesize it and attribute it to sources they consider reliable. To increase the likelihood of being cited in answers related to conversational search, The content must be clear, specific, and demonstrable.
Elements that increase the citability of the content
- Precise and unambiguous definitions
- A clear explanation of when a solution is appropriate and when it is not.
- Honest comparisons that include pros, cons, and nuances
- Own data, methodology or verifiable experience
- Visible authorship and clear update dates
For example, it's not the same to say "this works best" as it is to explain "this works best in companies with X structure, but it's not recommended if you have Y limitation." This kind of nuance increases credibility and the likelihood of being cited.
How to structure SEO and internal linking for conversational search
Although the context evolves, the technical foundation remains essential. A good structure makes it easier for search engines and artificial intelligence to understand the content and its relationship to the rest of the site. Headlines phrased as questions, well-developed paragraphs, and contextual internal linking all help the conversational search function as a logical path.
Good structural practices to consider
- Use H2 and H3 headings that reflect actual user questions
- Develop paragraphs with context and examples, avoiding superficial answers.
- Use lists and tables only when they provide real clarity
- Link internally to content that expands the conversation
How to measure a conversational search strategy
In strategies focused on conversational search, Measurement must go beyond traditional rankings. It's crucial to analyze what types of queries trigger generative responses and how users interact with the content.
Key metrics for evaluating performance
- Queries that generate featured snippets or generative responses
- Evolution of CTR when AI Overviews appear
- Content that assists conversions even if it's not the final click
How ARTIC helps you master conversational search
Adapting to conversational search isn't just about adding FAQs without a clear strategy. It requires understanding the user, redesigning content architecture, creating pieces geared toward real answers, and continuously measuring their impact. At ARTIC, we help brands implement this strategy by combining traditional SEO, AEO, and GEO to compete successfully in an increasingly conversational and generative search environment.
