Changing Your Approach: Answer vs Search Optimization in B2B

As AI-powered answer engines like ChatGPT, Perplexity, and Google's AI Overviews take over search behavior, marketers are facing new challenges. In particular, your content needs to work for AI systems that generate instant answers and aren't just made for readers scrolling through links.

This move toward Answer Engine Optimization (AEO) — one of the latest in a string of new AI search terms — represents a change in how content gets discovered and consumed online. Traditional SEO focuses on ranking web pages in search engine results pages (SERPs). But AEO targets the AI systems that generate those instant answers to user queries.

And the stakes are high. One report found that AI tools, like ChatGPT and Perplexity, accounted for around 5.6 % of US desktop search traffic in mid‑2025 — more than double the share from mid‑2024.

When an AI provides a complete answer directly, users may never click through to your website. This fundamentally changes the traffic and conversion models that marketers have relied on. Understanding the difference between these approaches — and how to optimize for both — has become essential for staying visible amid AI search.

Search success goes from rankings to answers

Traditional SEO has always been about keyword research tools and climbing the rankings ladder. Marketers optimize title tags, build backlinks, target keywords, and structure content to appear on page one of Google. The goal has always been to get users to click through to your site from the search results.

AEO operates on entirely different principles. According to Advanced Web Rankings Google AI Overview Tool, 60% of SERPs populate with an AI overview. And over 80% of those search queries have informational search intent behind them (55% have commercial intent).

So, instead of competing for a position on page one, you're optimizing to be the source that AI systems cite when generating answers. This means structuring content so that language models can easily extract, understand, and synthesize your information into coherent responses.

As a result, the goal changes from "How do I rank for this keyword?" to "How do I become the authoritative source that AI references?"

The implications extend beyond visibility. With AEO, your content might reach users without them ever visiting your website. AI answer engines pull information from multiple sources to create comprehensive responses, often citing sources but not requiring clicks.

This creates a world wherein your content can be highly influential and widely seen, but generate zero direct traffic. Your brand recognition grows, but your traditional metrics don't capture it.

What changes in your content strategy

The tactical differences between traditional SEO and AEO require rethinking how you create and structure content. Traditional SEO rewards comprehensive, keyword-rich pages with strong technical foundations and authoritative backlinks. AEO demands content that’s easily parseable, factually precise, and structured for AI comprehension.

Structured data takes on new importance. Schema markup — the code that helps search engines understand your content’s context — shifts from a nice-to-have SEO enhancement to a critical AEO requirement. AI systems rely heavily on structured data to understand context, relationships, and factual accuracy. Implementing detailed schema for articles, FAQs, how-tos, and product pages helps ensure AI engines can accurately interpret and cite your content.

But formatting matters just as much as structure. While traditional SEO favors long-form, exploratory content, AEO rewards concise, direct answers paired with supporting detail. Clear, definitive answers to specific questions — formatted in ways AI models can easily extract — are far more likely to be cited.

That means reworking your content for extractability:

• Use schema markup for every core page type.
• Convert key sections into Q&A format to make intent and structure obvious.
• Write clear, complete sentences in subject-verb-object structure to support summarization.
• Include structured summaries and lists like tables, bullets, and side-by-side comparisons.
• Cite sources inline with recent, trustworthy links to build credibility with AI engines.
• Balance length and clarity, using one- to two-sentence summaries followed by longer explanations.
• Refresh high-performing pages quarterly to stay accurate and AI-relevant.

The goal is to make your expertise machine-readable without losing your human voice.

Measurement changes too. Traditional SEO metrics like rankings, organic traffic, and click-through rates don’t capture AEO success.

Instead, marketers might track brand mentions in AI-generated answers, citation frequency across engines, and whether their content appears in AI responses — even when users don’t click through.

This shift demands new monitoring tools and a broader definition of content ROI.

Bottom line: Build the foundation for a hybrid search environment

Search behavior is fragmenting across traditional search engines, AI chatbots, voice assistants, and vertical answer engines. Users still click through to websites for detailed information, transactions, and exploration. But they also increasingly rely on AI-generated answers for quick facts and guidance. So marketers need traditional SEO and AEO.

The winning strategy involves creating content that serves both purposes. Start with the fundamentals: authoritative, accurate, well-researched content on topics relevant to your audience. Then layer on both traditional SEO elements (keyword optimization, technical SEO, backlink strategy) and AEO elements (structured data, clear question-answer formats, factual precision, easy extractability).

Test your content against both frameworks. Does it rank well in traditional search? Does it appear when you ask AI systems questions in your domain? Are you cited as a source?

This dual-optimization approach ensures visibility regardless of how users choose to search, positioning your brand for whatever search evolution comes next. Right now, search isn't either/or but both/and. Marketers who take this hybrid approach can maintain visibility as search evolves, whether users type queries into Google or ask ChatGPT for recommendations.