What matters to AI is the reason for being cited.

The traditional search experience was based on a very simple structure. Search engines listed results, and users clicked on one. The goal of SEO in this process was clear: to outperform competitors and generate more clicks.

However, in an AI-powered search environment, this premise is shattered. Search results pages are becoming increasingly narrow, and AI generates answers directly to questions. Users no longer worry about "where to click." Instead, they simply determine "is this answer sufficient?" This shift changes the very purpose of SEO.

The crucial question now is: "Are user behavior metrics still relevant for SEO?" The bottom line is that their significance hasn't disappeared. They've simply evolved from direct ranking signals to indirect signals that AI uses to determine trustworthy sources.

A key shift in the AEO landscape: Actions are now attributed to the "source," not the "page."

In an AI-powered search environment, search engines no longer simply compare individual pages. Instead, they determine "which source is qualified to answer this question." User behavior metrics then function as a source-level trust accumulation data, not page-level performance data.

In the past, CTR, dwell time, and bounce rate were indicators of individual page performance, but now these indicators are accumulated and serve as criteria for determining the relevance of a source to a single question.

• Did people actually choose this domain?
• Has this information repeatedly led to user satisfaction?
• Is this explanation method suitable for AI reconstruction?

In other words, behavioral indicators are no longer “scores for ranking,” but are reinterpreted as trust data that determines “whether AI can cite this information.”

Five User Behavior Metrics Reinterpreted from an AEO Perspective

1. Click-through rate (CTR): 'Selected sentence type', not the number of clicks

In an AI search environment, users don't need to click. However, this doesn't mean CTR is completely meaningless. In fact, CTR becomes important pattern data for AI to learn.

If we analyze the pages with high CTR, we find that they have something in common.

• A title that immediately reveals the core of the question
• Sentence structure that conveys the main point without unnecessary formalities
• A clear promise with predictable results

AI learns from this: "This type of answer is selected for this question." CTR is no longer simply a click-through rate; it's indirect data that trains AI's language selection model.

2. Dwell Time: Not the time spent, but the moment of complete understanding.

Dwell time has long been a controversial metric in SEO. Is long better, or is short worse? In the AEO environment, this question becomes irrelevant. AI doesn't interpret time directly. Instead, it infers:

• Does the user understand without further explanation?
• Is the answer complete without unnecessary exploration?

A short but significant dwell time can actually be a positive sign, as it indicates that "this page provided the answer to the question in one go." From an AEO perspective, dwell time is interpreted as an indicator of information density and explanatory completeness.

3. Bounce Rate: Not Failure, but the "Result of Fulfilling Intentions"

In traditional SEO, bounce rates are often treated as a negative indicator. However, in the AEO environment, interpretation becomes much more sophisticated. AI considers more than just the fact that a user has left a page; it considers the context surrounding the event.

• No further searches after leaving
• Are similar questions repeated?

If there's a rapid dropout and no re-search, it's likely interpreted as providing a perfect answer. In other words, the dropout rate in an AEO environment isn't a failure indicator, but rather a signal that determines whether the inquiry has been closed.

4. Internal Movement: The Existence of an Explanatory System, Not Fragmentary Information

AI prefers connected knowledge structures over single pieces of information. If a user moves seamlessly from one page to the next, it's evidence that the site doesn't offer a fragmented approach to the topic.

Definition → Reason → Case → Limitation Concept → Application → Cautions

Internal movement along this flow conveys an important message to the AI: "This site can systematically explain the topic." This significantly increases the likelihood of being selected as a source in an AEO environment.

5. Revisit Rate: "Reference Value," Not Brand

Revisit rates aren't simply a matter of brand loyalty. In AI search environments, they become a key indicator of whether a source is being repeatedly referenced.

• Does the same domain appear repeatedly in similar questions?
• Is it continuously used as a secondary source when generating AI responses?

Revisit rates are a measure of reference reliability from an AI perspective. For AI, information used repeatedly is a safer choice than information used once.

Technical Premise: Behavioral Indicators Only Work When Structured Right

No matter how positive the user response, if the structure is incomprehensible to AI, it will not be cited. For behavioral indicators to be effective in an AEO environment, the following conditions must be met.

• Clear subheadings and paragraph divisions
• Question-answer-oriented sentence structure
• Definitions and explanations without duplication
• Fast loading speed and stable server response
• Schema-based structured data

Behavioral indicators function as meaningful trust signals only under this premise.

Iropke's Perspective: SEO is a "Data archive" in the AEO Era

We don't view AEO as a temporary trend. What AI seeks to learn is how people make choices and understand them. And those choices always come from well-organized explanations, clear structures, and trustworthy attitudes. SEO in the AEO environment can be redefined this way.

Designing content that is explainable to both people and AI, not just to conquer search engines.

User behavior metrics remain important, but they are no longer just a means to boost search rankings; they are now the criteria by which AI determines whether or not to cite a post.