Last week, I read Giulia Panozzo’s article about rethinking audience targeting in the age of signal loss. I also read Harry Clarkson-Bennett’s article on creating non-product content. Then I read Matt G. Southern’s article about Google’s new AI search guide. Officially, AEO and GEO are still called SEO.
As I read these together, I kept hearing the same message that the basics apply.
So I went back to 7 Steps to Building a High-Impact Digital PR Campaign, which I wrote on August 11, 2022, two and a half months before OpenAI released ChatGPT.
borrowed from Aristotle
In my August 2022 article, I made it clear that the framework was not mine. This honor goes to Aristotle, who articulated the “elements of the situation” in his Nicomachean Ethics in the 4th century BC. who, what, when, where, why, how, and by what means. All I did was apply them to 21st century SEO PR. After 42 months and one AI revolution, the question worth asking is whether the seven steps are still relevant.
that’s right. But with each step, what was needed changed.
Who is the target audience?
This step in August 2022 was mainly about demographics and keyword personas. However, signal loss is not a new problem; it is a recurring problem. In 2013, Google’s move to encrypted search made “keyword not served” a major issue, stripping practitioners of the keyword-level analytics data they relied on to understand who was actually finding their content and why. we adapted. Other signals were also found.
Now there is another layer to this challenge. The data hole in Google Analytics 4 is real, and I’ve written about it in detail. The REM framework Panozzo describes deals with what happens when the data you rely on to define your audience becomes unreliable or incomplete. Her answer and mine are the same. It’s about getting closer to real people, not proxy data. Signal loss is inconvenient to the definition of a delayed viewer. This presents an opportunity for practitioners who are disciplined enough to collect first-party signals through direct observation.
What are their news search intentions?
Google’s new AI search guide published this week makes clear what has been implicit for years. AEO and GEO are not separate fields from SEO. These are SEO and apply to generative AI features. The underlying question is always the same. What are people actually trying to understand or achieve when they search?
What has changed is the form of answers they now expect. AI Overview and AI Mode show you the answer first. Quotes come second, if at all. For digital PR, this means the question is no longer just “Can I rank for this?” But “Can I get citations with the answers Google generates?”
The question of intentionality remains. The answer format has changed accordingly.
When do they conduct news searches?
Although this step is relatively stable, the tools for measuring temporal search patterns have improved significantly. Clarkson-Bennett’s article makes a good practical point. Google Trends data for terms like “family vacation” spikes every January, showing near-perfect consistency over five years. Seasonal patterns in news search intent are more persistent than most experts assume, and AI summaries are not disrupting the underlying rhythm, only the interfaces through which people receive answers.
Where do you search for news?
This is where I have made the most visible changes in 42 months. In August 2022, “where” meant Google Search, Google News, YouTube, and social platforms. Currently, the answer includes Google’s own ChatGPT, Perplexity, Claude, Gemini, and AI modes.
Similar web traffic data from April 2026 speaks for itself. ChatGPT records 5.5 billion monthly visits worldwide, while Google still leads with 84.8 billion monthly visits. In other words, the “places” of information search are truly fragmented in ways that matter to distribution strategies.
News articles that once gained visibility only through traditional Google searches are now reaching a smaller percentage of the overall information-seeking audience than in 2022. The PR question “Where will this land?” requires a broader answer.
Why is your news important to your target audience?
This is the step that Amit Singhal’s 23 Panda Questions from 2011 actually covered. “Does the article provide original content or information, original reporting, original research, or original analysis?” This question appeared in Google’s quality guidance 15 years ago. This week, it will be published in an updated form in Google’s new AI Search Guide.
Clarkson-Bennett’s article makes the same point through the concept of information acquisition. This patent is frequently cited by Google around the world, with recent updates. This patent rewards documents that estimate effort and add things to the index that don’t already exist. Problems with product content are not new. The Panda update was Google’s first systematic attempt to solve it. The AI era is the latest and most technologically sophisticated iteration of the same enforcement mechanism.
Why is your news important? Because it is original, specific, and cannot be duplicated by pattern recognition across existing things.
How can you change your heart, mind, and actions?
The panda question that applies here is: “Does the article have the quality you would expect to see referenced in a magazine, encyclopedia, or book?” That standard has not lowered even in the AI era. If anything, it’s more of a citation standard than just a ranking.
AI-generated summaries cite sources that convey authority, specificity, and genuine expertise. The PR content most likely to earn that citation is the content that passed Singhal’s 23 Questions in 2011 and still passes today. Original research. Primary sources. Certain claims based on verifiable data.
The means of changing one’s mind have not fundamentally changed. What has changed is that your audience can now receive your arguments through an AI intermediary instead of directly. The quality standards that intermediaries need to survive are high, not low.
How can I measure results?
This is where the most authentic new work was created over the course of 42 months. In August 2022, measurement meant organic traffic, impressions, and backlinks. They now want to track the frequency of citations in AI-generated answers, monitor brand mentions in AI summaries, and separate AI assistant referral traffic from traditional organic. GA4 added that functionality last week, adding new default channel groups for recognized chatbot referrers like ChatGPT and Gemini.
The measurement question that Aristotle didn’t need to answer was, “How do we know if we’re winning when our viewers don’t click through?” Citation share of statements in AI answers is becoming the new ranking position. It’s measurable. The tools are early and incomplete. However, the principles are the same as when SEO measurement began. That means identifying the signals that predict whether the right users are finding your content and tracking them consistently.
Aristotle’s correct judgment
Google’s new documentation states that AEO and GEO are still SEO. What it means is that the question under the term is always the same. Who are you trying to reach? What do they need to understand? How do you demonstrate to the systems your content will appear on that you truly address their needs?
Aristotle’s 7 Situational Elements survived for 23 centuries until I applied them to digital PR in 2022. These will also survive AI Mode, AI Overview, and whatever Google has to offer next.
The basics apply.
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