Last week I read Giulia Panozzo’s article on rethinking audience targeting in the age of signal loss. I also read Harry Clarkson-Bennett’s article on create non-commercial content. And then I read Matt G. Southern’s article on Google’s new AI research guide officially calls AEO and GEO “always SEO.”
Reading them together, I always heard the same message: the basic things apply.
And that took me back to something I wrote on August 11, 2022 – two and a half months before OpenAI released ChatGPT – “7 Steps to Creating a High-Impact Digital PR Campaign“,
What I borrowed from Aristotle
In my August 2022 article, I revealed that the framework was not mine. Honor goes to Aristotle, who articulated his “elements of circumstance” in the Nicomachean Ethics in the 4th century BCE. Who, what, when, where, why, in what way and by what means. All I did was apply them to SEO PR in the 21st century. The question worth asking now, 42 months and an AI revolution later, is whether the seven steps are still valid.
They do it. But the requirements of each step have changed.
Who are your target audiences?
As of August 2022, this step was primarily about keyword demographics and personas. But signal loss is not a new problem: it is a recurring problem. In 2013, Google’s move to encrypted search made “keyword not provided“a major problem, removing the keyword-level analytics data that practitioners relied on to understand who was actually finding their content and why. We adapted. We found other signals.
Today, the challenge takes on another dimension. THE data holes in Google Analytics 4 are real – I have written about them at length. The Panozzo REM Framework describes what to do when the data you relied on to define your audience has become unreliable or incomplete. His answer, and mine, is the same: get closer to real people rather than proxy data. Loss of signal is a disadvantage for lazy audience definition. This is an opportunity for sufficiently disciplined practitioners to gather signals first-hand through direct observation.
What is their news search intent?
Google’s new AI research guide, released this week, makes explicit something that has been implicit for years. AEO and GEO are not separate disciplines of SEO. These are SEO, applied to generative AI functionalities. The underlying question has always been the same: what is a person actually trying to understand or accomplish when they search?
What has changed is the format of the response they now expect. In AI Previews and AI Mode, the answer comes first. The quote comes second, if at all. For digital PR, this means the question is no longer simply “can we rank for this?” but “can we earn a citation in the answer generated by Google?»
The question of intention remains. The response format has changed around.
When do they search for news?
This stage is relatively stable, although the tools for measuring temporal search models have improved considerably. Clarkson-Bennett’s article illustrates the practical point well: Google Trends data for terms like “family vacation” shows spikes every January with almost perfect consistency over five years. Seasonal patterns in news search intentions are more durable than most practitioners realize, and AI insights have not disrupted the underlying rhythms, only the interface through which people receive responses.
Where do they search for news?
This is where the 42 months brought the most visible change. As of August 2022, “where” meant Google Search, Google News, YouTube, and social platforms. Today, the answer includes ChatGPT, Perplexity, Claude, Gemini and AI Mode within Google itself.
THE Similar web traffic data for April 2026 clearly tells the story. ChatGPT records 5.5 billion monthly visits worldwide, but Google remains in the lead with 84.8 billion monthly visits. So the “where” of information seeking has truly fragmented in a way that matters for distribution strategy.
A story that only gets visibility in traditional Google search now reaches a smaller fraction of the total news-seeking audience than it did in 2022. The PR question: “where will this end up?” requires a broader response.
Why is your news important to your target audiences?
This is the stage that Amit Singhal’s 23 Panda » The questions were really on topic, in 2011. “Does the article provide original content or information, original reporting, original research, or original analysis?” This question appeared in Google Quality Tips 15 years ago. It appears, in updated form, in Google’s new AI research guide this week.
Clarkson-Bennett’s article makes the same point through the concept of information gain – a patent that Google has cited frequently, worldwide and with recent updates, that evaluates effort and rewards documents that add something not already present in the index. The commodity content problem is not new. The Panda update was Google’s first systematic attempt to fix this problem. The AI era is the latest, and most technically sophisticated, iteration of the same enforcement mechanism.
Why is your news important? Because it is original, specific and cannot be reproduced by pattern recognition on what already exists.
How can you change hearts, minds and actions?
The Panda question that applies here: “Does the article have the kind of quality you would expect to see referenced in a magazine, encyclopedia, or book?” This standard has not fallen in the age of AI. Rather, it has become the threshold for citation rather than simply ranking.
AI-generated summaries cite sources with authority, specificity, and true expertise. Public relations content most likely to deserve this quote is the content that would have passed Singhal’s 23 questions in 2011 and still passes them today. Original research. Primary sources. Specific claims based on verifiable data.
The means of changing mentalities have not fundamentally changed. What has changed is that the audience can now receive your argument through an AI intermediary rather than directly. The level of quality required to survive this intermediation is higher, not lower.
How can you measure your results?
This is where the 42 months created the most authentic new work. As of August 2022, metric meant organic traffic, impressions, and backlinks. Today, this requires tracking citation frequency in AI-generated answers, monitoring brand mentions in AI previews, and separating AI Assistant SEO Traffic from traditional organic. GA4 added this feature last week, with a new default channel group for recognized chatbot referrers, including ChatGPT and Gemini.
The measuring question that Aristotle didn’t have to answer was: How do you know if you’re winning when the audience never clicks? Quote Share of Voice in AI Answers Becomes New Ranking Position. It’s measurable. The tools are early and imperfect. But the principle is the same as in the early days of SEO measurement: identify the signal that predicts whether the right people are finding your content and track it consistently.
What Aristotle was right
Google’s new documentation states that AEO and GEO are still SEO. This means that the questions under the terminology have always been the same: who are you trying to reach, what do they need to understand, and how do you demonstrate to the system that surfaces your content that you have truly met that need?
Aristotle’s seven elements of circumstance survived 23 centuries before applying them to digital PR in 2022. They will survive AI mode, AI insights, and whatever Google comes up with next.
Basic things apply.
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