Last week, I read Giulia Panozzo’s article about rethinking audience targeting in a signal-loss era. I also read Harry Clarkson-Bennett’s article about creating non-commodity content. And then I read Matt G. Southern’s article about Google’s new AI search guide officially calls AEO and GEO “still SEO.”
Reading them together, I kept hearing the same message: the fundamental things apply.
And that sent me back to something I wrote on August 11, 2022 – two and a half months before OpenAI released ChatGPT – “7 Steps To Building A High-Impact Digital PR Campaign,”
What I Borrowed From Aristotle
In my August 2022 article, I disclosed that the framework wasn’t mine. The 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 one AI revolution later, is whether the seven steps still hold.
They do. But what each step requires has changed.
Who Are Your Target Audiences?
In August 2022, this step was primarily about demographics and keyword personas. But signal loss is not a new problem – it’s a recurring one. In 2013, Google’s move to encrypted search made “keyword not provided” a major problem, stripping away the keyword-level analytics data that practitioners had relied on to understand who was actually finding their content and why. We adapted. We found other signals.
Today, the challenge has another layer. The data holes in Google Analytics 4 are real – I’ve written about them at length. The R.E.M. Framework Panozzo describes is addressing what to do when the data you relied on to define your audience has become unreliable or incomplete. Her answer, and mine, is the same: Get closer to actual people rather than proxy data. Signal loss is an inconvenience for lazy audience definition. It is an opportunity for practitioners disciplined enough to gather first-party signals through direct observation.
What Is Their News Search Intent?
Google’s new AI search guide, published this week, makes something explicit that has been implicit for years. AEO and GEO are not separate disciplines from SEO. They are SEO, applied to generative AI features. The underlying question has always been the same: what is someone actually trying to understand or accomplish when they search?
What has changed is the format of the answer they now expect. In AI Overviews and AI Mode, the answer comes first. The citation comes second, if at all. For digital PR, this means the question is no longer just “can we rank for this?” but “can we earn a citation in the answer Google generates?”
The intent question remains. The answer format has changed around it.
When Do They Conduct News Searches?
This step is relatively stable, though the tools for measuring temporal search patterns have improved considerably. Clarkson-Bennett’s piece makes the practical point well: Google Trends data for terms like “family holidays” shows spikes every January with near-perfect consistency across five years. Seasonal patterns in news search intent are more durable than most practitioners assume, and AI Overviews have not disrupted the underlying rhythms, only the interface through which people receive answers.
Where Do They Conduct News Searches?
This is where the 42 months have brought the most visible change. In 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 Similarweb traffic data for April 2026 tells the story plainly. ChatGPT logs 5.5 billion monthly visits globally, but Google still leads with 84.8 billion monthly visits. So, the “where” of information-seeking has genuinely fragmented in ways that matter for distribution strategy.
A news story that earns visibility only in traditional Google Search is now reaching a smaller fraction of the total information-seeking audience than it was in 2022. The PR question of “where will this land?” requires a broader answer.
Why Does Your News Matter To Your Target Audiences?
This is the step that Amit Singhal’s 23 Panda questions were really about, back in 2011. “Does the article provide original content or information, original reporting, original research, or original analysis?” That question appeared in Google’s quality guidance 15 years ago. It appears, in updated form, in Google’s new AI search guide this week.
Clarkson-Bennett’s piece makes the same point through the concept of information gain – a patent Google has cited frequently, worldwide, and with recent updates, which estimates 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 solve it. The AI era is the latest, and most technically sophisticated, iteration of the same enforcement mechanism.
Why does your news matter? Because it is original, specific, and cannot be replicated by pattern recognition across what already exists.
In What Way Can You Change Hearts, Minds, And Actions?
The Panda question that applies here: “Does the article have the kind of quality you’d expect to see referenced by a magazine, encyclopedia, or book?” That standard hasn’t lowered in the AI era. If anything, it has become the threshold for citation rather than just for ranking.
AI-generated summaries cite sources that carry authority, specificity, and genuine expertise. The PR content most likely to earn that citation is the content that would have passed Singhal’s 23 questions in 2011 and still passes them today. Original research. Primary sources. Specific claims grounded in verifiable data.
The means of changing minds have not fundamentally changed. What has changed is that the audience may now receive your argument through an AI intermediary rather than directly. The quality standard required to survive that intermediation is higher, not lower.
By What Means Can You Measure Your Results?
This is where the 42 months have created the most genuine new work. In August 2022, measurement meant organic traffic, impressions, and backlinks. Today, it requires tracking citation frequency in AI-generated answers, monitoring brand mentions in AI Overviews, and separating AI assistant referral traffic from traditional organic. GA4 added that capability last week, with a new default channel group for recognized chatbot referrers, including ChatGPT and Gemini.
The measurement question Aristotle didn’t have to answer was: How do you know if you’re winning when the audience never clicks through? Citation share of voice in AI answers is becoming the new ranking position. It is measurable. The tools are early and imperfect. But the principle is identical to what it was when SEO measurement began: Identify the signal that predicts whether the right people are finding your content, and track it consistently.
What Aristotle Got Right
Google’s new documentation says AEO and GEO are still SEO. What it means is that the questions beneath 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 surfacing your content that you’ve genuinely answered that need?
Aristotle’s seven elements of circumstance survived 23 centuries before I applied them to digital PR in 2022. They will survive AI Mode, AI Overviews, and whatever Google ships next.
The fundamental things apply.
More Resources:
- A Little Clarity On SEO, GEO, And AEO
- 3 Strategies That Can Survive AI Search In 2026: What I Shared At SEJ Live
- The Role Of E-E-A-T In AI Narratives: Building Brand Authority For Search Success
Featured Image: Roman Samborskyi/Shutterstock
