Your rankings can climb while your leads dry up. They can also drop while nothing's actually wrong. Jenna joins Chuck and Kayleigh to break down what's really happening with AI SEO, AEO, and generative engine optimization, and why "search volume" can't account for the millions of private conversations happening inside ChatGPT, Gemini, and Claude.

AI search is more conversational than a Google search bar ever was. That demands more human work, not less. Keyword tracking still has a place: treat it like a topic map, then expand into the actual questions people ask, the language they use, and the problems they're trying to solve. Jenna explains why the team is anti-slop, why LLMs are predictive text that still need a human doing the reasoning, and what "good farmer SEO" means: going back through existing content and making it clearer, fresher, and easier for both AI and people to use.

Brand reputation feeds AI visibility too. Customers complaining on Reddit or third-party sites shows up in what AI surfaces. That's why digital PR and outside validation matter, and why a single "AI visibility score" can hide what's actually happening across ChatGPT, Gemini, Claude, and the rest. If you want reporting you can explain to a client without jargon, and a strategy built on outcomes instead of vibes, this episode's for you.

In this episode:

• Why keyword tracking is a starting point, not the whole strategy
• Turning keywords into a topic map instead of a checklist
• Why AI SEO takes more human involvement, not less
• What "good farmer SEO" actually means
• Topic authority vs. just publishing a lot of content
• Being anti-slop: why LLMs can't reason and still need a human
• How Reddit reviews and public sentiment shape AI visibility
• Why digital PR and third-party validation matter for AI search
• The problem with a single "AI visibility score"
• How to explain AI SEO to clients without the jargon

Chapters 

0:34 The AI search disconnect: when rankings lie 

1:46 Why AI search is more conversational 

3:31 Keywords as a topic map, not the whole strategy 

5:57 Why AI SEO needs more human work, not less 

7:08 Talking to clients & semantic search 

8:53 What is "good farmer SEO"? 

9:39 Topic authority vs. just having content 

11:00 Why we're anti-slop: LLMs can't reason 

13:41 Reddit reviews & brand reputation 

14:50 Case study: pricing pages & qualified buyers 

16:23 How Reddit shapes your AI visibility 

17:53 Digital PR & third-party validation 

19:11 The problem with one "AI visibility score" 

21:26 How to explain AI SEO to clients (no jargon)

Happy searching.

“Only two tickets left” is sometimes true, and sometimes it’s a psychological crowbar. We sit down with Courtney Turrin, a psychologist and neuroscience-trained researcher who now works in marketing, to unpack why urgency, fear, and “limited time” language can hijack our attention even when we know better.

We dig into the core behavioral science that shows up in modern digital marketing: attention as the scarcest resource, emotional valence (negative, neutral, positive) and how it changes what people notice, and loss aversion as the engine behind FOMO-driven messaging. 
Courtney breaks down common conversion patterns like three-tier pricing and “most popular” positioning, then we stress-test what’s fair versus what’s manipulative using a real ticket-buying story that spirals into scalper pricing and fake scarcity.

We also talk about remarketing and why it works: repetition creates fluency and familiarity, which can build trust and recall, but it can also create that instant “ick” when relevance is off, or advertising tactics get too aggressive. 
The big takeaway for marketers is to stop relying only on hindsight metrics and start forming research-backed hypotheses about why people behave the way they do. Slow down, verify, and notice what lever is being pulled before you click.

If this helped you see ads and sales pages with clearer eyes, subscribe, share this with a skeptical friend, and leave a review with the one marketing tactic you want us to break down next.

00:00 Cold open: getting duped by a scalping site
00:24 Welcome to psychology expert Courtney Turrin
02:21 Monkeys, dingoes and a path into marketing
05:42 The psychological mechanisms in every marketing campaign
06:59 Loss aversion, false urgency and desensitization
07:38 Why every pricing page has three tiers
08:28 Emotional valence, explained
10:04 Fear tactics
11:27 Only two tickets left: the Flying Squirrels story
12:49 The blue dot phenomenon
14:33 What psychology changes about a landing page
15:56 Hindsight data vs research-backed hypotheses
18:40 Remarketing tracking suspicions
20:05 Where persuasion becomes manipulation
23:22 Getting Instagrammed: fluency, trust, and the ick
26:05 Solving a problem people do not know they have
27:53 Notice which lever is being pulled

Learn more about Xponent21
www.xponent21.com
instagram.com/xponent21
https://www.linkedin.com/company/xponent21-inc

Subscribe to To The Power of X, a Channel RVA Original Podcast
https://channelrva.com/shows/to-the-power-of-x

Everyone's using AI. A lot of people are using it to replace thinking instead of speed it up, and they can't always tell the difference.

In this episode, Chuck, Kayleigh, and Jenna get into what it actually looks like when AI stops being a tool and starts being a stand-in for judgment. That includes what AI hallucinations really are (and why the confident tone is the dangerous part), how a language model actually processes a question before answering it, why AI-generated content is getting easier for both people and Google to spot, and where AI is genuinely useful versus where it's quietly making you worse at your job.

If you touch ChatGPT, Claude, or Gemini at work in any capacity, this one's for you.

01:06 How you're using ChatGPT wrong 

03:24 The red flags of AI replacing strategic thinking 

05:08 When AI is actually a legitimate sounding board 

05:51 The "yes-man" problem of AI

07:35 What an AI hallucination actually is 

12:03 How AI actually answers your question (shadow prompting) 

14:24 Learning "strategy" from internet slop 

16:13 Why people can tell when content is AI-written 

18:18 Slop, sameness, and standing out 

19:21 The competitive risk of pure AI content 

19:45 Google is starting to stop indexing AI content 

Want a marketing team that knows when to use AI and when not to? 

Book a discovery call: https://xponent21.com/contact

Most AI visibility tools are giving you a dashboard. What they're not giving you is data you can actually make decisions from.

That's the problem Chuck, Kayleigh, and Will sit down to unpack in this episode of To the Power of X, and it's a problem that's been sitting in the background of almost every client conversation Xponent21 has had over the last year. 

When a client asks "what is AI saying about my business?" there isn't a clean answer. Not because the question is wrong, but because the tools built to answer it aren't built on real research infrastructure. They're built on shallow signal, marked up to enterprise prices, and handed to marketers who are expected to tell a story with it.

So Xponent21 built something else. CARL — the Cognitive AI Ranking Lab — started as internal software to help the team move faster and with more precision. It's since grown into something bigger: a research lab that prompts large language models across hundreds of topics and industries, captures those responses as data points, and analyzes how AI-assembled answers change over time as the models evolve.

In this episode, Will Melton breaks down what CARL actually is, why we built it, and what the early research is starting to show about how LLMs construct answers — including things like shadow prompts, compute thresholds, and the personalization layer that makes "what is AI saying about me" a genuinely hard question to answer at scale. 

Kayleigh brings the client-side perspective: what it's actually like to navigate those conversations without good data, and why the variation in LLM outputs is only going to get more pronounced as the models get more user-aware.

If you work in marketing, run an agency, or you're trying to figure out what your AI visibility spend is actually buying you, this one's worth your time.

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CARL Labs: https://carlaio.com/

Xponent21: https://xponent21.com/

Welcome to To the Power of X, the Xponent21 podcast about AI, marketing, and the tools and strategies actually worth your time. In episode 1, Chuck, Kayleigh, and KO break down how marketers should approach the overwhelming world of AI tools, with 5,000+ MarTech options out there and new models dropping every couple of weeks.
 
We get into building an AI strategy before you buy anything, how to test tools without getting lost in the fun, and when to reach for a foundational LLM vs a purpose-built tool. KO (our resident tool nerd) explains the difference between Claude Code and Claude Cowork, why model choice matters at every step, and how prompting turns into reusable skills you can share across your team. Plus: why voice AI like Wispr Flow is an easy two-hours-a-week win, and the case for diversifying your AI stack instead of betting on one model.
 
Whether you're AI-curious or already building agentic workflows, this one's for you.
 
Chapters:
00:10 Welcome to To the Power of X
01:08 Navigating the overwhelming world of AI tools
02:30 Developing an AI strategy
03:41 Testing & pilot programs
05:24 ROI, security & quality control
07:02 Quick wins: saving time in marketing
09:49 Tool spotlight: Wispr Flow
13:16 Claude Code vs Claude Cowork
17:08 Agents & personal assistants
18:57 Human review & markdown files
21:00 Model selection: Sonnet vs Opus vs GPT
24:43 Content creation: which AI writes better?
27:14 Key takeaways & prompt engineering
28:12 Diversifying your tech stack
30:13 Sharing knowledge & what's next