Podcast Summary:

The Digital Marketing Podcast
Episode: The Big Debate: Non Keyword Signals - AI Chats & Privacy
Hosts: Daniel Rowles & Ciaran Rogers
Date: December 8, 2025

Episode Overview

In this episode, Daniel Rowles and Ciaran Rogers dive deep into the evolving world of digital marketing signals. They debate the increasing importance of "non keyword signals" in a landscape shaped by AI-powered search, shifting privacy boundaries, and changes within platforms like Google and Meta. Central themes include the decline of traditional keyword-focused SEO, the rise of AI-driven behavioral insights, and the complex ethical questions marketers now face regarding data privacy and user consent—especially related to AI chat interactions.

Key Discussion Points & Insights

1. The End of Keyword-Only Targeting and Rise of AI Signals

• Context: Google Ads' "AI Max" campaigns and similar AI-driven approaches now focus on a wider range of signals beyond traditional keywords.

• Observation:

  • There's a dramatic increase in search impressions but a corresponding drop in clicks as AI answers more questions directly in search results.
    • "If you look in your search console reports... massive increase in impressions, but quite a big drop in the actual number of clicks that you're getting." – Ciaran [00:41]
  • Even with effective SEO, click-through rates are plummeting because users get their answers in summaries or featured snippets, bypassing publishers’ sites.
    • "Our data... our impressions have pretty much doubled over the last 12 months. ... Our clicks at the same time have halved." – Daniel [01:21]

• AI’s Expanding Dataset:

  • Google is correlating not just search queries but a broad array of user behaviors (e.g., video watching, email activity, location via Maps).
  • AI employs this data to infer intent and interest in real-time, enabling "almost anticipating what you might be interested in or looking at next." – Ciaran [02:38]

• Campaign Performance:

  • AI-maximization campaigns are leading to "20, 30% uplift in results, basically by using ... keywordless signals." – Ciaran [03:39]

2. Privacy Implications and Ethical Dilemmas

• Core Debate: How far should platforms go in aggregating and leveraging behavioral data to personalize and target ads?
• Hosts’ Approach: Actively invite listener engagement and debate via LinkedIn, emphasizing the need for community perspective.
• Quote: "We want to find out how you feel about the privacy implications of these things." – Daniel [04:28]

Google vs. Meta Approaches

• Meta’s Evolution:

  • Meta (Facebook/Instagram) has shifted from using "connections" and explicit likes to heavily AI-driven content recommendation based on non-keyword signals—especially passive video consumption behaviors.
  • "The algorithm then has to change hour by hour, day by day because you might be in the mood for watching recipes at one moment and the next week you might be interested in fitness." – Daniel, referencing Alex Schultz [05:49–06:45]
  • Platforms dynamically adjust what users see using these complex behavioral metrics.

• AI Chat Data and Privacy

  • Meta announced a policy change: conversations with AI agents (e.g., in Messenger, Instagram, WhatsApp) may be used to target advertising.
    • "Those conversations, what they learn from those conversations and the insights they can glean can then be used to target advertising." – Daniel [07:04]
  • Ethical and practical uncertainty: how much privacy and anonymity should users expect from AI chat?
    • "Do we expect our AI chats to be anonymous?" – Daniel [07:29]
  • Distinction raised between user expectations for paid chat platforms (ChatGPT Pro) vs. open platforms.

Brand-Level Exposure & Data Control

• Brand Chatbots on Meta/WhatsApp:

  • Ciaran highlights concern over businesses using Meta-hosted chatbots: will AI-driven recommendations leak sensitive purchase intent signals to competitors?
    • "If any interactions with like AI chats within the meta platform, like how far does that extend? ... Does that mean those signals are going to be used by my competitors and available to buy within the ad space?" – Ciaran [08:24]

• Defining "Sensitive" Data:

  • Meta claims sensitive data will be filtered, but there’s ambiguity:
    • "How do you define sensitive data, actually? Because it's not a black and white thing." – Ciaran [09:10]

3. Notable Hypotheticals & Grey Areas

• Daniel's Hypothetical Business Model:

  • Creating a free expert chatbot for sites, with a catch: all data input could be used for ad targeting.
    • Raises the question: Is it ethical or even legal if buried in T&Cs?
    • "All I've done is in my terms, conditions. I've just said you can have this for free, but in exchange we get to use the data for targeting." – Daniel [10:43]
  • Further debate on whether website owners and visitors are truly aware of the implications.

• Trust in Conversational AI:

  • The more natural the AI-human chat, the more likely users are to disclose sensitive information—raising the stakes for responsible data handling.
    • "You implicitly trust it a little bit more. Like you start having a much more human conversation with it." – Daniel [11:15]

• Organizational Data Risk:

  • Daniel recounts practical risks: with organizational AI tools like Copilot accessing legacy cloud storage (e.g., OneDrive), poorly set permissions can accidentally expose sensitive information.
    • "Suddenly it's got access to their OneDrive and they haven't got their settings set up right…suddenly I can say, how much does Kieran earn?" – Daniel [12:56]

Notable Quotes & Memorable Moments

• On the impact of AI summaries:

  • "The click through rate isn't this. It was necessarily. And that's again, people aren't just aren't clicking right. Because they're getting, giving the answers..." – Ciaran [01:35]

• On platform privacy policies:

  • "How far does sensitive go?" – Ciaran [09:10]

• On the gray zone of free tools and user consent:

  • "Could you though? Is that explicit concept? Was that made clear? Did I opt into that?" – Ciaran [11:09]

• On human trust in AI chats:

  • "Because you implicit when you talk to somebody, you implicitly trust it a little bit more..." – Daniel [11:15]

Community Engagement & Listener Challenge

• Debate Invitation:
  • Listeners are encouraged to join the debate on LinkedIn (search for "Target Internet" or "Daniel Rowles") and via the podcast website for a chance to win books and merchandise.
  • Aim: Gather opinions and real-world experiences related to AI, privacy, and non-keyword signal marketing (see [14:43]).

Timestamps for Key Segments

• Introduction to Non-Keyword Signals – [00:10]–[02:38]
• AI Summaries and Decline in Organic Clicks – [01:21]–[03:39]
• Privacy Debate: Google, Meta & Chatbots – [04:28]–[08:24]
• Data Use Cases – Hypotheticals and Concerns – [10:25]–[12:21]
• AI Tools, Organizational Security Risks – [12:56]–[14:11]
• Listener Engagement and Call to Action – [14:43]–[15:13]

Tone and Final Thoughts

The episode is analytical but conversational, with a healthy skepticism toward big tech’s use of data and a strong call for marketers and consumers alike to critically examine the boundaries of privacy and consent. Both hosts openly question the implications of current trends while encouraging a broader community dialogue.

“I think it's just an interesting area... Big questions.” – Ciaran [14:11]

Join the debate and share your perspective:

• LinkedIn: [Target Internet / Daniel Rowles]
• Podcast website: targetinternet.com/podcast