In this episode of The Ross Simmonds Show, Ross sits down with Nick Lafferty, Founding Marketing Engineer at Profound, to unpack the fast-moving world of AI visibility, AEO, GEO, and AI search. They explore how brands can earn citations across ChatGPT, Claude, Perplexity, Grok, and Google AI, why visibility is no longer just an SEO problem, and how marketers can build systems that help their teams move faster.

Key Takeaways and Insights:

1. Building Marketing Taste Before Automating with AI

- Nick explains why AI does not have taste on its own and why marketers need judgment, experience, and creative instincts before automating workflows.

- Great marketing taste comes from studying campaigns, consuming strong creative work, testing in public, and learning from feedback.

- Creating content consistently, whether through LinkedIn posts, newsletters, blogs, or videos, helps marketers sharpen their voice and understand what resonates.

2. The Rise of the Marketing Engineer

- A marketing engineer is part builder, part artist: someone who understands marketing strategy and can build AI-powered systems to solve business problems.

- Nick shares how he automated manual unsubscribe syncing across multiple email tools at Profound, saving time for the marketing operations team.

- The strongest marketing engineers are AI-native, deeply curious, and focused on redesigning workflows with AI at the center instead of simply automating outdated processes.

3. AI Visibility, AEO, GEO, and the New Search Landscape

- Nick challenges the idea that AI visibility is only a content or website problem, noting that most AI citations come from third-party sources.

- Profound research shows only about 5–10% of citations come from a brand’s own domain, while the majority come from places like Reddit, YouTube, review sites, press releases, documentation, and partner ecosystems.

- Enterprise brands need cross-functional alignment across SEO, PR, social, product marketing, affiliates, and content to compete in AI search.

4. Making the Case for AI Visibility Internally

- Nick recommends marketers look for declining organic traffic, rising impressions with fewer clicks, inaccurate AI answers, and poor competitive comparisons as signs of an AI visibility problem.

- The Profound team uses the concept “make the invisible visible” to surface hidden risks and opportunities.

- Marketers should bring screenshots, prompt examples, traffic trends, and suggested solutions to leadership to win buy-in.

5. Measuring AI Visibility and Proving ROI

- Nick advocates for using a required “How did you hear about us?” field to capture self-reported attribution from sources like ChatGPT, Claude, Gemini, and Perplexity.

- Profound tracks AI bot traffic, server logs, citation trends, competitive benchmarks, and visibility changes over time.

- The conversation highlights why measurement needs to evolve as buyers increasingly discover brands through AI-generated answers.

6. Personas, Memory, and Personalized AI Search Results

- Profound’s personas feature helps brands understand how different buyer types may see different AI answers.

- Teams can analyze visibility across personas such as SEO managers, CMOs, affiliate managers, PR leaders, and demand generation teams.

- Personas help marketers approximate how memory and personalization may shape AI search results for different audiences.

7. Reddit, Listicles, and Off-Site Citation Strategy

- Nick explains why Reddit requires a contribution-first mindset and compares it to joining a dinner party where listening matters before speaking.

- Listicles may still work in some industries, especially affiliate-heavy categories, but many marketers are over-investing in them as a short-term tactic.

- The bigger opportunity is building adaptable systems that can respond to changing citation patterns across AI search platforms.

Resources & Tools:

🔗 Profound

🔗 Every

🔗 HubSpot

🔗 Customer.io

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