How AEO Differs Tactically from SEO

Alex asks about tactical differences; Josh explains the need to supply answer engines with concise, crawlable resources rather than just ranking pages.

Play episode from 07:23

chevron_right

Transcript

chevron_right

Transcript

Episode notes

In this episode of The Long Game Podcast, Alex Birkett speaks with Nick Lafferty (Head of Marketing) and Josh Blyskal (AI Strategist) from Profound, an AI visibility platform focused on answer engine optimization (AEO). They explore the shift from SEO to AEO, where brands must optimize for AI-driven search experiences across ChatGPT, Perplexity, and Google’s AI Overviews. The conversation covers why agility is the new moat, how brand mentions and structured content shape AI visibility, and how both startups and incumbents can compete. Nick and Josh share tactical approaches—from Wikipedia and affiliate strategies to structured HTML tables—that improve citations in AI-generated answers. The discussion underscores the rising importance of PR, off-site visibility, and concise, high-utility content in the AI search era.

Key Takeaways

AEO Defined: Answer engine optimization is about making your brand the chosen answer in AI-driven search experiences.
User Experience Wins: Search is converging with chat—people want answers, not links—so engines prioritize utility and ease.
Agility as a Moat: Speed and adaptability matter more than long-term content calendars in today’s volatile AI search space.
Brand Mentions Beat Keywords: AI models lean heavily on off-site mentions (Reddit, Wikipedia, affiliates) as trust signals.
Structured Content Boosts Citations: Bullet points, HTML tables, and concise formatting make content “citation-friendly” for AI.
Startups vs. Incumbents: Incumbents benefit from brand equity, but startups can flank them by acting faster and publishing niche, high-utility content.
PR Is Back: Media coverage and Wikipedia presence play a critical role in being cited by AI engines.

Show Links