From SEO to GEO: How LLMs Are Changing Brand Discovery
This episode of the Marketing AI SparkCast explores the shift from traditional SEO to AI-driven brand discovery, with Aby Varma and Gumshoe CEO Todd Sawicki. They discuss how large language models (LLMs) are replacing ranked search results with contextual, probabilistic recommendations and what marketers must do to remain visible. Key topics include AI Optimization (AIO), Generative Engine Optimization (GEO), and how brands can audit and shape their presence in LLM outputs.
This story was produced through MarketScale. See how Professional AV teams put it to work with Customer Stories & Case Studies.
Promoted content from The Marketing AI SparkCast on MarketScale.
Key takeaways
LLMs are displacing traditional SEO by delivering contextual, persona-driven brand recommendations rather than ranked search results.
Gumshoe uses synthetic personas and simulated chat sessions to audit how often and in what context LLMs recommend a brand.
Brands can improve LLM visibility by ensuring crawlable, structured content across product pages, FAQs, knowledge bases, and authoritative third-party citations.
Free workspace
Turn your Professional AV expertise into content.
Record interviews, organize footage, and write with AI in a free MarketScale workspace. Qualifying companies also get one professional video edit a month. No credit card.
This episode of the Marketing AI SparkCast features Aby Varma, founder of Spark Novus, a strategic partner to marketing leaders adopting AI responsibly. Aby is joined by Todd Sawicki, CEO and co-founder of Gumshoe, an emerging platform built to help brands understand what large language models (LLMs) think about them and how to act on it. The conversation dives deep into the paradigm shift from traditional SEO to AI-driven brand discovery. Marketers will walk away with a much clearer view of AI Optimization (AIO), Generative Engine Optimization (GEO), the mechanics behind AI answers, and how to align messaging with LLMs to improve brand visibility.
Topics Covered:
From SEO to AIO and GEO: Traditional SEO is losing ground as LLMs define how users discover brands
AI’s Personalization Power: LLMs generate contextual recommendations based on user behavior and profile
Understanding AI’s Brand View: Gumshoe audits show how often and why LLMs recommend your brand to specific personas
AI’s Impact on Paid and Organic: Even paid search is affected as AI models push answers above ads
Probabilistic Nature of LLMs: Discovery is no longer ranked and deterministic but context-driven and dynamic
Gumshoe’s Methodology: Uses synthetic personas and chats to audit brand visibility in AI
Training the AI Sales Rep: Brands must actively shape how AI perceives and represents them
Key Channels LLMs Trust: Product pages, FAQs, knowledge bases, expert mentions, and academic citations
How to Get Found: Crawlability, structured content, and relevance to AI queries now define visibility
Todd Sawicki is the CEO and co-founder of Gumshoe, a platform that helps brands audit and optimize their visibility within AI-driven discovery platforms. His career spans Disney, early-stage internet startups, performance marketing, and building programmatic ad platforms—all culminating in his latest venture, Gumshoe.
LinkedIn: https://www.linkedin.com/in/toddsawicki
Aby Varma is the founder of Spark Novus, a firm that partners with marketing leaders to adopt AI responsibly and strategically. He specializes in fusing brand, content, and growth through modern marketing strategy.
LinkedIn: https://www.linkedin.com/in/abyvarma/
Part of this channel
The Marketing AI SparkCast
Practical AI guidance for B2B marketing teams, episode by episode.
Your experts belong here
Every story in MarketScale Professional AV starts with a company putting its integrators, design engineers, and product specialists on the record. Buyers are already reading this topic. The only question is whose experts they find.
When a spec writer or facilities lead searches this category, your integrators are what they find instead of a competitor.
About the author
