Mastering Schema & Metadata for AI Search Success | Conductor Spring Summit 2026
Stop chasing keywords and start winning in AI search. Learn how to optimize your metadata and schema for the LLMs of 2026.
Is your SEO strategy stuck in the past? Nick Gallagher, Senior Strategy Director at Conductor, breaks down the fundamental shift from traditional keyword matching to the semantic relationships required by Large Language Models (LLMs).
In this deep dive, you’ll discover why traditional ranking signals like backlink authority are being joined by new "visibility" metrics in AI engines like Perplexity. We explore why title tags and meta descriptions still matter—but with a twist—and how to use structured data (Schema) to build the authority signals that AI bots crave.
Stop focusing solely on traffic and start focusing on brand visibility in the AI conversations that matter most to your specific personas.
Timestamps
0:00 - Introduction to AI Search & LLMs
0:48 - Keywords vs. Semantic Relationships
2:01 - Authority: Backlinks vs. Authoritative Sourcing
3:13 - The Power of Schema Markup for AI
4:13 - Persona-Driven SEO & Targeted Audiences
6:06 - Traffic vs. Visibility: Redefining KPIs
9:45 - Optimizing Metadata for AI Context
12:24 - Do LLMs Respect Canonical & Hreflang Tags?
16:01 - Advanced Schema Strategies (atID & SameAs)
21:36 - 3 Key Takeaways for AI Optimization
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