The Age of Conversation: Same Question, Different World Continued
Following on from Jon’s talk at brightonSEO, every digital experience that can be a conversation is becoming one. But here’s the catch: the conversation your customers are having with your content may not be the one you’re seeing. Add to this the need to optimise for multi-turn conversations, and the challenge becomes clear: where do you even begin?
Jon Earnshaw reveals why the journey your audience takes into search matters more than ever, how to anticipate and predict multi-turn queries, and how to transform these insights into a future-proof content strategy.
This session is for anyone intrigued and perhaps perplexed by the rise of conversational search – from AI Overviews and AI Mode to ChatGPT and beyond. Where is it all heading? How do you ensure your brand doesn’t just join the conversation, but persists through multiple turns?
Put the thinking into practice
Jon also references our free Conversational GPT, designed to help teams turn traditional keywords into conversational queries. Use it to explore how your target terms evolve across intent, context, and multi-turn search journeys.
Overview
Search is experiencing a “paradigm shift” as legacy keyword-matching gives way to intent-driven, multi-turn AI interactions (Google AI Mode, Gemini 3, ChatGPT Search, and Perplexity). This session breaks down how brands can move past one-off prompt tracking, adopt structured DUO (Deep, Unique, Original) content frameworks, leverage emerging interactive SERP visualizers, and measure true conversational presence.
Executive Summary
Relying strictly on narrow keyword SEO or single-query ranking is no longer enough to maintain market share. As AI engines prioritize intent, multi-turn stateful search, and synthesized answer blocks, brands must optimize for continuous conversational journeys. By combining DUO content principles, authentic “fast” video assets, and structured schema, organizations can consistently capture citation doorways across AI surfaces.
Key Takeaways
The Shift from Keywords to Intent & Conversations: Search queries in LLMs average 23 words (compared to traditional 3-word keywords). Over 80% of conversational queries are unique, multi-layered intents rather than simple Q&A lookups.
The “DUO” Content Framework: To avoid having content collapsed or ignored by AI synthesis engines, Vice President of Search Liz Reed recommends three core pillars:
Deep: Show full mastery of the topic by answering not just the primary question, but the secondary and tertiary follow-up questions.
Unique: Provide distinct first-party data, distinctive methodology, or specific product parameters that competitors lack.
Original: Supply fresh analysis, verified author credentials, and firsthand experience (E-E-A-T).
The Surge of Video & Fast Content: Short-form video content (YouTube, TikTok, Instagram, LinkedIn) is heavily featured in AI Overviews and video carousels. Individual creators utilizing Fast Content (Firsthand, Authentic, Social, Trusted) frequently outrank established corporate domains in AI synthesis.
Gemini 3 & Generative Layouts: Interactive SERPs are emerging through “thinking modes” and generative UI modules. Consumers can now adjust interactive sliders (e.g., comparing camera value vs. features) or interact with real-time simulations directly within Google AI Mode.
Stateful Search & Contextual Carryover: Search interactions are stateful—meaning Google remembers previous steps in a user’s journey. A user entering AI Mode after browsing an AI Overview receives a deeper, personalized response tailored to what they have already read.
Practical Strategy: Mapping Multi-Turn Conversations
Avoid Single-Prompt Tracking: Judging AI visibility on the first prompt alone is like judging a marathon by the first 100 meters. Track brand presence across entire 4-to-6-turn decision flows.
Utilize Synthetic Prompts for Intent Mapping: Use contextual carryover prompts to map specific sub-conversations (e.g., fuel types, maintenance, safety, or gifting) to discover where your domain drops out compared to market rivals.
Double Down on Video Chapters: Break video assets into clear, semantic chapters to maximize your real estate footprint in AI Overview carousels.
Monitor Off-Site Sentiment: AI recommendations rely heavily on third-party sentiment (e.g., Reddit, YouTube, industry blogs). Track referring domains and sentiment metrics to maintain recommendability.
