Brand Perception in LLMs
Analysing how probabilistic models categorise, frame, and recommend brands against specific situational buying triggers (CEPs) — focusing on contextual sentiment over raw citation counting.
Quentin Aisbett
After 16 years leading organic search strategy, my focus has shifted to how conversational engines are entirely rewriting brand discovery. As the Lead SEO & AI Search Specialist at Deputy, founder of Salyence, and strategic advisor at Searcht, I spend my time understanding how large language models map brand data to real-world intent, and translating classic principles of mental availability into the digital layers that dictate machine recommendations.
About
I've spent the last 16 years helping businesses turn search into their most reliable growth channel — first as an agency founder, now as an in-house Lead SEO and AI Search Specialist. Along the way, I've led search strategy for eCommerce brands, educators, legal firms, and real estate agencies, always balancing immediate performance wins with long-term brand building.
My work relies on digging past high-level metrics in Google Search Console, GA4, and Semrush to uncover true behavioural insights — and increasingly, analysing brand entities and how they're being perceived in LLMs as search shifts toward AI answer engines. I started Searcht in 2010 to help brands grow visibility and trust across traditional search, and in 2026 founded Salyence, an AI brand health platform that measures how reliably conversational engines recommend brands for specific situational buying triggers.
Before specialising in search, I spent three and a half years as the Marketing & Sponsorship Manager for a football club, where I was responsible for driving commercial sponsorships, memberships, events, and digital strategy. I hold a Bachelor of Arts (Public Relations, International Relations) from Deakin University.
Expertise
Four core disciplines that dictate how modern brands are surfaced, understood, and retrieved across the digital ecosystem.
Analysing how probabilistic models categorise, frame, and recommend brands against specific situational buying triggers (CEPs) — focusing on contextual sentiment over raw citation counting.
Using forward statistical sampling to monitor shifting AI engine behaviours, tracking variance across models like ChatGPT and Gemini to isolate genuine visibility trends from stochastic noise.
Ensuring frictionless crawling environments through pristine DOM structures, edge-delivery speed, and precise entity schema architecture that makes data perfectly machine-readable.
Building editorial frameworks designed for the transition from keyword volume to conversational intent, prioritising informational utility so content satisfies both human buyers and retrieval engines.
Ventures
Founder
An AI brand health platform that measures how reliably conversational engines recommend your brand for specific situational buying triggers.
Founder & Strategic Advisor
A search marketing agency helping brands grow visibility and trust across Google and AI search, combining SEO, digital PR, and content. Based in Brisbane, serving clients nationally.
Ideas
Notes from the shift toward AI search — the themes I'm writing and talking about right now.
With WebMCP, agents won't just retrieve marketing copy — they'll perform tasks directly through the browser. Utility is becoming the new social proof.
Grounding source, citation, and mention are three different things. Understanding query fan-outs matters more than chasing any single citation.
Most AI-influenced visits return through Search and Direct, not AI referrals — meaning branded SERPs are more important than ever, not less.
Contact
Based in Pottsville, New South Wales.