Lab Notes

Our research into how AI systems discover, evaluate, and recommend businesses. These findings inform everything we build.

PlaybookMar 2026

The Independent Hotelier's AI Visibility Playbook

A five-phase plan for independent hotels to become visible in AI travel recommendations. Combines technical foundations, content strategy, and ongoing optimisation into a practical roadmap.

Guide / ContentMar 2026

How to Write Website Content That AI Engines Actually Cite

AI engines extract and cite specific types of content. This guide covers the content structures, formats, and writing patterns that increase your chances of being recommended.

PerspectiveMar 2026

Why AI Visibility Monitoring Is Not Enough

Knowing your AI visibility score is useful. Knowing what to change is what actually matters. At Delphium Labs, we think the industry is focused on the wrong problem.

Market / ReportMar 2026

The State of AI Visibility in UK Hospitality: 2026

Where the UK hospitality industry stands on AI visibility in early 2026. Most businesses remain invisible to AI recommendations, creating a significant first-mover advantage for those who act now.

GEO / HotelsMar 2026

Why Your Boutique Hotel Disappears in AI Travel Answers

Most boutique hotels are invisible to AI travel recommendations. Delphium Labs analysis identifies the five technical gaps that cause this and the specific fixes that restore visibility.

Market / ComparisonMar 2026

ChatGPT vs Perplexity vs Gemini: Which Matters Most for Hospitality?

Each AI engine recommends hotels and restaurants differently. Delphium Labs tested 300 queries across all three to map where each engine sources its answers and which matters most for your business.

Market / AnalysisMar 2026

Why OTAs Are Investing in AI and What It Means for Direct Bookings

Booking.com, Expedia, and TripAdvisor are building AI-powered travel assistants. For independent properties relying on direct bookings, this creates a new competitive threat that traditional SEO cannot address.

Guide / TechnicalMar 2026

Schema Markup for Hospitality: A Technical Guide

How to implement Hotel, Restaurant, LocalBusiness, and Event schema markup so AI engines understand your hospitality business. Includes JSON-LD examples ready to use.

PerspectiveMar 2026

From Research to Product: Why We Built FindingFin

The story behind FindingFin. What Delphium Labs found in 18 months of AI visibility research, the gap it revealed in the market, and why we decided to build a product to close it.

Guide / HotelsFeb 2026

9 Steps to Improve Your Hotel's AI Search Visibility

A practical, step-by-step guide to making your hotel visible in ChatGPT, Perplexity, and Gemini recommendations. Based on patterns from hundreds of AI visibility audits.

GEO / DiningFeb 2026

How AI Engines Choose Which Restaurants to Recommend

A deep dive into the recommendation mechanics behind AI restaurant suggestions. Based on FindingFin analysis of 150 dining queries across ChatGPT, Perplexity, and Gemini.

GEO / WeddingsFeb 2026

AI Visibility for Wedding Venues: What 30 Audits Revealed

FindingFin visibility audits across 30 UK wedding venues found that only 4 appeared in AI answers. All 4 shared three specific technical characteristics that the others lacked.

GEO / ResearchFeb 2026

We Tested 200 Restaurant Queries Across Three AI Engines

Delphium Labs queried ChatGPT, Perplexity, and Gemini with 200 real diner questions. Google Business Profile data, menu content, and specific dish descriptions drove the strongest AI visibility.

GEO / ResearchJan 2026

Chain Hotels vs Independent Properties in AI Search Results

A detailed breakdown of where chain hotels dominate AI recommendations and the specific query types where independent properties can compete. Based on Delphium Labs analysis of 500 AI responses.

GEO / ResearchJan 2026

How AI Engines Recommend Hotels: A 500-Query Study

Delphium Labs tested 500 traveller queries across ChatGPT, Perplexity, and Gemini. Chains dominate 72% of recommendations. Here is what determines which hotels AI engines choose to cite.

Delphium Labs . Lab NotesRResearch