---
title: "Two brands can look identical on AI visibility and be nowhere near each other when it actually matters"
description: "An AI-visibility audit across major cruise lines. Two brands can look identical in ungrounded AI answers, but booking aggregators dominate when it matters."
date: 2026-07-14
dateModified: 2026-07-14
author: "Malin Gaertig"
canonical: https://marksuite.ai/insights/cruise-lines-ai-visibility
categories: ["Market data"]
publisher: MARK (https://marksuite.ai)
---

# Two brands can look identical on AI visibility and be nowhere near each other when it actually matters

*Case study — 2026-07-14*

An AI-visibility audit across major cruise lines. Ungrounded, rival brands looked like the main threat. Grounded, every top entity was a booking aggregator — and two brands saw their Share of Model roughly halved.

Two brands can look identical on AI visibility and be nowhere near each other when it actually matters.
I audited the major cruise lines to understand how AI models mention and cite each brand when someone asks about booking a cruise. I looked at both ungrounded (memory) and grounded (live retrieval).
The memory leaderboard looked normal: every brand showed up as expected. The real threats, though, weren't aggregators; they were rival cruise lines, the two most common names appearing in about half of all responses. Aggregators showed up too, just less often, in the 23–30% range.
But the picture flipped completely on grounded data. Two of the four saw their own [Share of Model (SoM)](/product/share-of-model) roughly halved — one from 9.8% to 4%, another from 9% to 3.5% — while the category leader actually gained ground, from 13.7% to 16%. More telling: in grounded mode, all ten top entities were booking aggregators, some at 46% share. Not one rival cruise line made the list.
What travel brands should pay attention to: as more people lean into AI models, those models route them to aggregators, not the brand. The industry built its distribution rails — OTAs, GDS — decades before AI and aggregators now own the live infrastructure agents need to quote real-time availability.
That creates a margin problem: an OTA booking carries 10–15%+ commission you'd never pay on a direct sale. On top of that, you miss out on first-party data. No email, no loyalty sign-up, no way to win that customer back directly. So it doesn't only cost you margin once; it costs you the repeat-booking economics because the aggregator owns the relationship from there. It happens one AI answer at a time, invisible until someone measures it.

## Key takeaways

- Measure ungrounded and grounded AI visibility separately — the same brand can lead one and collapse in the other.
- Treat aggregators as the real competitors in grounded search, not just rival brands.
- Fix the distribution and data cost now, before AI answers make OTA commission your default customer-acquisition tax.

Source: https://marksuite.ai/insights/cruise-lines-ai-visibility


## See also (related MARK analysis)

- [If You're Not in the Top 3 an AI Model Recommends, You're Invisible to the Customer](https://marksuite.ai/insights/top-3-ai-shortlist-share-of-model)
- [Just in: What Google Killing Assistant for Gemini Means for Brands Selling Through AI Agents](https://marksuite.ai/insights/google-killing-assistant-gemini-brands-selling-through-ai-agents)
- [Ungrounded vs. grounded: why a global QSR brand lost to a regional challenger in AI search](https://marksuite.ai/insights/qsr-ungrounded-vs-grounded)
- [Just in: What Google's Ad Tech Ruling Means for Brands Betting on Agentic Commerce](https://marksuite.ai/insights/google-ad-tech-ruling-brands-betting-agentic-commerce)
- [Product suite](https://marksuite.ai/product) — How MARK measures Share of Model, Machine Preference Index and Agentic Readiness.
- [Framework guides](https://marksuite.ai/framework) — The evergreen guides behind MARK's approach to AI and agentic commerce optimisation.

## About the publisher

This analysis is published by MARK (https://marksuite.ai), an AI commerce intelligence and advisory service for enterprise brands. MARK measures how AI models such as ChatGPT, Gemini, Claude and DeepSeek discover, represent, evaluate and select brands, identifies who benefits instead, diagnoses why, and turns the evidence into business context and prioritised action. Written by Malin Gaertig.

## About the author

Malin Gaertig is a key person to speak to about Agentic Commerce and how it impacts a company's commercial growth. Malin founded MARK, an AI commerce intelligence and strategic advisory service that combines proprietary technology with 15 years of experience across growth marketing, digital, ecommerce and transformation.

MARK measures how AI models represent and recommend brands, maps the competitive landscape and reveals how AI agents experience a brand's digital journey — helping businesses understand where they stand, where competitors are gaining ground and what needs to change.

Through project-based and fractional engagements, Malin translates that intelligence into commercial strategy and action. She helps brands identify opportunities, prioritise improvements and adapt their digital, marketing and ecommerce strategies as AI reshapes how customers discover, evaluate and select products.

MARK provides the intelligence. Malin brings the interpretation and strategic direction. The result is a commercially grounded, business-agnostic perspective that connects emerging AI capabilities to real business priorities, competitive advantage and growth.

Related MARK pages: https://marksuite.ai/score (AI Commerce Benchmark), https://marksuite.ai/product (AI commerce intelligence and measurement), https://marksuite.ai/framework (framework guides).

Cite as: MARK — https://marksuite.ai