In Brief: Stephanie Smith explores the emerging dichotomy in AI application within hotels, focusing on its role in enhancing discoverability of services versus facilitating transactions.
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The New Hotel AI Funnel: Discoverability vs. Transaction – Image Credit Cogwheel Marketing
Not all AI investments for the hotel industry are equal. Many solutions focus on transaction infrastructure, but discoverability is often the gating factor for success.
AI hotel distribution has two components: being recommended and being bookable. Most hotels should focus first on being recommendable before investing heavily in booking integrations.
It’s a classic case of hotel Marketing vs. Revenue Management.
Make sure your investment aligns with the desired outcome.
The Discoverability Component (The “Marketing” Side)
Think of this as the modern version of SEO. In this scenario, we want to know:
Is the AI recommending your hotel?
What is it saying about our hotel?
How often are you appearing in topical prompts like
“best boutique hotels in downtown Denver for a girls weekend”?
Just like getting a hotel to rank on page one of Google, discoverability is about being an option in the consideration set, or were we surfaced as an option at all. The AI builds its “opinion” of your hotel based on:
- Own website with schema and good content
- Local blogs and media mentions
- Influencers and social media
- Third-party reviews
- Structured and unstructured backlinks & citations from credible sources
LLMs do not use backlinks as ranking signals in the same deterministic way Google does. Instead, it looks through consistent third-party coverage and entity mentions across credible sources that can influence its training. These references also, essentially, become a warehouse for data to be retrieved through connected search layers which ultimately shapes whether and how your property is recommended.
This isn’t just about your website or your schema markup. It learns from many places to determine when and if it will offer up your hotel as a suggestion. And if those mentions are not consistent and robust, you risk AI at best learning nothing about you because the data is off, or at worst creating “hallucinations” about you because it’s learning from inconsistent data.
Just like Google deciding whether you belong on Page 1 or Page 5, LLMs are deciding:
- Whether you’re mentioned
- How confidently you’re described
- In what context you appear
If you aren’t discoverable, the guest never even makes it to the next step. Just like with SERPs, if you don’t have strong foundations, even the best website won’t be mentioned, because both on-page and off-site signals matter.
But being recommended is only half of the equation. Once a guest decides where they want to stay, the question becomes: can the AI actually act on that decision?
The Transactional Component (The “Revenue” Side)
Once a guest decides where they want to stay, they need to know how to book it. This is where the technical plumbing comes in.
Some AI assistants are beginning to integrate with travel platforms via connected tools or MCPs (think of MCPs like historical APIs) that allow retrieval of real-time Availability, Rates, and Inventory (ARI). These integrations are platform-specific and still emerging, but represent the technical foundation that would allow an AI assistant to move from recommendation into execution.
The LLMs do not learn from MCPs; It pulling it into context for that session
While research data right now seems to indicate most guests are not ready to allow AI to take them all the way through a transaction, the time is approaching. And it is approaching much faster than the original adoption rate of the Internet in the early 2000s.
Bottom Line: An LLM cannot transact on your behalf if it never surfaced your hotel in the discovery phase
You can have the best transactional connection in the world, but if the LLM doesn’t “know” your hotel is a good fit for a “boutique pet-friendly hotel in Savannah,” you’ll never get the click.
Historically, our industry has treated visibility as a marketing function and conversion as a revenue management function.
LLMs blur that line.
- Discoverability becomes a marketing + PR + content ecosystem challenge
- Transaction readiness becomes an infrastructure + distribution challenge
In an LLM-driven world, distribution doesn’t begin at the hotel’s booking engine, it begins at recommendation. And if your hotel isn’t part of the answer the AI gives, you’re no longer competing on price, you’re competing for existence in the consideration set.
Stephanie Smith, CEO and Digital Matriarch, Cogwheel Marketing & Analytics, HSMAI Marketing Advisory Board Member. Connect with Stephanie on LinkedIn.
Source: View the original article at Cogwheel Marketing.
