I Booked a Room Online… and Immediately Regretted It.

Why Hotel Bookings Are Broken in the Age of LLMs

A few weeks ago, I booked a hotel for a short business trip. The photos looked great. The room category sounded perfect: “Deluxe City View.” The reviews were reassuring. Everything pointed to a seamless stay — until I arrived.

What I walked into was technically the room I had booked. But experientially? Not even close. The view was a glimpse of a rooftop AC unit. The quiet I expected turned into elevator shaft symphonics. The desk I needed for work barely fit my laptop.

And that familiar frustration resurfaced: Why does booking a room online still feel like rolling the dice?

The truth is, online purchases — especially in hospitality — are fundamentally broken. And ironically, the gap is widening in the age of LLMs, where machines can understand nuance but booking systems still can’t express it.

The Real Problem: We Have No Shared Language for Experiences

Consumers may or may not know exactly what they want, but even if they do, most can’t articulate it.

• What does quiet mean?

• What does a nice view mean to you versus me?

• What does good for work actually entail?

We lack a shared language to describe experiences because experiences are deeply individual and shaped by sensory, contextual, and emotional dimensions that standard room categories can’t capture.

On the other side, suppliers can’t present their rooms across those dimensions. So they fall back on category labels created 40 years ago for operational convenience, not for guest relevance.

The result?

• Guests can’t express what they truly want.

• Hotels can’t show what truly differentiates their rooms.

Both sides lose. We settle for “Superior”, “Deluxe”, “Premium” — labels that mean everything and nothing. No wonder product and expectation rarely match.

Why This Happens: Our Booking Systems Flatten Complexity

Rooms are complex and individualized. They differ in layout, micro-location, design, ambiance, noise, view, sunlight, bedding, bathroom configuration, functional features, and emotional triggers. But booking systems reduce all of this richness into a single data point: Category.

In that simplification, everything that makes a room special, or terrible, gets lost.

Even worse, categories don’t reflect how people choose. We don’t pick a category… we pick a feeling, a fit, a context.

Traditional booking systems cannot capture:

• sensory dimensions (light, sound, smell)

• contextual dimensions (trip purpose, sleep preferences)

• relational dimensions (travel companions)

• narrative dimensions (the story you're trying to create)

These are the dimensions that actually shape the experience of a stay and none of them appear in a booking engine.

A Way Forward: A New Language and Data Structure for Experiences

If we want better matching between what guests seek and what hotels offer, we need more than prettier room photos or more filters.

We need a fundamentally different data foundation.

One that can:

• describe rooms in high granularity

• adapt descriptions to each guest’s context

• capture experiential nuances

• reveal differentiators

Help both sides understand each other

This is exactly why we built Dynamic Inventory at GauVendi.

Dynamic Inventory: Bringing Context, Features, and Experience Dimensions Into the Booking Journey

Dynamic Inventory redefines what a “room” is and enables a better matching between guest and room. Instead of being locked into a fixed category, the same physical unit can be represented differently for different guest profiles by highlighting the features that matter for that traveler.

• A family sees the connecting door and safe layout.

• A business traveller sees the ergonomic desk and quiet micro-location.

• A couple sees the balcony and sunset view.

• A wellness traveller sees the bathtub and natural light.

One room. Multiple narratives. Infinite relevance.

How it works

We built a data structure that breaks each unit down into granular features assigned to experience dimensions such as:

• space type & layout

• bedding & sleep comfort

• views & exposure

• outdoor areas

• room size & feel

• micro-location

• bathroom configuration

• design elements

• functional attributes

This multidimensional structure lets the system understand meaningful similarities across rooms, the kind humans intuitively sense but booking engines fail to capture.

It also allows AI models to generate better textual and visual representations and suggest more relevant alternatives.

The Outcome: Better Matches, Better Expectations, Better Stays

Imagine if, back on that business trip, the system had understood that I cared about quiet, workspace comfort, and a true city view, not just a “deluxe” label.

It could have:

• surfaced rooms with the right micro-location

• highlighted workspace-friendly setups

• differentiated between rooftop vs. skyline views

• warned me about elevator proximity

• suggested the right room even if cheaper

That’s the power of dynamic inventory and smarter matching. It moves us from guessing to understanding, from categories to context, from generic to hyper-personalized.Because in the age of LLMs, there’s no excuse for broken booking experiences.

We now have technology that can interpret nuance, understand individual needs, and translate experiential language into meaningful recommendations.

What we’re missing is an inventory model that speaks the same language.

Dynamic Inventory from GauVendi finally closes that gap. And when we fix the foundation, every part of the booking journey, from discovery to upsell to expectation, becomes more intuitive, more relevant, and more human.