hotels.impt

Hotel Search by Vibe

Most hotel searches start with the wrong question. You open a booking site, and it asks: city, dates, guests, star rating. But that's not how you actually think about a trip. You think about a feeling — a creaky wooden lodge with a fireplace, a quiet boutique with a balcony for morning coffee, a resort where the kids will be entertained for six hours straight while you read a book.

Vibe-based search flips the order. Instead of filtering by amenities and hoping the photos match the mood, you describe the mood and let the system find properties that fit.

What "vibe" actually means in a search

A vibe is a cluster of signals: architectural style, location type, guest demographics, price tier, and the small details that show up in reviews. When you type "cozy lodge winter," you're not asking for a checkbox — you're asking for timber interiors, mountain access, a fireplace lounge, snow nearby, and probably fewer than 60 rooms. An AI search reads that intent and translates it into property attributes.

A few examples of how the translation works:

None of these descriptions map cleanly onto a single filter. That's the gap vibe search is built to close.

How the matching actually happens

Behind the scenes, an AI search does three things in sequence. First, it parses your phrase into intent and constraints — what kind of place, what location, what time of year, who's coming. Second, it expands the intent into property attributes it can actually look up in inventory data. Third, it ranks hotels by how well they match the full picture, not just the keywords.

The ranking step matters most. A hotel can have "boutique" in its name and still feel like a chain. Review language, photo content, and guest sentiment carry more weight than marketing copy. That's why vibe results often surface properties you wouldn't have found by sorting on price or star rating alone.

If you want to see how this plays out in practice, try a vibe search in IMPT — type the trip you're imagining rather than the filters you'd normally pick.

Writing a vibe query that actually works

You don't need to be poetic. Short and specific beats long and flowery. A useful vibe query usually has three parts:

  1. The feeling or property type — cozy, minimalist, design-led, family-friendly, party, quiet, historic.
  2. The location or setting — beach, mountain, old town, lakeside, a specific city or neighborhood.
  3. The context — winter, anniversary, kids, work trip, dog-friendly.

"Minimalist hotel Lisbon walking distance old town" works better than "nice hotel Lisbon." "Adults-only beach resort Greece September" works better than "Greece vacation." The more you tell the search about the trip you're actually planning, the less filtering you have to do later.

Where vibe search fits — and where it doesn't

Vibe search is strongest in the discovery phase, when you know the feeling but not the property. It's weaker when you already have a shortlist and need to compare specific amenities or rates — at that point, structured filters are still faster. The realistic workflow is to start broad with a vibe query, narrow to a few candidates, then check the details.

If you're curious how this compares to older approaches, see AI vs traditional search. For the underlying mechanics, natural-language hotel search covers how the parsing works. And if you're planning a whole trip, not just one stay, trip planning with AI picks up where hotel search leaves off.

The short version: describe the trip you want. Let the search do the translation.