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Competition

How to build a hotel compset that actually works

2026-06-23 · 10 min read

Almost every hotel believes it knows who its competitors are. Very few actually do. There is a huge gap between the hotels you would like to be compared with and the hotels the guest truly compares you against before booking. Your competitive set, or “compset”, is that second group, the real one. Build it wrong and every rate adjustment you make for the rest of the year will be miscalibrated from the root. This guide is so you build it once, build it right, and keep it alive.

What a competitive set is and why it decides everything

A competitive set is the small group of hotels you measure your performance, your price and your reputation against. It is not an honor roll or a prestige ranking. It is a working tool. When a revenue manager asks “am I expensive or cheap today?”, the only useful answer is “compared to whom?”. That “whom” is your compset. Without it, a rate is just a loose number. With it, that same rate tells a story: you are ahead of the market, you are behind it, or you are right on the mark.

In practice, the compset feeds three daily revenue management decisions. The first is rate shopping, meaning watching the price at which hotels like yours are selling for future dates. The second is positioning, knowing whether your rate sits above or below that group and whether that makes sense. The third is reading demand, because when your whole compset raises prices for the same weekend, the market is telling you something your own calendar cannot see yet.

Real competitors, not aspirational ones

This is where most hotels in LATAM stumble. The owner wants to be measured against the prettiest hotel in the area, the one with the international brand, the one in the magazines. It is natural and it is human, but it is a trap. If your mid-rate boutique hotel compares itself with a luxury resort, you will look cheap forever, you will feel you are leaving money on the table, and you will push prices up until you price yourself out of the market you actually compete in. The aspirational compset inflates your ego and bleeds your occupancy.

A real competitor meets three simple conditions. First, the guest considers it at the same time as you, meaning it shows up in the same search and the same price range. Second, it solves the same need, same kind of trip, same area, same reason (leisure, work, an event, a road stop). Third, it has a scale similar to yours in room count and services, because a four hundred room hotel plays a different inventory game than a twenty room one. If a hotel does not meet all three, it is not your competitor, no matter how much you wish it were.

  • The guest sees it next to you, in the same search and the same price range.
  • It solves the same need, same travel reason and same area.
  • It has a similar scale in rooms, services and type of operation.
  • It competes for the same stay, not for the same trophy in a magazine.

A good exercise to find them without bias: put yourself in the guest’s shoes. Open the OTAs as if you were traveling to your own city, search your dates, filter by your area and your price range, and see which hotels appear next to yours on the same screen. Those hotels, the ones sharing a search result with you, are your true competitors. Not the ones you admire, but the ones the OTA algorithm has already decided are your alternative.

Primary and secondary compset

Not all your competitors carry the same weight, so it pays to split them into two groups. The primary compset is the three to five hotels the guest truly sees as your direct replacement. They are your most faithful mirror, the ones you watch every day, and the ones that most influence how you set your rate. Keep it short. A primary compset of fifteen hotels is not a compset, it is noise, and it ends up averaging everything until it tells you nothing.

The secondary compset is a wider ring, another five to ten hotels that are not your exact replacement but do mark the trend of the market. Maybe they sit a category above or below you, or in a neighboring area. You do not set your price by looking at them, but you do use them to read where the whole market is heading. If your primary and secondary move together, there is a real demand signal. If only your primary moves, it may be one competitor’s isolated move and not the market’s.

Compare price AND quality, never price alone

The most common silent mistake is building a compset that only watches rates. Price without context lies. If your neighbor charges less than you but has half your review score, you are not expensive, you are charging what your better product is worth. And if someone charges close to you but has a stronger reputation and more services, that competitor is more dangerous than their rate suggests, because the guest is getting more for the same money. Price only makes sense when you place it next to perceived quality.

The good news is that perceived quality is public and measurable. The average score on the OTAs, the total number of reviews, recent comments and the position in the local ranking are signals anyone can read. A hotel with a high score and thousands of reviews has a cushion of trust that lets it charge more without losing demand. Your compset should always log both columns together: at what price they sell and with what reputation they do it. A rate without its score beside it is half a truth.

  • Average score on the OTAs, not just yours but each competitor’s too.
  • Total number of reviews, because a high score with few reviews weighs less.
  • Recent trend of the comments, to see who is improving or slipping.
  • Included services, because breakfast, parking or transfers change the real value of the same rate.

The public signals from the OTAs

You do not need to spy on anyone. Booking platforms, channels like Booking or Airbnb, show valuable clues in plain sight if you know how to read them. The most obvious is the public rate for future dates, which is the raw material of rate shopping. But there is more. The “few rooms left” warnings, how often a hotel appears in promotions, the “in high demand for your dates” messages and the price differences between weekdays and weekends are all hints of how full or empty the competition is.

Read together, these signals tell you a lot about the pace of the market. If your primary compset starts flagging low availability for a long weekend several weeks out, that is your cue to hold or raise rate with confidence. If everyone still shows wide availability and aggressive promotions a few days before a date, the market is soft and lowering to fill may be the right call. The trick is not to watch one isolated signal, but the pattern of the whole group over time.

Common mistakes when building the compset

Beyond the aspirational compset, there are traps even experienced hotels fall into. The first is making it huge. A compset of twenty hotels looks more complete, but when you average twenty rates the result no longer resembles your real competition, only the average of the whole city. The second is building it once and forgetting it. The market changes, new hotels open, others drop a category, and a compset frozen in time makes you take decisions with an old map.

The third trap is comparing apples to oranges. Putting an all inclusive beach hotel and an urban business stopover in the same compset gives a meaningless average, because they sell different stays to different guests. The fourth is ignoring your own direct channel and looking only at the OTA, when part of your business and your competitors’ moves outside those platforms. And the fifth, the subtlest, is letting pride choose the compset instead of the data: measuring yourself only against who you want to resemble, not against who actually takes bookings from you.

  • A compset so large it averages itself into noise.
  • A list built once and never reviewed while the market changes.
  • Mixing hotels that sell completely different stays and guests.
  • Watching only the OTA and ignoring the direct channel, yours and theirs.
  • Letting ego, and not data, decide who enters the compset.

How often to review it

The compset runs on two different clocks, and it pays not to confuse them. The first is the fast clock: your competitors’ rates and signals change every day, so rate shopping must be daily, especially for near and high demand dates. There is no way around this, checking prices once a week is arriving late to almost everything. The second is the slow clock: the composition of the compset, meaning which hotels make up your list, does not change daily, but it should not stay fixed forever either.

A good cadence for LATAM is to review the composition of the compset every three months, and always when something big happens in the market: a new hotel opens near you, an existing one fully renovates and moves up a category, the season shifts hard, or you notice your numbers no longer match what the group is doing. That last clue is the most valuable. If your occupancy and your rate start to diverge from the compset for no apparent reason, it is almost always a sign that the compset no longer reflects your real competition and it is time to rebuild it.

From the list to the decisión

Building a good compset is half the work. The other half is turning that observation into action every day, and that is where revenue management stops being a spreadsheet and becomes a discipline. An honest compset, with price and quality side by side, read continuously, gives you the context. But context only helps if you cross it with your own occupancy, your booking pace and your pickup to set rate with a cool head and not a hunch.

That is exactly the line where a revenue management system like SENTINEL AI saves a LATAM team hours. Instead of manually reviewing each competitor’s rates and reviews every morning, it watches your compset continuously, shows you your position against the group, and translates the public market signals into a clear price recommendation. You still decide, always. What changes is that you decide with a clean, focused mirror, instead of an old, incomplete list chosen by pride rather than by the data.

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