Hotels have always watched their competitors’ room rates. It’s a useful reference point when setting their own prices, but it tells them nothing about why another hotel is charging what it does.
A neighboring hotel might lower its rates because it’s struggling with occupancy, while another could simply be following an outdated pricing strategy. Neither decision necessarily reflects demand across the wider market.
As more pricing decisions become automated, that lack of context creates a new risk. Imagine a hotel lowering its rates to fill a few remaining rooms on an unusually quiet Tuesday. A neighboring hotel’s pricing system picks up the change and responds. Other hotels then see several competitors lowering their prices and adjust too.
What began as a decision specific to one property could create a feedback loop, driving prices down across a market even though overall demand hasn’t changed.
Are hotels putting too much faith in their competitors?
A competitor’s rate is a single data point, and it might not be a particularly good one. A hotel charging $120 could be struggling to fill its rooms, or it could be almost fully booked and failing to maximize revenue. It might have a sophisticated pricing strategy, or it might barely practice revenue management at all.
Yet competitor rates carry considerable weight in hotel pricing decisions. Our recent research found that 51% of hoteliers consider competitor rates a very influential factor in their pricing, just one percentage point behind demand forecasts. That’s a lot of weight to give a number when you know so little about what’s behind it.
Good pricing systems consider booking pace, remaining inventory, and demand forecasts. But if they put too much weight on competitor rates, they risk following price changes that have little to do with wider market demand.
A revenue manager might see a rival’s sudden discount and question whether there’s a good reason to respond. An automated system configured to follow competitor prices could make that adjustment almost immediately, potentially across several dates. If enough hotels take the same approach, they could end up responding to each other’s algorithms rather than changes in actual guest demand.
The danger of looking backwards
Competitor rates aren’t the only numbers that can send hotels in the wrong direction; last year’s performance can be just as misleading. Many hotels compare today’s occupancy with where they stood twelve months ago, but shorter booking windows can distort that comparison.
A hotel might be behind last year’s booking pace and assume it needs to discount, even though guests are simply booking later. Worse, competitors could interpret that discount as a sign of weakening demand and lower their own rates too.
This is where hotels need to be careful about reacting too quickly. A slow booking week doesn’t automatically mean the price is wrong. Hotels should pay closer attention to current booking patterns, including cancellations, which room types are selling and occupancy over the coming weeks, before deciding whether a rate change is necessary.
More data doesn’t always mean better decisions
Automation can process more information than any revenue manager could reasonably analyze manually, but that doesn’t mean every signal deserves equal weight. Take Airbnb rates. For a five-room property fighting short-term rentals for the same guest, that number is gold. For a fifty-room hotel with a completely different guest, it’s noise. One hotel’s treasure is another hotel’s trash, and a system that weights them the same isn’t doing you any favors.
This is where revenue management becomes more nuanced. A hotel’s own booking pace and remaining inventory should carry significant weight. If you’ve only got three rooms left to sell, you’re in a very different position from a competitor with thirty. Matching their discount could mean giving away revenue on rooms you were likely to sell at a higher rate anyway.
Local demand can also provide an early indication of changing conditions. Around Cascais, outside Lisbon, summer temperatures can be five to ten degrees cooler than in the city. When a heat wave hits during the school holidays, many people decide at the last minute to leave Lisbon for the coast. A hotel monitoring local conditions and its own bookings may spot that shift before it shows up in competitors’ prices, giving it an opportunity to increase rates.
Knowing when to leave your rates alone
Hoteliers often feel pressure to act whenever bookings slow or competitors change their prices. But holding a rate while assessing the evidence can be just as sensible as changing it. One of the most valuable things a revenue management system can do is help a hotelier understand when a price change is actually warranted. Sometimes the right decision is to increase rates, sometimes it’s to lower them, and sometimes it’s to leave them exactly where they are.
For independent hoteliers, automation can take much of the daily work out of revenue management and help them make decisions they might otherwise lack the time or expertise to make. But that doesn’t mean handing over every decision without understanding what’s driving it. Hoteliers should be able to see why their system is recommending a particular rate. Is demand picking up? Are rooms selling faster than expected? Or is the recommendation mainly a response to what another hotel is charging?
The best systems should help hoteliers make sense of these signals and give them the confidence to stick with their strategy when the evidence supports it, even if competitors are moving in a different direction.
Competitor rates will always have a place in revenue management. But if a competitor’s price is influenced by another hotel’s algorithm, which is itself responding to someone else’s pricing decision, how much does that price really tell you about demand?
