They are generally circled out in any hotel commercial team’s calendar as critical points to drive revenue and consequently you must have the right strategy in place.

A core part of this is understanding rate evolution up to the event date, especially as these events buck normal demand patterns, introducing new variables into the revenue management equation.

With this in mind, it’s time to go on a deep dive and show you how major events can affect hotel market pricing.

The typical rate evolution: Prices rise as the stay date approaches

Let’s first look at how hotel room rates normally develop up until the stay date, where major events aren’t involved, by looking at some of the world’s most popular destinations for tourist arrivals.

For this we will use a snapshot examining Bangkok, Dubai, London, New York, Paris, Rome, Singapore and Tokyo. It looks at average rates in these cities over a 120-day period prior to the point of stay across a 90-day historical selection before the time of writing, which was in April 2024.

— Source: Lighthouse (formerly OTA Insight)— Source: Lighthouse (formerly OTA Insight)
— Source: Lighthouse (formerly OTA Insight)

This produces a broad, repeating pattern where rates are largely discounted in the run up to the stay. The difference between the final price and discounted rates reduces as the stay date approaches and inventory sells out, with prices rising steeply in the two weeks before a guest arrives.

In the case of New York, Paris and Tokyo, rooms are, on average, priced above the very final price listed by a few percentage points in the last week before the stay.

The principal behind this is simple: as we move closer to the stay date, the room is less price elastic and there should be less supply in the marketplace as bookings accumulate.

That lower supply means the goods are scarcer and therefore prices can be pushed up.

Then, the necessity of the stay, and the falling availability of substitutes and time to find those alternatives for travelers, means the good becomes increasingly inelastic as we approach the stay date which is why the curve is exponential in most cases, rather than linear, with prices increasing to a greater degree the closer to the stay we get.

Although in the above example there is a wide variation in the rates posted, with the smallest discount falling at just 2% below final price in Paris but up to 18% in Bangkok, this is the general rule regarding room rate evolution for stay dates in locations where major events aren’t taking place.

When we looked at wider data sets across regions, the above trendline held whether it was in Asia-Pacific or South America.

Higher market demand, demands higher hotel prices - but is it that simple?

What happens when we introduce a high demand generating event into a location?

Does it shorten the period of discounting relative to the price on the date of stay? Does it increase the rate at which prices climb pre-stay?

It seems logical to expect the same shape of evolution but with a more exaggerated curve.

However, the true shape of the pricing curve during the moment leading up to major events is typically inverted: prices are set high and then fall closer to the stay date.

Although, this is not a hard and fast rule for every event, it is a recurrent trend.

For this analysis we picked a broad range of events of different types and across different geographic locations, including musical festivals, sporting events, carnivals and major national vacation points. These are:

  • The Sziget Festival in Budapest on 10th-15th August 2023.
  • Memorial Day in Orlando on 26-29th May 2023.
  • The Rugby World Cup semi-finals in Paris on 20-21st October 2023.
  • The Austin City Limits Festival on 6-15th October 2023.
  • The Sapporo Snow Festival on 4th-11th February 2024.
  • The Super Bowl in Las Vegas on 11th February 2024.
  • Mardi Gras in New Orleans on 9-13th February 2024.
  • The Melbourne Grand Prix on 22-24th March 2024.
— Source: Lighthouse (formerly OTA Insight)— Source: Lighthouse (formerly OTA Insight)
— Source: Lighthouse (formerly OTA Insight)

We can see that across these events, prices are higher further out from the final stay date. Hotels then cut rates as the key dates approach, with major reductions typically introduced for final remaining inventory in the last two-to-three weeks.

Averaging out across these eight events, the highest price point is 110 days out from the event, which in normal demand periods is way beyond the average point at which travelers even begin their initial research for their trips.

For events with extremely strong demand held over a very limited time period, such as the Super Bowl or Melbourne Grand Prix, that last-minute discounting is steep and focused on the final week-and-a-half.

In Vegas, hotels were priced 38% higher nine days out from the final stay date during Super Bowl weekend and 22% higher in Melbourne, before being cut down depending on how the booking curve was developing. The largest average cut for these two cities was between four and three days out from the stay in Las Vegas, when hotels cut prices by 13% overnight on average.

Curves were less steep when in-demand dates are more spread out and when there is more inventory choice.

For example, at the Sziget Festival in Budapest there are a substantial number of on-site camping tickets available over the six-day event run and Memorial Day travel in Orlando is less concentrated, with tourists potentially arriving over a two-week period and for different blocks of time, which might help to explain why they sit at the bottom of our chart.

The 2022 FIFA World Cup in Qatar also offers a fascinating case study. As Doha braced for the tournament in November and December hotel prices initially surged until mid-October, only to witness a downturn as the event came closer.

By November 9th, Doha's hotel rates (looking 60 days into the future) had plummeted by a significant 34% compared to the preceding month, a trend that extended into the tournament's duration. Contrary to expectations, the World Cup's global appeal didn't uphold the initially high pricing, leaving hotels with more vacancies than anticipated.

In response, hoteliers strategically reduced prices to attract last-minute bookings and optimize occupancy.

This scenario underscores the importance of data-driven decision-making in the hospitality industry, particularly for revenue managers navigating the ever-changing currents of demand and pricing.

The destination booking curve and competitive landscape dictates the hotel room rates

While large influxes of travelers for specific events typically invert the pricing pattern up to the point of stay but as we mentioned above this is not set in stone.

Hotel room pricing is of course dependent on market conditions, and therefore competitor pricing and demand development relative to norms, are also key factors to consider.

Let’s take a look at how demand and pricing developed in Bangkok in the run-up to the Lunar New Year holidays in 2024.

Pre-pandemic, this was a major demand-generating event, but high dependency on Chinese travelers hit bookings hard. Finally, in 2024 bookings exceeded where they were in 2019 and were massively higher this year in Bangkok compared to 2023 as Chinese travelers went abroad en masse.

This was especially so as in 2024 the official holiday period was eight days rather than the usual seven, further incentivizing international trips.

It was therefore a predictable point of raised demand and likely to be a critical period for Bangkok hotels to maximize possible revenue.

— Source: Lighthouse (formerly OTA Insight)— Source: Lighthouse (formerly OTA Insight)
— Source: Lighthouse (formerly OTA Insight)

However, we see a more typical pricing curve shape and that it was more steeply discounted a month out from the stay than was the average throughout 2023, with rooms priced more than 30% under the final rate until 33 days before arrival.

So, what was happening here and why is it dramatically different to the other events we have looked at?

Well, firstly revenue managers in Bangkok have been coming off several years of depressed demand in the post-pandemic environment, and Chinese travel did not immediately return in the way many hoped after the Xi Jinping government lifted travel restrictions.

This pushed the market to be cautious in its pricing strategy, especially as this is a competitive space, with regional markets also keen to attract prized Chinese tourists.

Then, let’s combine that with how the booking curve was developing. While bookings were above the average curve in 2023, there is a noticeable gap compared to some of the other major events we have looked at when it comes to very early on-the-books reservations.

— Source: Lighthouse (formerly OTA Insight)— Source: Lighthouse (formerly OTA Insight)
— Source: Lighthouse (formerly OTA Insight)

While occupancy in Bangkok for Lunar New Year was 15% at the start of 120-day window compared to the 8% average seen in the city across 2023, hotels in New Orleans were 35% booked for Mardi Gras and 53% in Melbourne for the Grand Prix, compared to an average of 10% and 14% at 120 days out in 2023, respectively.

Once bookings begin to come in very rapidly in Bangkok from 40 days out from the stay, then there is a slight lag, but we can clearly see revenue managers across the city responding and rates heading upwards.

However, if revenue managers in Bangkok were using predictive analytics taking into account market demand, pricing and occupancy, they would have had a more incisive view of their destination.

It would have enabled them to spot that market occupancy was double compared to the average in 2023 and as a result could have been relatively aggressive when setting rates. Especially as all of these events ended up having very similar occupancy rates of 91-92%, which is typical for major events in the analysis.

Final thoughts

These examples reinforce that even if a high-demand period is coming, it is not independent of market conditions and is contextual to the environment. This leads to wide variation from location to location, even if there is a general pattern in most cases for periods of elevated demand tied to a specific event.

This makes real-time market intelligence critical for setting accurate room rates that reflect emerging demand, on-the-books reservations and competitor behavior.

The Lighthouse commercial platform has been built with hoteliers' needs in mind. We combine a comprehensive range of data sets, from competitor pricing to predicted market demand and occupancy, into actionable insights, displayed in easy-to-read dashboards.

That way you are always best positioned to capitalize on events in your market and drive maximum revenue, no matter what the market conditions.

About Lighthouse

Lighthouse (formerly OTA Insight) is the leading commercial platform for the travel & hospitality industry. We transform complexity into confidence by providing actionable market insights, business intelligence, and pricing tools that maximize revenue growth. We continually innovate to deliver the best platform for hospitality professionals to price more effectively, measure performance more efficiently, and understand the market in new ways.

Trusted by over 65,000 hotels in 185 countries, Lighthouse is the only solution that provides real-time hotel and short-term rental data in a single platform. We strive to deliver the best possible experience with unmatched customer service. We consider our clients as true partners—their success is our success.

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