Dynamic Pricing for Hotels: An Expert’s View on 2025 Trends

Dynamic pricing for hotels: An expert’s view on 2025 trends

Dynamic pricing is more than just a revenue management strategy—it’s part of a broader hotel technology trend, reflecting the industry’s shift toward data-driven innovation.

It’s a strategic way for hotels to respond to some of the hospitality industry’s most pressing challenges, from staffing shortages to unpredictable market and demand shifts.

Hotel experts increasingly view demand-based dynamic pricing as the most effective strategy for maximizing room profitability. One expert who agrees is Michael McCartan, EMEA Vice President at IDeaS, a leading hospitality revenue management system (RMS) provider.

In this article, Michael shares his insights on dynamic pricing, including its benefits and challenges, and how it can shape the future of hospitality.

Are you a hotel tech startup looking to build your brand’s reputation through strategic PR? Drop us a line.

What is dynamic pricing in the hotel industry?

Dynamic pricing is a key strategy in hotel revenue management. It automates continuous price adjustments to help hotels offer the right price to the right customer at the right time.

For example, a four-star hotel in a major tourist destination during peak season might charge a business traveler a premium price for a one-night stay in a suite. That same hotel might also offer a discounted rate for a standard room to leisure travelers staying multiple nights.

To understand dynamic pricing, Michael says it’s important to see it from a revenue management perspective: “Before hotels can dynamically price, with revenue management, they’re first trying to get a picture of what the demand looks like.”

This means hotels will explore demand from various angles, including:

  • Each customer segment
  • Future dates
  • Room types
  • Ancillary products, like meeting rooms and spa packages

Once hotels have a better understanding of demand, they can calculate price sensitivity—how rate changes will affect customer demand—to ensure they can attract and convert the most profitable segments. For instance, while a hotel might want to maximize room revenue, setting rates too high for a specific customer segment may create a drop in bookings and future demand.

This is where dynamic pricing models come in. Dynamic pricing software for hotels leverages AI to analyze historic and real-time demand and price sensitivity changes over time. Based on its findings, the dynamic pricing tool will automatically update rooms with optimal rates to capture fluctuating demand.

Let’s say a hotel receives a group booking during peak season that takes up 90% of its inventory. Dynamic pricing will enable hotels to be more aggressive with the rates of their remaining rooms because customers might be willing to pay more before the hotel sells out. In this case, dynamic pricing places a higher rate on the rooms left because there’s less availability and more demand.

This is how dynamic pricing can do the heavy lifting for hotels, continuously adjusting prices based on real-time pricing sensitivity and demand.

What are the benefits of dynamic pricing for hotels?

Michael says hotels can benefit from dynamic pricing in multiple ways:

  • Reduced workload. Dynamic pricing can automate much of the time-consuming manual analysis and forecasting to create optimal pricing in real time for all customer segments and date ranges.
  • Revenue optimization. With effective dynamic pricing, hotels can customize rates to capture the most valuable mix of customers, for example, long-stay bookings, group reservations, or high-value client segments.
  • Improved forecasting for data-driven decisions. Dynamic pricing relies on real-time data and advanced analytics to spot patterns, forecast demand, and predict price sensitivity. These insights inform a hotel’s rate and length-of-stay pricing strategies.
  • Increased profitability. By pricing rooms more strategically and adjusting them automatically (and quickly) based on real-time calculations, dynamic pricing can help generate higher overall revenue and profits compared to static pricing, which can miss opportunities for higher rates.
  • Competitive edge. With dynamic pricing, hotels can respond to market changes more quickly than competitors using static pricing models, which apply fixed rates that don’t change over time.
  • Improved customer experience. Dynamic pricing can help hotels offer more competitive and attractive rates to customers, providing an enhanced perception of value. Hotels can also better manage demand and availability, which creates a smoother booking experience for future guests.

Using the latest AI-driven revenue management tools, hotels can automate dynamic room pricing based on a holistic view of demand. This allows hotels to optimize their time, customer experience, revenue, and profitability more effectively while staying ahead of competitors yet to adopt smart hotel technology.

What separates modern dynamic pricing from the old-school approach?

Traditionally, hotels set high prices for high-demand days without considering the impact on longer stays. Modern dynamic pricing does the opposite, looking for ways to maximize revenue for all types of stays.

In the past, a revenue manager would adopt pricing strategies for individual dates. For example, if a hotel is usually busy on a particular Tuesday, the revenue manager might raise the price to the highest amount that customers would still consider reasonable.

However, Michael says this static approach can backfire because it doesn’t account for subtle changes in demand, like longer stays. Rates that are out of sync with real-time market changes can affect guest satisfaction, hotel reputation, and profitability.

Instead, modern systems forecast demand for different lengths of stays, not just single dates, to achieve a balance and optimize revenue and profit.

For example, the RMS will know that selling four nights is more profitable than a single night. It will then forecast demand and create pricing based on different lengths of stay, from one to four nights. But dynamic pricing may also see those one-night requests coming in faster than longer stays. To maximize revenue, it will put restrictions in place to encourage longer bookings first.

Michael sees dynamic pricing’s ability to fill in multiple dates to maximize profitability as akin to “playing Tetris, but with the advantage that you can see what size blocks of demand are coming through beforehand.” With dynamic pricing, “hotels can lay down the long stays to establish a solid base of business, then start plugging the gaps with the more expensive, one-night stays.”

Since dynamic pricing relies on extensive data analysis and insights to offer the right mix of rate strategies, from single dates to length-of-stay pricing, it can meet demand and customer expectations while maximizing hotel revenue. This approach sets dynamic pricing apart from old-school revenue management.

How does a revenue management system work, and what factors does it consider when forecasting demand?

Revenue management is a combination of forecasting demand and calculating price sensitivity to arrive at the optimal price for each customer for the rooms and products (e.g., spa treatments, upgrades) hotels are selling.

When forecasting demand, an RMS will analyze four main dataset types:

  • Historical data. An RMS will look at past data to understand reservation patterns, booking windows, pickup times (the rate at which bookings came in), and how different customer-segment bookings happen.
  • Current data. The RMS will compare past and present data to identify and match past patterns to current trends. If it sees similarities, it can optimize pricing based on this comparative analysis and the behaviors it recognizes.
  • Competitive analysis. The system evaluates the impact of competitor actions on hotel demand. For example, an RMS might see that demand for a hotel drops when competitor A lowers weekday prices, but not when competitor B cuts weekend rates. These insights help inform pricing decisions to gain a competitive edge.
  • Future trends. An RMS can analyze reservations already on the books and upcoming demand that hasn’t yet materialized in bookings to reveal trends. For example, if it detects a recurring seasonal pattern, it may slightly raise prices for the same period next year to optimize revenue.

In addition to these datasets, an RMS also considers conversion rates as a key factor in determining the right price. This involves setting a price based on historical and real-time data and pushing it to the hotel’s various channels to monitor the response.

According to Michael, it’s important to use the RMS to constantly monitor the appropriateness of each price. This approach creates a closed-loop system: setting a price, observing the booking pickup, and recalibrating the price if the expected results aren’t achieved. By continually refining the pricing strategy, hotels can optimize their revenue while adapting to real-time demand and customer behavior.

An RMS will combine these buckets of information to get a better picture of demand for the hotel and calculate rates accordingly.

What are the most common mistakes revenue managers make when using an RMS for the first time?

Revenue managers using an RMS for the first time risk human bias, which will lead to a divergence from the recommendations.

Michael says revenue managers are often anxious when using an RMS for the first time. They may feel their knowledge of the hotel and business outweighs the system’s recommendations, and insist on double-checking any updates before accepting them.

However, the more they intervene, the more likely they are to override the system’s pricing and inventory suggestions. While in some cases this manual intervention is justified and provides another data input for the RMS to refine its recommendations, the reality is humans can’t process the available information effectively and too many overrides neutralize the system’s effectiveness.

A University of Zurich 2023 study reveals the impact of human intervention on dynamic pricing—revenue captures improves by 2% when humans interrupt the dynamic pricing system compared to a 36% improvement when the RMS updates recommended prices automatically.

“This study concludes that the hotel may just as well have static pricing if the revenue manager has to manually approve decisions,” Michael says. “They lose out on real-time revenue opportunities because they’re preventing the RMS from updating the prices as soon as it forecasts demand and calculates rates.”

For example, if the RMS generates a recommendation at 8 pm but the revenue manager doesn’t see it until 12 hours later, that pricing decision may no longer be valid.

Michael recommends trusting the RMS’s recommendations, despite the temptation to override them, and adopting a fully automated, closed-loop decision system.

How can hotels find the perfect balance between automation and human input?

Balancing automation and human input isn’t an exact science, but hotels can take a management-by-exception approach to find the sweet spot.

Software like RMS can “capture and analyze thousands of data points that humans can’t manage or process as fast, humans can still choose to intervene at opportune moments and even challenge the output when it makes sense,” says Michael.

For example, some RMS like IDeaS feature built-in alerts and notifications that can highlight unusual events for human review before updating prices. This management by exception allows revenue managers to evaluate extraordinary occurrences on a micro level. Instead of having to analyze thousands of data points, a revenue manager will review an alert that encompasses a specific time frame for a certain room type based on unusual data.

IDeaS then enables revenue managers to run a “what-if” analysis scenario to simulate the consequences of the recommended price changes. Once they run a scenario test, they can decide whether to accept the recommended changes (because it provides a revenue opportunity) or override it.

Revenue managers can also take this approach a step further with IDeaS. If a hotel believes a proposed price will be detrimental to revenue, they can test another pricing scenario to understand if their decision is sound before putting it into effect.

Another example of management by exception is inputting additional information into the RMS to override the system’s recommendations and improve decision-making.

Let’s say the revenue manager expects to receive a group booking, which the RMS hasn’t picked up on yet because initial inquiries happened by phone. Since the revenue manager knows there’s a high chance of receiving this group booking, they want to increase rates. In this case, the revenue manager has more information than the RMS. By inputting that additional insight and overriding the system, they can improve the decision-making to optimize revenue.

Can boutique hotels benefit from dynamic pricing the same way that large hotel chains can?

While boutique hotels are increasingly looking to hospitality tech companies for solutions that can help streamline smaller operations without requiring large teams or budgets, they might not take dynamic pricing or RMS into consideration.

Because of their smaller size and fewer rooms, boutique hotels might think they can’t use revenue management. Yet a modern RMS can be as impactful for smaller boutique hotels as for large hotel chains.

It’s actually more important for a small hotel to price their rooms correctly because they have less inventory to play with. A pricing mistake, even for a short period, can cause a greater loss of revenue in a boutique hotel with 30 rooms than the same mistake in a large hotel with 150 rooms, where the impact on their top line is negligible.

“The closed-loop, real-time, and automated updating of prices can significantly benefit a small hotel because it ensures their pricing is positioned correctly all the time and they’re not missing valuable revenue opportunities,” says Michael.

Another misconception he sees is that boutique hotels don’t feel they have the in-house resources to benefit from a revenue management solution. But he says boutique hotels can easily address this by taking the time to set up the RMS correctly.

“It’s important for boutique hotels to build a solid foundation for their RMS. A correct setup enables boutique hotels to automate their strategy, even without in-house resources to actively revenue manage on a daily basis.”

Boutique hotels can also consider outsourcing. A consultant who understands the RMS can run the revenue management for them. However, boutique hotels shouldn’t think consultants need to work on this every day. To be effective, the RMS needs to run independently with as little intervention as possible, as long as it is set up with a proper framework.

With IDeaS, boutique hotels can receive support in implementing the correct setup during the onboarding process, and training to help them get started on the right foot.

Transforming hotel revenue management with dynamic pricing

Dynamic pricing is transforming the way hotels approach revenue management. With automation, machine learning, and data-driven insights to drive price optimization, hotels can adapt quickly to demand fluctuations, maximize profitability, and stay competitive.

As the hospitality industry continues to evolve, embracing these advanced pricing tools will be key to shaping the future of revenue management.

Are you a hotel tech startup looking to build your brand’s reputation through strategic PR? Drop us a line.

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