Dynamic pricing in hotel management software: does it work?
Learn how dynamic pricing tools in popular PMS software work and why they might not be enough.
Dynamic pricing has garnered growing interest among hoteliers and property managers in recent years. The reason is simple: the post-pandemic period demonstrated that relying on fixed rates is no longer sufficient to stay competitive in an increasingly complex and evolving market.
For those lacking specific expertise or an in-house revenue manager, many managers have found valuable support in the dynamic pricing tools integrated into their PMS software.
Maybe this applies to you as well: your PMS offers a dedicated dynamic pricing feature, you’ve set it up, and you think the problem is solved. But is it really?
Not all dynamic pricing tools function the same way: the one included in your PMS may seem sufficient, but have you ever wondered how it actually works, what its limitations are, and what alternatives exist?
In this article, we’ll examine the two most common types of dynamic pricing: rule-based pricing and market-based pricing. We’ll explore how they work, their disadvantages, and the best approach for implementing a truly effective dynamic pricing strategy.
Rule-based dynamic pricing: what it is and how it works
A rule-based pricing approach refers to a system that adjusts prices according to manually defined rules set by the property owner or revenue manager.
These static rules operate rigidly, meaning the system updates prices only when predefined conditions are met.
Example rules:
- "If occupancy falls below 50%, reduce rates by 10%."
- "Increase prices by 15% on weekends or during local events."
Most systems allow the use of rules based on occupancy only. Even when other parameters are available, they are usually limited to the booking window, events, or specific days of the week.
Additionally, it’s often only possible to set a single rule for the entire property and season.
Limitations of rule-based dynamic pricing
While rule-based pricing may seem like a practical solution for adapting rates to predictable situations, it has significant drawbacks:
Lack of flexibility
Rules are static, meaning they remain unchanged unless manually updated. In a market with continuous fluctuations—like sudden demand spikes, unexpected events, or spontaneous competitors actions—this rigidity requires constant manual adjustments to be truly effective.
Complexity of variables
To consider all factors influencing demand, a property owner would need to create numerous rules requiring data often unavailable in rule-based systems (e.g., ADR, on-the-books data, or historical trends).
In addition, they would have to be able to manage these rules simultaneously and anticipate their cumulative effect on the final rate.
Generic pricing strategies
Rule-based systems often result in generic pricing strategies that fail to account for unique property characteristics, market changes, or customer booking behaviors.
Market-based dynamic pricing: what it is and how it works
Market-based dynamic pricing tools work similarly to rule-based ones but also incorporate data from the local market to inform pricing decisions.
In this case, a greater number of variables are taken into account:
- Competitors’ rates
- Competitor rate trends over time
- Demand fluctuations throughout the year
More rarely, you may also have data on events and estimated market occupancy.
Limitations of market-based dynamic pricing
Despite being more advanced than rule-based systems, market-based pricing has its own limitations:
Over-reliance on competitor pricing
Relying too much on your competitors can be risky: if they make pricing mistakes, you may end up replicating their bad decisions. In addition, simply "copying" the market does not allow you to differentiate and position your property based on its unique features and value.
Limited use of internal data
Market-based tools often overlook critical internal data, such as booking pace, guest behavior, or historical performance, limiting the ability to customize rates.
Complex configuration
These systems also require significant manual effort: setting base rates and adjusting parameters involves time, specialized skills, and ongoing market monitoring, increasing the risk of errors.
Dynamic pricing based on machine learning: what it is and how it works
As discussed earlier, the most common dynamic pricing tools in PMS software often fall short due to their rigidity, limited personalization, and time-consuming setup.
This is why, in most cases, the best choice is to use a third-party revenue management software that integrates with your PMS.
The most advanced solutions in this field are specifically designed to overcome the limitations of rule- or market-based approaches by leveraging artificial intelligence and machine learning algorithms.
What does machine learning mean in practice?
Instead of requiring the user to define specific rules to perform a task, these tools analyze large datasets and autonomously “learn” the rules to optimize prices.
Advantages of machine learning-based dynamic pricing
This approach offers unmatched precision, personalization, simplicity, and automation compared to traditional systems.
Unparalleled analytical capability
Machine learning algorithms can process vast amounts of data, both internal (e.g., booking pace, guest behavior) and external (e.g., local market trends), identifying recurring patterns and trends. They can also automatically detect holidays and events and their impact on room rates.
Maximum customization and simplicity
Modern dynamic pricing software is user-friendly, even without revenue management expertise. Once initial parameters are set, the algorithm continuously recalculates optimal rates automatically in response to changes in internal or market variables. This means that you maintain maximum control over the strategy at all times, but let the software do all the "heavy lifting".
If you’d like to learn more about how modern revenue management software works, download our free guide with practical examples and use cases.
Smartpricing is dynamic pricing and revenue management software that uses artificial intelligence and machine learning to enhance pricing strategies and simplify your work.
The result? Over 4,000 hoteliers and property managers who have chosen Smartpricing have achieved an average revenue increase of +30%.
Want to see how Smartpricing works and how it can help you? Request a free, personalized demonstration.
