Prediction: How Much More Can AI Improve Revenue?
For many hotels, the ability to predict demand and adjust pricing dynamically is already a significant competitive advantage. Many hotels already use advanced revenue management systems (RMS) incorporating various data sources—competitor pricing, local events, online behavior, macroeconomic trends, and weather patterns. These incredibly sophisticated systems have a proven track record of driving profitability through accurate demand forecasting and dynamic pricing. A hotel with a solid Revenue Generation Index (RGI) above 1.00 already captures more of the market than its competitors. So, why would such a hotel consider adopting an AI-driven solution?
Marginal Gains vs. Investment
While AI can offer some incremental improvements, for many hotels, especially those small to mid-sized properties like a 100-room hotel, the benefits may not be substantial enough to justify the investment. Here’s why:
- Current RMSs are Advanced: Today’s RMSs go beyond essential demand forecasting. To optimize room rates, they analyze competitor pricing, local events, guest behavior, macroeconomic trends, and even weather data. AI might offer marginal improvements in prediction precision, but these gains—perhaps only 1-2%—are unlikely to revolutionize an already well-optimized system.
- Cost vs. Return on Investment (ROI): Switching to a total AI-driven solution involves a significant financial investment in implementation costs and ongoing system management. For a hotel already performing well, the potential uplift in revenue from AI-driven predictions might not offset these costs. The marginal revenue gain may not be enough to justify the expense.
Future Proofing with AI Enhancements in RMS
The good news for hoteliers is that many RMS providers are already beginning to integrate AI features. Rather than switching to an entirely new system, hotels can benefit by upgrading their existing RMS as vendors roll out AI-powered improvements. This approach allows hotels to access AI-driven precision without the heavy costs of a complete system overhaul.
When Might AI in Prediction Be Worth It?
There are specific scenarios where AI-driven prediction systems may have a more substantial impact:
- Large hotel operations with hundreds or thousands of rooms, where even small percentage improvements in forecasting or pricing can yield significant financial gains.
- Highly competitive markets, where a hotel needs every possible edge to capture incremental market share.
- Complex hotel operations with multiple revenue centers—such as resorts with F&B, spas, and activities—where AI might better optimize total revenue across departments.
For most small to mid-sized hotels, the incremental benefits of AI prediction may not yet justify the switch. Instead, focusing on incremental enhancements to existing RMS will allow hotels to stay competitive while adopting AI features over time as they become more accessible and cost-effective.
Improving Predictions with Better Data: The First Step for Hotels
Whether a hotel uses an advanced revenue management system (RMS) or an AI-driven solution, predictions are only as accurate as the data that feeds into these systems. One of the quickest and most impactful ways to improve predictive accuracy is to ensure that the data going into the system is high quality. Unfortunately, many hotels still lack robust data management processes, which limits the effectiveness of even the most advanced technologies.
The Importance of Data Quality
RMS and AI solutions rely heavily on historical data, real-time inputs, and external factors to make accurate predictions. Even the best systems will struggle to produce reliable forecasts if the underlying data is incomplete, outdated, or inaccurate. Data consistency, completeness, and accuracy are essential for driving better predictions.
Steps Hotels Can Take to Improve Data Quality
- Audit Data Sources:
- Begin by reviewing all the data sources feeding into the RMS or AI solution. This includes Property Management Systems (PMS), point-of-sale systems, guest feedback platforms, booking engines, and external data sources like market trends or competitor pricing.
- Make sure that these data sources are accurate, up-to-date, and free from duplicate or conflicting data.
- Implement Standardized Data Entry Procedures:
- Inconsistent data entry practices often lead to incomplete or incorrect data. Ensure all teams—front desk, reservations, sales, and housekeeping—follow standardized data entry protocols.
- Define what data fields are mandatory and ensure employees are trained to input data consistently.
- Automate Data Collection:
- Manual data entry is prone to errors. Where possible, automate data collection from various systems to reduce human error. For instance, integrating systems like PMS and RMS can ensure seamless data flow without the risk of mistakes during manual transfers.
- Monitor and Clean Data Regularly:
- Even with standardized procedures and automation, regular data monitoring is necessary. Set up data quality checks to identify and correct errors, missing information, or inconsistencies.
- Invest in periodic data cleansing initiatives to remove obsolete or inaccurate data that could skew forecasts.
- Use Real-Time Data:
- The speed at which data is updated also affects prediction accuracy. Ensure your systems can ingest real-time data, especially demand forecasting and dynamic pricing.
- This real-time data includes market fluctuations, competitor rates, and real-time booking behavior.
- Leverage Guest Data:
- Hotels often overlook the wealth of data from guests, including their preferences, booking patterns, and feedback. By incorporating guest data into the prediction process, hotels can anticipate guest behavior, such as the likelihood to book, cancel, or return, and adjust marketing efforts and pricing accordingly.
A Focus on Data Management: The Key to AI-Driven Success
Before investing in new AI-driven systems or upgrading current RMS solutions, hotels should focus on building a solid data foundation. A robust data management strategy will ensure that predictions from RMS or AI are far more accurate and actionable. Hotels that take the time to implement these processes will see immediate improvements in forecast accuracy and be better positioned to leverage future AI advancements.
Classification: Elevating Guest Segmentation and Marketing Precision
In most hotels today, guest segmentation is done manually by assigning segment codes in the Property Management System (PMS), such as categorizing guests into business, leisure, group, or transient segments. Similarly, hotels track the distribution channels—direct bookings, OTAs, corporate travel agents—that drive their reservations. This classification level gives hotels valuable insight into guest behavior and channel performance.
Improving Classification with High-Quality Data: A Critical Step for Hotels
AI can only take classification to the next level if hotels provide high-quality data. Even the most advanced AI systems will struggle to deliver meaningful insights without accurate, clean, and well-structured data. Unfortunately, one of the biggest challenges in the hotel industry today is the low quality of data stored in siloed systems. Many hotels still rely on disconnected platforms, manual data entry, and inconsistent data practices, which limit their ability to leverage AI effectively.
Hotels need to invest in data quality for AI to identify patterns and trends that are difficult—if not impossible—to see manually. AI’s power lies in its ability to quickly process large amounts of data and categorize it based on subtle, multi-dimensional factors. This can significantly boost a hotel’s ability to optimize marketing, distribution, and operations, but only if the data it receives is complete, accurate, and integrated across systems.
Why Data Quality is Crucial for AI Success
Hotels that do not prioritize high-quality data will not be able to reap the full benefits of AI. Poor data quality leads to unreliable predictions, inaccurate segmentation, and inefficient operations. To ensure that AI systems deliver value, hotels must:
- Break down data silos by integrating data from all systems, including PMS, CRM, and booking platforms.
- Implement standardized data entry protocols to ensure consistency.
- Regularly audit and cleanse data to remove duplicates, errors, and outdated information.
Without this foundation, any investment in AI will be ineffective. A hotel that cannot provide high-quality data will not be able to fully leverage AI’s capabilities, and the potential benefits—such as improved guest segmentation, personalized marketing, and optimized channel strategies—will remain out of reach.
What More Can AI Do?
Here are several ways AI can enhance classification in hotels:
1. Deep Guest Segmentation Beyond Manual Codes
While hotels may segment guests into basic categories such as corporate, leisure, or group, AI can go much deeper. AI can analyze various data points, from booking behavior, spending patterns, and length of stay to online behavior, to create more granular guest segments. For example:
- Micro-segmentation: AI can classify guests by broad categories and specific preferences, such as business travelers who book last minute or leisure travelers who always book during holidays but look for room upgrades.
- Predictive segmentation: AI can classify guests based on their future behaviors, such as identifying those most likely to book again within a specific period or those who are likely to churn without targeted offers.
2. Identifying High-Value Guests
Beyond simple VIP or loyalty statuses, AI can help identify high-value guests that may not be immediately visible through manual classification. For example, AI could identify guests who, while they may book less frequently, tend to spend more on ancillary services such as dining, spa treatments, or other premium experiences. This allows hotels to focus marketing and guest services on individuals who deliver the most value to the business.
3. Identifying At-Risk Guests
AI systems can classify guests likely to churn based on various indicators—such as booking frequency, average spend per visit, or lack of interaction with loyalty programs. Once identified, these at-risk guests can be targeted with personalized offers to re-engage them before they defect to competitors.
4. Channel and Distribution Strategy Optimization
While hotels already classify distribution channels, AI can take this further by analyzing the performance of each channel in greater detail, including:
- Booking lead times, conversion rates, and average revenue per channel.
- Channel profitability: AI can classify the volume of bookings and the profitability of each channel by factoring in acquisition costs, commission fees, and guest lifetime value. This insight can help hotels focus on the most profitable channels rather than just the highest-volume ones.
- Market and Channel Dynamics: AI can help hotels understand how distribution channels perform under varying market conditions. For instance, specific channels may deliver more profitable bookings during high-demand periods, while other channels may provide better reach during off-peak periods. AI can classify these patterns and help hotels adjust their channel strategies dynamically to maximize profitability.
- Channel Churn Prediction: AI can also help identify channels at risk of underperformance, enabling hotels to proactively address issues with distribution partners or invest more heavily in marketing on channels that are expected to perform better in the future.
5. Personalized Marketing Campaigns
While hotels already segment their marketing efforts based on broad guest categories, AI allows for more targeted marketing by automatically classifying guests based on their preferences and behavior. For example:
- AI can analyze a guest’s past stay history, booking methods, and ancillary spending to classify them into more specific marketing segments.
- Dynamic targeting: Instead of sending a generic marketing campaign, AI can classify guests and send highly personalized messages, such as offering room upgrades to frequent leisure travelers or special packages to business travelers who often extend their stays.
This degree of personalization can result in higher engagement rates, increased direct bookings, and greater guest loyalty by ensuring the right message reaches the right guest at the right time.
6. Classifying Operational Needs Based on Guest Behavior
AI’s classification capabilities can extend beyond guest marketing and booking trends into operational efficiency:
- AI can classify guests based on their likely service preferences, such as which types of rooms they prefer, whether they are more likely to dine at the hotel restaurant, or which amenities they’re likely to use. This allows hotels to optimize resource allocation, ensuring that staff, amenities, and services are tailored to the specific needs of incoming guests.
- AI can also classify patterns for peak check-in times, food and beverage demand, or even the need for specific housekeeping services, leading to better scheduling and inventory management.
Why AI-Driven Classification Matters for Profitability
By using AI to classify guests, booking channels, and operational needs with more precision, hotels can make more informed and strategic decisions that positively impact their profitability. Instead of relying solely on manual codes or static reports, AI-driven classification enables hotels to be more proactive:
- Higher guest satisfaction due to personalized offers and services tailored to their needs.
- Increased conversion rates by identifying high-value guests and sending more relevant marketing messages.
- Optimized channel strategies by focusing on the most profitable distribution partners.
- Improved operational efficiency through better forecasting of guest behavior and resource needs.
Ultimately, AI helps hotels move beyond basic segmentation and manual classification, enabling a more data-driven approach to managing guest relationships, marketing strategies, and operational logistics. This results in higher profitability by ensuring that hotels get the most value from their data, marketing efforts, and guest services.
Taking the First Step: Leveraging Business Intelligence Tools like Demand Calendar
Before diving into full AI-driven solutions, many hotel groups can improve their operations and profitability by adopting sophisticated business intelligence tools such as Demand Calendar. Demand Calendar is explicitly designed for hotels, offering advanced features and functions that allow hotels to analyze, classify, and present data insights effectively—much like the classifications we’ve discussed earlier.
For example, Demand Calendar already has the capability to:
- Segment guests based on various factors, such as booking behavior, length of stay, spending patterns, and combinations to identify micro-segments, allowing for more targeted marketing and sales strategies.
- Analyze distribution channels, giving hotel managers a clear view of where bookings are coming from, which channels are most profitable, and how to adjust strategies accordingly.
- Optimize revenue through total revenue forecasting tools that align demand predictions with pricing strategies, ensuring the hotel captures every revenue opportunity.
Using Demand Calendar, hotel groups can benefit from many of the classification and prediction capabilities typically associated with AI without making a massive leap into entirely new systems. It’s an ideal starting point for any hotel group looking to improve their data-driven decision-making and lay the groundwork for more advanced AI implementations.
A Practical First Step
Adopting a powerful business intelligence tool like Demand Calendar is a practical first step for many hotels, especially those in the early stages of data management improvement. It consolidates data from multiple sources, eliminates manual data entry, and provides instant access to actionable insights. Once a solid data management foundation is in place, the path to more advanced AI solutions becomes clearer and more achievable. Demand Calendar will continue implementing AI features to help hotels grow revenue and maximize profits.
Conclusion: Preparing for AI in Hotels with High-Quality Data and Business Intelligence
AI has the potential to transform hotel operations through improved prediction and classification. Still, the success of any AI-driven solution is heavily dependent on the quality of the data that feeds into it. For many hotels, the most immediate step toward harnessing the power of AI is not a massive technology overhaul but rather ensuring that they have solid data management practices in place.
A practical first step for hotels is adopting sophisticated business intelligence tools like Demand Calendar. With features that already allow for advanced classification, demand forecasting, and channel analysis, Demand Calendar enables hotels to unlock many of the benefits associated with AI without the steep investment or disruption of switching to entirely new systems. By consolidating data, improving accuracy, and providing actionable insights, Demand Calendar helps hotels build the strong data foundation necessary to fully leverage AI in the future.
Key Takeaways:
- AI in Prediction: AI can improve forecasting and pricing strategies. However, smaller hotels will only realize real gains if they first ensure high data quality and integrated systems.
- AI in Classification: AI can offer deep guest segmentation and optimized channel strategies, but only with access to structured, high-quality data. Business intelligence tools like Demand Calendar can help with many of these tasks.
- Demand Calendar as a First Step: Adopting a powerful business intelligence tool like Demand Calendar is an excellent first step for hotels. It provides many classification and analysis capabilities needed to optimize operations and can serve as a stepping stone toward more advanced AI solutions.
- Data Quality is Crucial: Hotels should focus on improving data quality before investing in AI. A solid data foundation will ensure AI systems deliver the best insights and results.
By improving data quality and leveraging tools like Demand Calendar, hotels can start reaping the benefits of AI-driven insights today, laying the groundwork for future growth and profitability.
