The hospitality industry's revenue management seems promising with the integration of AI-based systems. Classic dynamic pricing, primarily based on rules, is now evolving into AI pricing. This complementary method utilizes algorithms to quickly identify and evaluate relevant market movements and influencing factors from various data sources.
Ideally, the software recognizes demand flows and makes automatic price adjustments. Experts believe implementing AI in revenue management is crucial for long-term success in the hotel industry. Finding the right balance between human judgment and AI support is essential. To adequately utilize advances in AI to increase sales, the hotel industry needs to adopt an appropriate software solution that already has AI integrated.
Benefits of AI in Revenue Management in the Hotel Industry
- Real-time adjustments: AI systems can adjust prices and availability in real-time to react to market demand, exploiting their full potential.
- Personalization: Hotels can create personalized offers by analyzing guest data during search and booking.
- Forecasting and data analysis: AI can analyze large volumes of data to identify patterns and trends, allowing for more accurate forecasting of future demand and pricing.
- Time savings: Automated processes reduce workload, allowing employees to focus on strategic tasks.
While AI has its own advantages, some challenges must be overcome. The effectiveness of AI systems depends mainly on the quality and timeliness of the data they use, whether the hotel's internal or market data. Employees must have additional specialist knowledge to ensure transparency about the use of AI and data protection. Therefore, hotels must regularly invest in training and further education.
Finding the right balance between human judgment and AI support is crucial for revenue management. Even though the widespread use of AI will undoubtedly change the job market fundamentally, experienced revenue management experts are still needed.
The future of hotel revenue management through AI-based systems is promising. However, a fully cross-departmental approach is the next stage of development. Some price recommendation systems can do a lot, but as a hotel becomes more complex by serving more market segments and secondary outlets, demand assessment becomes more complex, too. This necessitates the use of AI-supported revenue management software. While high prices can optimize yields, they are not the only goal. The cost and occupancy must maintain a healthy relationship with each other. The ultimate goal is to increase income by maximizing utilization at the best possible price and reducing workload.
