By Adam and Larry Mogelonsky
The property management system has traditionally been the hub for storing hotel guest information. In today’s age of customer data platforms and extract-transform-load processes, the PMS has become a goldmine for machine learning and artificial intelligence-driven strategies.
The most prominent application of AI in this space is guest personalization. While this idea has long been at the forefront of AI discussions, it’s worth exploring further. AI enables a deeper level of personalization by democratizing the process, allowing hotels to tailor experiences based on specific guest profiles or situational contexts. With the right infrastructure, powered by automation and smart technology, hotels can deliver more personalized service at scale.
Consider how ML can be applied to PMS data when combined with other key sources like the CRM or POS systems:
- Analyzing booking history, billing details, and guest preferences to predict service needs or identify what could ‘surprise and delight’ the guest during future stays. This insight can also assist in error recovery or any service that benefits from real-time adjustments.
- Beyond the traditional use of algorithmic rate optimization, where revenue management systems already excel, ML can develop upselling strategies and purchase propensity models.
- Bridging sentiment analysis with rate strategy to create models for dynamic pricing and highly personalized marketing. For instance, identifying high-value customers and offering targeted promotions based on their lifetime value, even if it means offering introductory discounts as a loss leader.
- Enhancing loyalty programs through ML by offering more individualized perks, moving beyond the typical tier-based approach to deliver more compelling, personalized rewards.
A natural extension of these personalization efforts is AI-driven customer segmentation and microsegmentation. While conventional categories like leisure, corporate, and group travelers still hold relevance, they’re too broad in today’s fast-paced, data-driven environment. AI allows for more granular segmentation by testing assumptions and revealing what actually motivates specific types of guests to book and spend more during their stay.
Here’s how ML can improve customer segmentation:
- Create new audience groups or refine existing segments by verifying or challenging human biases, enabling hotels to better target high-value guests and optimize marketing campaigns.
- Conduct competitive benchmarking, revealing which properties are true competitors for different guest segments and uncovering areas for improvement.
- Use sentiment analysis from sources like social media or CRM tools to uncover correlations with PMS data, guiding pricing strategies, package creation, and marketing efforts.
As seen in these examples, AI-enhanced segmentation is closely tied to personalization, and many more use cases are bound to emerge as hotels embrace ML, generative AI, and other advanced technologies. A key factor in maximizing these opportunities is ensuring robust integrations—whether through CDPs, robotic process automation, or other tools—to unify siloed data sources for comprehensive insights.
Lastly, beyond personalization and segmentation, AI has the potential to drive significant operational efficiencies across various departments. For example, in accounting, AI can assist with error detection during audits or invoice processing. In housekeeping, predictive tools can forecast room readiness, optimize cleaning schedules, and refine staffing needs based on occupancy projections. AI can also help align staffing with citywide events, improving long-term scheduling. Moreover, large language models could soon be employed to interpret standard operating procedures or operations manuals, enabling faster customer support, micro-training, and real-time answers for team members working on specific tasks.
With so many applications emerging, it’s time to reach out to your tech vendors and explore how these tools can drive both guest satisfaction and operational success.
