How decision intelligence unlocks hotel data for better insights

For years, the gold standard guiding business strategies for hotels has relied heavily on historical data, analyzed a few times a year (at best), making it difficult to swiftly respond to changing market conditions. 

While better than operating without data, this approach is reactive and inefficient, resulting in missed opportunities. Thankfully, things are changing, and with the introduction of decision intelligence powered by next-generation AI, hotels will be equipped with the information they need to make proactive, game-changing decisions. 

In this article, we explore what decision intelligence is and the transformative effect it’s bound to have across demand optimization, segmentation, operations, and training and enablement. 

But first, listen to Nikhil Shah, Head of Data Science at Cloudbeds, and Eric Ellis, Senior Director of UX Design at Cloudbeds, discuss how the industry is moving from simplistic to intelligent decision-making with the help of causal AI. 

Decision intelligence platforms integrate various data sources, apply predictive and prescriptive models, and offer insights for real-time decision-making. For hotels, this includes making dynamic rate suggestions and identifying segments and offers for marketing campaigns. 

For example, Cloudbeds Intelligence analyzes billions of future-looking data points, including competitor rates, events, holidays, and search information, combined with a property’s own data to understand how every combination impacts profit. 

From here, the platform makes intelligent suggestions backed by data, like increasing your rate due to demand (from a Taylor Swift concert, for example) and pace. This can be done across functions, including distribution, marketing, guest experience, operations, and finance. Hotels can then accept (or deny) these suggestions, resulting in fast, accurate decision-making.

5 key features of decision intelligence platforms

Decision intelligence offers several advantages over traditional data analytics.

1. Integrated approach to data

Decision intelligence uses ML to analyze historical data patterns and predict future trends. It goes further by integrating data from multiple sources, including feedback on the outcomes of past analyses and decisions. 

Why it’s important for hotels?

This feedback loop improves data quality, resulting in more complete, up-to-date, and accurate information. 

2. Scalable decision-making

Thanks to the continuous integration of larger and more diverse data sets and the use of advanced algorithms, DI becomes more powerful and accurate over time.

Why it’s important for hotels?

This scalability is especially valuable for hotels – as more information is collected about guest behavior, booking trends, and occupancy patterns the more precise rate adjustments, inventory management, and marketing strategies will be in the future. 

3. Accessible process

Instead of organizing and analyzing data manually, DI provides ready-to-act insights in an easy-to-understand format, making complex decision-making more accessible to non-technical users.

Why it’s important for hotels?

These platforms often provide automated insights and alerts that proactively notify decision-makers. For example, if occupancy suddenly drops, the platform sends an alert with a suggested offer and segment. 

4. Real-time decisions

Unlike traditional analysis, which relies on periodic reports, AI/ML models automate or augment decision-making for real-time responses to emerging trends and conditions. 

Why it’s important for hotels?

If there’s a sudden change, for example, an influx of last-minute bookings hits the system, the platform can enable revenue managers to adjust room rates dynamically to maximize revenue. 

5. Collaboration

Decision intelligence provides a single, integrated platform where all teams have access to the same data, insights, and performance metrics. 

Why it’s important for hotels?

This creates a more collaborative environment between departments that traditionally have separate goals, such as revenue managers and guest services or marketing and operations teams.

The value of decision intelligence for hotels

Since hotels began digitizing their operations, the challenge has not been accessing data but harnessing that data to make decisions. Consider booking patterns, cancellation rates, average length of stay, guest preferences for room amenities or dietary restrictions, website and app metrics, competitor rates, and market trends—the list goes on. 

With decision intelligence, hotels can analyze all of this data collectively, uncovering new insights and cause-and-effect relationships. 

Practical applications include:

Demand optimization

In hotel revenue management, pricing strategies rely on many different factors, including room rates, upsell opportunities, market and seasonal trends, and competitor pricing. Traditional analysis, however, has limitations, as it tends to correlate single factors in isolation. For example, it might show that whenever there’s an increase in competitors’ prices or in demand during holiday weekends, it’s possible to increase rates without hurting occupancy. 

While this strategy often boosts revenue, an analysis that considers a wider range of demand signals and predicts the outcomes of different actions can yield even better results. Decision intelligence unifies the full range of pricing decision-making through both OTAs and direct bookings. 

A decision intelligence model powered by causal AI might reveal, for example, that during high season, offering a last-minute discount on unusually hot days (either through reduced rates or free amenities) attracts more local bookings, filling additional rooms and driving higher ancillary revenue. 

During slower seasons, rather than applying heavy discounts, DI might show that bundling a slightly discounted room rate with a complimentary spa or dining voucher is more appealing and generates more revenue.

All these decisions can be automated, allowing the system to adjust pricing automatically as the ideal conditions arise.

Segmentation

Guest segmentation based on traditional factors, like demographics, booking behaviors, and preferences, is relatively static and unable to capture emerging patterns in guest activity—such as frequent searches for specific amenities or price points—until after the fact. With DI’s real-time analysis, hoteliers can tailor offers to evolving guest needs, identify new segments with high conversion potential, and adjust promotions on the fly.

DI helps hoteliers get more granular with their segmentation. Instead of just segmenting by business travelers and leisure travelers – hotels can differentiate by weekday business travelers or high-spend leisure travelers, for example, and target them with different offers and promotions. 

Operations

Scheduling housekeeping and tracking inventory are daily operations that, though repetitive and time-consuming, require a level of analysis that makes them difficult to automate with traditional rule-based systems. Decision intelligence adds the extra capability necessary to fully automate these processes.

For housekeeping, it integrates updated data on occupancy levels, seasonal demands, and historical cleaning times across room types to optimize scheduling. 

For inventory tracking, it factors in booking trends, event schedules, and even guest profiles to accurately predict supply usage and automate restocking orders at the right time. 

For predictive maintenance, DI analyzes performance and usage data from IoT devices, traditional sensors, and past breakdown records, uncovering patterns and trends that help maintenance teams address potential issues before they escalate. This proactive approach prevents disruptions to the guests’ experience due to unexpected breakdowns and extends the lifespan of equipment.

Training & enablement

Unlike traditional systems that work with only one data type at a time, decision intelligence, powered by multimodal AI, can unify, analyze, and manipulate text, images, and audio simultaneously into a single search interface. This level of integration allows staff to provide quick and relevant answers—whether that be room images, maintenance voice notes, or training materials—to a wide range of questions from guests or other staff. 

For example, when preparing a room for a special event, housekeeping and maintenance can access set-up instructions and images to ensure accuracy. Or, if a guest asks about adding an extra bed, staff can locate and share a photo of a room with a rollaway bed, creating a clear visual upsell opportunity. DI can also be more proactive and suggest upsells tailored to guest profiles and booking patterns.

Multimodal AI can also provide new hires with quick access to relevant materials—such as visual guides, audio instructions, and set-up images—through a unified search interface. This on-demand access helps staff gain practical knowledge faster.

Cloudbeds Intelligence: A decision intelligence engine 

Cloudbeds Intelligence is a decision engine powered by advanced AI and machine learning. It’s equipped with forecasting, trend analysis, and automation capabilities and is built into the Cloudbeds platform, allowing users to make smarter, data-driven decisions directly across the system. 

Cloudbeds gathers data from every action within the platform—whether it’s our own native platform or our partners’—, organizing it in a way that supports effective AI and machine learning applications. This level of integration breaks down traditional silos, enabling information to flow freely between teams and providing a comprehensive view of the property’s performance and goals.

With Cloudbeds Intelligence, hoteliers can:

1. Achieve near-maximum occupancy at optimal rates every time by unifying decision-making factors into a coordinated strategy. This includes setting profitable room rates, leveraging upsell opportunities, and running targeted promotions or discounts to attract bookings during specific times or for select guest segments.

2. Capture and analyze historical data and predictions of future trends to design timely and relevant marketing campaigns.

3. Automatically create target segments based on past guests and cart abandonment data, guiding optimal promotions and pricing in direct marketing campaigns.

4. Consolidate and manipulate data in various formats—text, images, booking data, floor plans, and more—to answer guests’ queries, create upselling opportunities, and provide training materials to new hires on the fly.

5. Provide hotel management with real control over operations, helping them improve efficiency, increasing revenue, saving time and costs, and enhancing the guest experience.

Coming in 2025, Cloudbeds Intelligence with unify departments to deliver unmatched decision-making intelligence for revenue managers, marketers, GMs, operations staff, and more.