Cloudbeds Expands AI Platform to Help Hotels Boost Occupancy and RevPAR

Originally published here at Hotel Technolgy News

Cloudbeds, the AI-powered platform fueling hotel growth, today announced advanced revenue intelligence and guest marketing capabilities for Signals, the hospitality industry’s first foundation AI model designed specifically for hotels. Built on breakthrough causal AI technology that processes 4 billion data points per hour, these new capabilities revolutionize revenue management and guest marketing by understanding cause-and-effect relationships between market forces rather than simple correlations.

These purpose-built capabilities address critical industry challenges as hotels navigate increasingly shorter booking windows, contracted markets, and the breakdown of traditional forecasting methods. COVID-19 fundamentally transformed revenue management by invalidating historical data reliability, while the post-pandemic “revenge travel” boom is declining. Traditional forecasting approaches struggle with accuracy rates around 50-70%, leaving hoteliers lacking the precision needed for optimal decision-making.

“AI will define the future of hospitality, but only if it truly understands hospitality,” said Adam Harris, CEO and Co-Founder of Cloudbeds. “Signals is the first foundation model built with and for hoteliers, trained on billions of real booking, guest, and market signals. It predicts demand, but better yet—it explains it. For the very first time in this industry we turn data into intelligence into an organization-wide asset that helps hoteliers make faster, better decisions with accuracy they can finally trust.”

Unlike traditional AI systems that rely on correlations, Signals uses causal AI to model cause-and-effect relationships between different market signals. This groundbreaking approach enables hoteliers to understand the true impact of changing rates, deploying marketing campaigns, or responding to event announcements. The system processes diverse data streams including competitor rates, event feeds, weather patterns, and booking behaviors to deliver actionable insights.

The platform’s unique “time surface of booking data” technology uses both dimensions of booking data simultaneously to understand correlated days and projects in two dimensions for higher accuracy. This industry-first innovation allows Signals to achieve up to 95% forecasting accuracy across 90-day periods, particularly excelling in the critical seven-day booking window.

Early adopter Mercure Paddington Hotel demonstrates Signals’ transformative impact. Operating in London’s competitive city center market with challenging booking windows and varied business mix, the property has used Signals for revenue intelligence across both revenue and marketing strategies for over a year.

During a challenging January period, Signals enabled targeted email campaigns and strategic rate adjustments that delivered remarkable results:

• Hotel occupancy: 93% vs. competitor set average of 64%
• RevPAR: £120 vs. competitor set average of £79
• Outperformed market through targeted segmented mailers and data-driven rate strategy

Beyond revenue optimization, Signals enables hotels to deliver hyper-personalized guest experiences from first contact through post-stay engagement. The system analyzes guest behavior, preferences, and booking patterns to create tailored content, offers, and communications that resonate with individual travelers.

Case study Bespoke Hotels illustrates this personalization power. Starting with zero guest data after acquiring 40 properties, the company used Signals to collect customer information through Wi-Fi integration and create personalized marketing campaigns based on customer segments (coastal, rural, seasonal). The causal AI identified demand gaps, determined optimal booking timing, and generated relevant content, achieving £1 million in revenue within one year through targeted email marketing with 20% open rates for highly segmented campaigns.

Signals addresses a critical gap in the AI landscape: while large language models like ChatGPT have limited hospitality-specific data (just 0.004%), Cloudbeds has spent over a decade collecting and structuring hospitality data, breaking down silos between revenue management, marketing, operations, and guest experience.

Key differentiators include:

• First foundation model specifically designed for hospitality
• 4 billion data points processed hourly
• Causal AI framework modeling true cause-and-effect relationships
• Integration of revenue and marketing data for unified insights
• Proprietary hospitality data treatment and time surface technology

Signals serves as the AI foundation powering the entire Cloudbeds platform, extending beyond revenue intelligence to transform guest sentiment analysis, review categorization, digital marketing optimization, and enterprise search capabilities. The technology enables natural language queries across hotel operations and unlocks patterns from both structured and unstructured data sources.

The Cloudbeds platform enables hotels to capture untapped revenue opportunities through better market visibility, demand prediction, and personalized guest engagement while automating processes that previously required manual analysis.

“Hotels are experiencing a fundamental shift where traditional approaches are failing,” said Amit Popat, Head of Machine Learning at Cloudbeds. “Signals represents the kind of innovation the industry needs—technology that doesn’t just provide data, but delivers actionable intelligence that empowers hoteliers to make instant decisions with confidence.”