Revenue Analytics Launches AI-Driven Pricing Tool
Revenue Analytics just unveiled its next-gen Climber RMS, a revenue management system featuring progressive AI-driven pricing automation. The platform is designed to analyze demand trends and competitor rates in real-time to optimize pricing and allocation decisions. The move signals a broader industry shift toward fully automated, dynamic pricing to maximize RevPAR and reduce revenue leakage.
Atlanta-based Revenue Analytics has deep roots in hospitality pricing, with its co-founder, Robert G. Cross, having pioneered the first hotel yield management system with Marriott back in 1987. The company, founded in 2005, has a history of developing custom revenue management systems for major brands like IHG and Starwood before launching its own SaaS products. The new tool is an evolution of the Climber RMS platform, which Revenue Analytics acquired in June 2025. The acquisition of the Portugal-based Climber was followed by the integration of Revenue Analytics' advanced AI framework into the platform, leading to this next-generation release. The enhanced Climber RMS is designed for scalability, offering three distinct tiers—Smart Pricing, Growth, and Pro. This structure allows a multi-property group to implement foundational AI-driven pricing at some locations while using more advanced features, like group management and dynamic pricing by room category, at others. This launch is part of a wider industry shift where AI is used to analyze real-time data on market demand, competitor pricing, and even local events to automate rate adjustments. Companies that have adopted AI for revenue management have reported revenue increases of up to 17%, according to a report by McKinsey. For a multi-island resort chain, the impact of such a system extends directly into supply chain logistics. More accurate, AI-driven demand forecasting allows for optimized inventory management of everything from food and beverage to linens, a critical advantage in regions with inter-island freight constraints. By automating pricing, which can be updated as frequently as 12 times a day, revenue teams can shift their focus from manual spreadsheet analysis to higher-level strategy. This aligns with a move toward total revenue management, where data from all departments is used to optimize profitability across an entire property portfolio.
