A Canadian real estate and hospitality firm with a multi-brand hotel portfolio of nearly 10,000 rooms across North America sought to enhance its decision-making with a stronger foundation in data and analytics.

Key challenges included:

• Disconnected internal systems and teams managing different brands and properties
• Limited access to third-party tourism and travel trend data
• Lack of advanced forecasting tools for occupancy rates and pricing optimization
• Need for better visualization of market trends to support leadership decisions
• Gaps in the technology stack required to support analytics initiatives

The firm needed a comprehensive strategy to align data efforts with business goals, drive operational improvements, and enable AI-powered forecasting.

CVM's team designed and implemented a Hotel Data & Analytics Strategy tailored to the organization's complex needs.

Key components of the solution included:

• Stakeholder Collaboration: Engaged multiple internal and external stakeholders to understand pain points, define use cases, and drive alignment.
• External Data Sourcing: Identified and procured tourism and market intelligence datasets to complement internal property data.
• Technology and Process Implementation: Established new systems, workflows, and governance processes to support sustainable data and analytics initiatives.
• AI Model Development: Built machine learning models to forecast hotel occupancy rates and optimize dynamic room pricing strategies.
• Market Analytics Tools: Developed dashboards and analytics products to visualize trends in occupancy, pricing, and travel demand across markets.

Throughout the engagement, CVM's team emphasized creating flexible, scalable systems designed for long-term value and adaptability.

• Improved Forecasting Accuracy: AI-powered models enhanced occupancy rate predictions, enabling better operational and revenue planning.
• Optimized Pricing Strategies: Data-driven pricing models helped maximize room revenue while adapting to shifting market conditions.
• Expanded Market Insights: New visualization tools provided leadership with real-time views of travel trends and competitive landscapes.
• Stronger Analytics Infrastructure: Implemented processes and systems created a sustainable foundation for future analytics initiatives across the hotel portfolio.

• Strategy and Execution Must Go Hand-in-Hand: Building tools without an enabling strategy and processes risks short-term gains but long-term failure.
• External Data Unlocks Competitive Advantage: Augmenting internal data with external travel intelligence significantly strengthens forecasting and pricing.
• AI Must Serve Real Business Needs: Forecasting and pricing models were designed for direct operational use, not just theoretical analysis.