Dynamic Pricing Engine and Market Intelligence

THE CHALLENGE

A leading European parking reservation platform operates in a highly competitive market where supply and demand fluctuate constantly. The traditional model of static pricing or flat seasonal rates limited its capacity to maximise revenue (Revenue Management).

The main challenge was to overcome the rigidity of manual tariffs. They needed an intelligent solution capable of analysing market behaviour in real time and adjusting prices automatically to capture maximum value during peak demand and guarantee occupancy during off-peak periods, all without increasing the team’s operational workload.

THE SOLUTION

GALEO developed and implemented an AI-based Dynamic Pricing engine designed to automate the pricing strategy and optimise the performance of each parking space. The solution operates on a continuous cycle of data and decisions:

1. Demand Forecasting: Machine Learning models were trained using historical booking data, seasonality, local events, and public holidays to predict future occupancy with high precision.
2. Price Optimisation Algorithm: The core of the solution applies price-demand elasticity models. The system calculates the optimal price for each product and time slot, seeking the perfect balance between maximising margin and ensuring sales volume.
3. Automation and Deployment: The solution not only suggests prices but integrates with the backend to update tariffs on the platform in real time, eliminating manual intervention in day-to-day operations.
4. Competitive Monitoring: Integration of competitive intelligence modules to adjust strategies based on market movements.

BUSINESS IMPACT

The implementation of the dynamic pricing engine has transformed their commercial strategy, shifting from a reactive model to a predictive one.

• Revenue and Gross Margin Increase: Significant increase in revenue per available space (RevPAM) by capturing surplus during peak demand. In 2025, the impact was a 7.92% increase in gross margin, a direct result of continuous algorithm optimisation based on accumulated annual data.
• Occupancy Optimisation: Improved occupancy rates during low-demand periods via automatically calculated attractive prices.
• Operational Efficiency: Liberation of human resources by automating tariff management, allowing the business team to focus on strategy rather than manual price change execution.
• Market Agility: Immediate response capability to unexpected changes in demand or competitor actions.

FUNCTIONAL FLOW: Real-Time Value Generation

Every time a driver searches for parking on this platform, the system instantly activates an artificial intelligence engine that simultaneously evaluates the user profile, geographic area, real-time demand, and seasonality. In less than a second, the algorithm calculates the optimal management fee and returns it personalized to the user, who sees a price tailored to their context before confirming the booking.

This process completely eliminates manual rate management, freeing the operations team to focus on strategic decisions. The result is a system that continuously and autonomously maximizes revenue per parking space, adapting to market fluctuations without human intervention.

ANALYTICAL FLOW: Continuous Improvement Cycle

On a daily basis, all booking data is automatically ingested into a Data Lake on AWS S3, following a Bronze, Silver, and Gold layered architecture that ensures data quality and traceability. From there, a Power BI dashboard enables real-time comparison of the performance of different pricing models, segmented by zone, season, and user profile.

ARCHITECTURE & TECHNOLOGY

The solution utilizes a modern data architecture to support model training and real-time inference.

• Core ML: Python (Scikit-learn, Pandas) for developing prediction and optimisation models.
• Cloud Infrastructure: Scalable architecture for historical data processing and algorithm execution.
• Integration: REST API for bidirectional communication with the e-commerce platform.
• Visualisation: KPIs dashboards for Revenue and Occupancy tracking.

CUSTOMER REVIEW

“Leaving static tariffs behind and adopting a predictive AI engine has been transformative. By automating the adaptation of our prices to market fluctuations, we have freed the operational team and sustainably increased our revenue per space.”