Acropolium
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⏩ AI Hotel Revenue Management and Dynamic Pricing Software

case study

AI Hotel Revenue Management and Dynamic Pricing Software

Implementing AI dynamic pricing for room rate optimization and better demand forecasting. Centralizing revenue management across multiple properties while providing local flexibility. Streamlining processes that result in increased occupancy and revenue.

client

NDA Protected

Greece
120 employees

Our client is a top hotel chain with properties in urban hubs and resorts. They serve business travelers, families, and groups, offering modern amenities and tailored services. Focusing on quality, technology, and sustainability, the company delivers exceptional guest experiences.

request background

Hotel Revenue Management AI for Advanced Pricing

The hotel chain faced major pricing and operational efficiency challenges due to outdated manual processes.

With properties across urban and resort markets, each with unique demand patterns and guest profiles, their existing approach often led to inconsistent pricing. During peak periods, the company missed opportunities to maximize rates, while in slower periods, underpricing reduced profit margins.

Another critical issue was accurate demand forecasting. Without advanced tools, the chain struggled to anticipate booking trends, competitor pricing, and external factors like seasonality or local events. This reactive approach made it difficult to adapt quickly to changing market conditions, resulting in lost revenue and a competitive disadvantage.

The client sought an AI driven revenue cycle management system to automate real-time pricing, predict demand accurately, and provide actionable insights. The solution also had to account for the unique characteristics of each property — such as location, audience, and seasonality — while integrating smoothly with existing systems.

AI revenue management request background

challenge

Obstacles to Address with Hotel AI Revenue Management

The company struggled with several operational challenges and turned to Acropolium for an advanced solution.

For example, the hotel chain used manual pricing, which was time-consuming and inconsistent across properties. This approach couldn’t quickly adapt to market changes, leading to missed opportunities in peak and slower periods.

Manual pricing adjustment didn’t allow the chain to react quickly enough to the changes in current situation and trends. The lack of automation meant pricing strategies often lagged behind market conditions, leaving the company at a competitive disadvantage.

Another challenge was demand forecasting. Without insights into future trends or events, the chain struggled to change pricing proactively, missing opportunities to optimize rates.

Decentralized revenue management worsened the problem. Each property had its own market conditions, and there were no centralized tools or data sharing. This led to inconsistent pricing and lost revenue.

Revenue management efforts focused primarily on room rates, leaving significant potential in untapped services like dining, spa offerings, and event packages. Without tools to analyze guest behavior and preferences, the chain missed upselling opportunities.

Their pricing system also failed to scale and didn’t integrate well with other operational tools like booking platforms or CRM systems, limiting their ability to manage pricing effectively across all properties.

We considered all the company's challenges when developing AI hotel revenue management software.

goals

Automate real-time dynamic pricing and adjust rates based on market demand and competitor pricing.
Provide accurate demand forecasting with AI-driven predictive analytics.
Centralize AI revenue management across properties while allowing for local flexibility.
Enhance operational efficiency by reducing manual pricing interventions.
Maximize additional revenue through upselling and cross-selling opportunities.
Boost profitability and gain a competitive edge with data-driven pricing strategies.

solution

Hotel Pricing Software with AI Integration and Property Centralization

Node.js, Express.js, PostgreSQL, MongoDB, Redis, Python, TensorFlow, PyTorch, RabbitMQ, Apache Kafka, React, SignalR, Socket.io, Kubernetes
29 months
8 specialists

To tackle the challenges, we worked closely with the hotel chain through a detailed discovery phase. This phase involved learning about their specific needs, reviewing current pricing and revenue management processes, and identifying areas where automation and AI-driven revenue management could bring the most value. We focused on understanding the client’s pain points and goals to ensure the solution fully aligned with their requirements.

Based on these findings, we automated manual processes to increase their efficiency and guarantee more reliable outcomes. Then, we developed a software solution specifically tailored to the needs of the hotel chain.

Now, the software uses advanced AI algorithms to analyze market demand, competitor pricing, local events, and booking trends in real time. It uses dynamic pricing AI to optimize revenue by providing competitive pricing and taking advantage of peak periods.

AI in revenue management also includes intelligent analytics capabilities to enable proactive pricing strategies that maximize profit during peak demand periods and optimize for slower periods.

The solution centralizes pricing across all properties, ensuring consistency in strategies. It also allows for adjustments based on local market conditions to boost revenue at each location.

It was also important to integrate hotel software AI with existing reservation systems, CRM platforms, and operational tools. This not only supports the growth of the hotel chain but also ensures a seamless data flow and coordinated revenue strategies for all properties.

In addition to room pricing, the software identifies opportunities to increase ancillary revenue streams. By analyzing guest preferences, it offers personalized upsell and cross-sell capabilities for services such as dining, spa reservations, and event packages.

And, of course, the platform offers an intuitive dashboard for revenue managers that provides actionable insights, performance analytics, and customizable reports.

The platform with AI-driven dynamic pricing, powered by real-time market data and competitor analysis.
Predictive analytics capabilities for demand forecast and optimized pricing strategies.
Centralized pricing, powered by flexible settings.
Seamless system integration with CRM systems and external sources.

outcome

AI Based Revenue Management, Leading to Process Automation and Revenue Growth

AI-driven pricing increased occupancy by 12% through real-time price optimization.
Automating pricing adjustments reduced manual pricing tasks by 30%, freeing up time for strategic focus.
Dynamic, data-driven pricing led to a 15% revenue growth by quickly adapting to market changes.

AI driven revenue cycle management results

client feedback

Working with Acropolium was a great experience, as they understood our challenges and customized AI hotel software to fit our needs. The AI insights improved our pricing strategy, and the software boosted our team's efficiency. We've seen strong results and stayed ahead in the market.

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