Matt Schwartz, Co-founderPricingService.ai leads the hospitality industry into futuristic, precision pricing with their most advanced revenue management service. Powered by the collective expertise of the latest academic research, native AI technology, and practical industry insights, the service helps hotels autonomously calculate optimized prices for rooms in milliseconds—redefining revenue efficiency.
“We are revenue management reimagined. We equip revenue managers with powerful Machine Learning algorithms for optimal pricing, freeing them to focus on the timeframes, room types, and market segments they care about most,” says Matt Schwartz, co-founder.
Dan Zhang & David Li, Co-foundersTraditionally, 90 percent of the world’s 470,000 independent hotels have no revenue management system (RMS) integrated to their property management system (PMS). With no revenue management system, 99 percent of the time there’s no revenue manager. As a result, the General Managers of these independent hotels resort to manual, timeconsuming pricing analysis based on past experiences, competitor rates, perceived demand, availability, and intuition.
Co-founders Matt Schwartz, Professor Dan Zhang, and Professor David Li bring over six decades of combined experience in hospitality and academia. Both professors’ expertise spans mathematics, AI, ML and operations, crucial for revenue management. Integrating the latest research in academia and related industry information, they’ve developed an algorithm-based application engine with AI technology delivering exceptional value to hotels on each available room.
Simplifying Pricing
PricingService.ai offers three pricing services—‘Fully Autonomous’, ‘Hybrid’, and ‘Second Opinion’—simplifying and modernizing the hotel room pricing process. Using its library of proprietary ML algorithms, it integrates with PMS tools, for optimal room pricing.
In ‘Fully Autonomous’ mode, the service continuously monitors the situation and dynamically updates pricing for all room types every few hours, or as needed, instantly addressing the challenges of dynamic pricing. Similar to Uber’s real-time rate adjustments, it addresses complex demand-supply dynamics in milliseconds. Detailed pricing stats are delivered via email directly to the client’s inbox.
In “Hybrid’ mode revenue managers can control pricing elements they choose to manage on their own, while PricingService.ai handles the rest. For instance, they can focus on specific room types like ocean-facing rooms or King size rooms.
‘Second Opinion’ mode is designed for hotel owners and asset managers. This service provides daily reports comparing current pricing with AI-driven recommendations, offering valuable insights for making informed decisions to adjust pricing for maximum room revenue.
The three pricing services are tailored to different stakeholders based on their role in the hotel—general manager, revenue manager, or hotel owner/asset manager.
PricingService.ai recommends their Fully Autonomous service to general managers, enabling them to prioritize guest experiences and staff engagement, saving time, increasing revenue, and ensuring pricing continuity over the long-term.
For instance, Matt Bowry, GM of the Yorktown Beach Hotel, became PricingService.ai’s first client in December 2021. Since then, with the Fully Autonomous service integrated with Stayntouch PMS, he hasn’t needed to set any prices, saving 10 to 15 hours weekly. This allows him to focus on customer satisfaction and working with his associates and community.
Using PricingService.ai’s strategy, the GM as well as the hotel owner witnessed a significant increase in room rates, even doubling during peak demand periods like July 4th that attracted large crowds to witness the American Revolution type setup of the town with big firework celebrations. The average daily rate (ADR) soared from $200 to exceeding $400. The price experimentation approach led to significant annual gains in room revenue from 2021 to 2024.
If the revenue manager is open to AI-based insights and suggestions, the Hybrid service is recommended emphasizing flexibility for hotels. The Hybrid service is well-suited for those wishing to retain control over critical aspects of pricing while delegating others to AI algorithms for simplifying tasks and boosting productivity. Automating transient pricing lets PricingService.ai take some pricing work off their plate. The revenue manager can easily override pricing anytime.
“The hybrid model’s Copilot concept has received positive response from revenue managers, with our 90-day recommendations and automated pricing beyond those 90 days,” says Professor Li.
We are revenue management reimagined. We equip revenue managers with powerful Machine Learning algorithms for optimal pricing, freeing them to focus on the timeframes, room types, and market segments they care about most
The pricing environment is very dynamic. The foremost reality is that revenue managers are expected to be alert 24x7 to detect any change that can impact pricing. The other reality is that the amount of data they need to process is overwhelming.
A revenue manager for a major third-party management company overseeing a portfolio of hotels in the US, exemplifies the hybrid approach. People who are traveling with their friends and family normally book 90 days in advance. She focuses solely on optimizing the transient booking window, typically 90 days out, for each hotel in her portfolio. PricingService.ai’s Second Opinion reports provide her with daily insights for the next 90 days, allowing her to make informed decisions quickly.
Meanwhile, she entrusts PricingService.ai with pricing for days 91 to 365, freeing her to concentrate fully on maximizing revenue in the short term. This hybrid model enhances her productivity and effectiveness in revenue management across multiple properties. All her hotels work on Opera Cloud.
For hotels managed by the owners themselves or by asset managers, PricingService.ai recommends adopting the Second Opinion service which gives them the benefit of calculated options but also gives the freedom to audit the pricing strategies employed by third-party management companies.
Partnerships that Generate Growth
PricingService.ai maintains partnerships with external data providers to augment its algorithms. Its current PMS partners are Stayntouch, Oracle Hospitality’s Opera, MEWS, Infor and Cloudbeds, and more are in its pipeline.
It augments the power of its algorithms with external data sources, including weather forecasts and historical data, as well as competitor pricing data through partnerships with NOAA and Lighthouse, and event data companies like PredictHQ. For example, Taylor Swift’s Eras Tour dates are seamlessly integrated, providing a comprehensive foundation for pricing decisions.
“We are unique in the sense that we use competitor price data as a guardrail and not as a primary input in calculating optimized pricing,” says Professor Zhang.
Price testing is also a unique feature not typically found in most revenue management systems. Drawing inspiration from tech giants like Amazon and Uber, the professors advocate the concept of price experimentation for designing effective price permutation. Subjecting pricing strategies to rigorous testing, hotels can uncover optimal pricing strategies for a competitive edge.
Another example showcases the power of AI-driven pricing in maximizing revenue, even without historical data or personal experience. Nico, a general manager in Kitzbuhel, Austria, inherited a hotel without historical data or firsthand knowledge of its performance. Transitioning to the MEWS platform, he entrusted PricingService.ai with Fully Autonomous pricing while focusing on marketing and community engagement. This leap of faith in AI resulted in remarkable success, with the hotel achieving high occupancy and rates in its first season under Nico’s management.
The rising popularity of its Fully Autonomous and Hybrid services reflects a transformative shift in revenue management. With a successful track record and increasing customer satisfaction, PricingService.ai has become the destination for hotels to garner exponential growth—staying true to ‘revenue management reimagined.’
