Revenue management in the hotel industry has become a science over the last few years with pricing strategies that increasingly factor in supply/demand fluctuations and the development of automated revenue management systems (RMSs). The progress has resulted in a rate adjustment approach that is both more efficient and highly personalized, based on multiple data sources from guest demographics to current market conditions.
When it comes to selecting an RMS, some hoteliers still opt for a product that is based on manual rules where the operator must play a role in calculating the rate. But for those seeking an advanced tool that leverages machine-learning, IDeaS Chief Evangelist Klaus Kohlmayr suggested several ideal features to look for in the product:
- Versatile, automated pricing that adjusts and remains competitive when demand fluctuates, business segments shift, or booking trends change.
- Accurate demand forecasts that are based on varied, relevant, and properly weighted data sources that quickly adjust to market changes.
- Tools for maximizing group business: With the influx in group demand, hoteliers need a solution that forecasts both their transient and group business. Sales managers can quickly respond to inquiries and determine if the hotel is likely to make more money by accepting that group or if they should hold out for the expected transient business [see sidebar, below].
- The ability to manage by exception with workflows that reduce repetitive, tedious work and give revenue managers more time to focus on strategic initiatives.
Regarding the last feature, Kohlmayr added that revenue managers and sales representatives can still have fruitful interaction with the system. “It’s not a ‘set it and forget it’ situation; you still have the ability to interact with the solution in many ways that impart what you know,” he said. In a recent interview with LODGING, Kohlmayr elaborated on the evolved role of the revenue manager and provided other insights into today’s tech-enabling forecasting and pricing.
How has the revenue manager’s role changed due to the increased sophistication of RMSs?
A revenue manager’s work has evolved significantly with technology advancements. They’ve moved from setting rates using spreadsheets, to interacting with technology to help automate and refine that process, to now becoming revenue leaders who need to be able to effectively communicate revenue strategy throughout the organization.
This evolution is not without challenges. While many revenue managers may be very comfortable with their numbers and analysis, some may be less comfortable driving the interdepartmental changes needed to help their organization think differently and maximize revenue opportunities.
Revenue managers can shine within their organization by going beyond the minutiae of the data and articulating what it means for the organization at a bigger-picture commercial level. This means understanding the business impact opportunities may bring and having the influence to circulate ideas at the right levels within their organization.
Great revenue leaders should spend the majority of their time leading the commercial change their hotel needs. While setting this direction is a collaborative process, it should be led by insights that are in the revenue manager’s wheelhouse.
A great revenue management solution can help revenue managers gain confidence in its outputs, especially when proven metrics, such as ADR, can be increased to levels never before thought possible.
What are some of the latest types of data sources that RMSs are leveraging?
There are many data sources and factors that can feed an RMS, such as historical data, future on-the-books, market trends, competitor data, reputation scores, etc.
The premise of “latest” data sources might not be the right way to think about it—these data sources are nothing new. It’s really what you do with the data that determines if that information is useful or not.
For instance, many solutions display external data within the RMS interface for the revenue manager to decipher and decide how to use. At IDeaS, we feel that introduces noise into the equation. Knowing revenue managers are extremely busy and have more strategic endeavors to focus on, our solution (G3 RMS) keeps that noisy, up-for-interpretation data analysis under the hood, so to speak. This is done by using effective, adaptive demand forecasts that influence a host of pricing and inventory management decisions.
Through the use of advanced demand forecasting methods that take in factors like the hotel’s data, booking pace, guest segment price sensitivity, competitive data, market trends, and more, we’re able to efficiently generate and distribute optimal prices by room type and/or market segment.
How does machine learning enable better pricing and forecasting over time?
Overall, artificial intelligence (AI) together with machine learning enables hotels to analyze vast amounts of data, make more accurate demand forecasts, and refine pricing strategies.
IDeaS’ G3 RMS has been using revenue science for decades. Revenue science is the process of transforming data into accurate, automated, and actionable revenue-enhancing decisions.
Unlike other solutions, G3 RMS uses a variety of analytical models in forecasting demand and estimating guest price sensitivity. These models are specific to hospitality demand and auto-select to optimize pricing and rate availability with a keen understanding of segment relationships and unconstrained demand.
These forecasting models refine over time as more data comes in. This is an oversimplification, but it can help to think of it this way—this wide variety of forecast models outputs a range of demand projections. With limited data, that range of potential demand forecast outcomes is wider as there are more elements of uncertainty, but as more data comes in this range narrows. Over time, advanced forecasting methods get better at understanding which demand forecast models are more likely to be accurate for a particular property and in turn, weight those models’ projections accordingly.
Does the greater functionality of today’s RMSs call for a more involved training staff process?
It’s no revelation, but powerful tools require knowledge to be used effectively. We also know the teams at our client properties aren’t static—established RMSs power users on staff get promoted, move on to new opportunities, and so on—which is why we’ve placed an emphasis on building a client training and support structure that ensures clients have what they need to be successful for the long haul.
That client support goes beyond the obvious—and critical—start-up training and orientation for new client properties. For instance, throughout the duration of their relationship, IDeaS clients work closely with a Success Manager who helps ensure the hotel’s pricing strategy is being carried out effectively.
IDeaS has also developed training content tailored to the user’s job role on the property. This content helps users build confidence through self-paced interactive learning modules and one-on-one guidance from IDeaS experts.
Within the solution, users can access step-by-step guides, visualizations, and micro-demos where and when they need them without switching screens.
Additionally, IDeaS users can take advantage of ongoing on-demand e-learning and live events like monthly webinars, community Q&A sessions, and expert panel discussions to increase their learning and engagement in the solution.
All of this effort, at its essence, is about making sure clients can get the answers and help they need when they need it. That’s a necessity for any RMS provider.
What are the potential future uses of AI in revenue management, beyond its current role?
Currently within G3 RMS, AI and machine learning are hard at work finely tuning the core analytics to maximize profit or revenue by automating the decisions of pricing, rate availability, and overbooking. AI uses in revenue management will continue to ease your most mundane and repetitive tasks so you can add value in other areas.
Outside of the RMS, hotels have a clear opportunity to use AI tools and applications to analyze guest data and improve their experiences, whether that is through streamlined bookings, high-tech room amenities, or more convenience.
No-Guesswork Group Sales: Software Designed to Maximize MICE Revenue
Group business revenue management is gaining support from highly sophisticated products on the market, and Duetto’s solutions are a case in point. With the launch of BlockBuster in 2017 and the acquisition of MiceRate in 2024, Duetto has enhanced its revenue management solutions in this area to now offer a full-service revenue solution that encompasses rooms and event space.
Duetto delivers a suite of SaaS cloud-native applications for hospitality businesses to optimize every booking opportunity for greater revenue impact. Duetto’s applications include GameChanger for pricing and ScoreBoard for intelligent reporting, along with BlockBuster and MiceRate.
BlockBuster focuses on group accommodations. Working with GameChanger, it enables revenue managers to determine the optimal mix of group and transient business. It provides room rate recommendations based on acquisition cost, transient displacement, ancillary profit margins, and group demand forecast.
MiceRate also leverages demand forecasts to support function space and group F&B sales specifically. “You can look at different demand levels based on different function spaces, dates, minimum spends, and more,” explained Gerhard Wasem, Duetto’s director of product.
Discussing the evolution of MiceRate, Wasem said: “Once we had all the strategies and settings, we built a quote calculator so you can see what to charge for the F&B package, parking spaces, etc. And with the booking engine, you can see live availability and live pricing on your brand.com website like you do with rooms. This is where we are more efficient and more profitable at the same time.”
Wasem added that MiceRate primarily relies on property-level data to make forecasts and rate recommendations, as “it’s quite hard to get market data because there is no STR data for function space usage.” Thus, the system uses past event data from the property management system and KPIs to calculate and recommend event space rates.
“MiceRate is the first decision-making tool where we use those KPIs to come up with a certain demand level and then a price recommendation, e.g., for this particular Wednesday, you should charge $XX for the F&B package and function space.”
Wasem added, “We can pull event data for a certain destination and look at the change in demand with big events coming up and everyone booking hotel rooms in the city. This is where we use AI to identify those demand fluctuations and change the room rate immediately.”
Working together, the Duetto solutions can serve up room and event space rate recommendations based on parameters like run of house, shoulder dates, comparisons between event types (e.g., wedding reception vs. conference business), etc.
Wasem emphasized that revenue management tools like BlockBuster and MiceRate are not a replacement for strategic thinking. Commercial teams create strategies and input them into the system, enabling the Duetto solutions to automatically calculate rates based on market demand while following the predetermined settings.
