Recently I conducted a detailed 360-degree analysis of Revenue Management technology available in the hospitality industry today. About 30 vendors were analyzed (yes, we have that many RMS vendors, it’s not just between iDeas and Duetto). Feel free to reach out via email or LinkedIn for the full report, but here’s the outline of the main conclusions that resulted from this research.
Let's put it this way: there's a lot of potential for existing RMS vendors to improve their products in order to catch up with the real needs of a modern hotelier.
Everyone would agree that the hospitality industry has drastically changed in the last 10 years. And it will continue changing at a more rapid pace. But while hoteliers are readapting to the new environment in an attempt to become more efficient, successful and profitable – legacy tech vendors don’t seem to be able to catch up to these new needs.
Most aspects of their functionality (forecasting, pricing, segmentation, etc.) are built in the pre-covid era. But do those strategies still work? Are they optimal and do they actually drive ROI and improve operating efficiencies and profitability for hospitality businesses? Or does our new reality dictate a new approach? Can we do better? Each of those existing vendors need to ask themselves these questions critically so that they are able to truly understand what works and what doesn’t and enhance their products to ensure that they correspond to the new model of our reality and the transformed needs and wants of hospitality businesses.
Hoteliers have a lot of questions, too. How do we maximize profit? How do we ensure that our forecasts are reliable? How do we track costs? How do we incorporate our revenue management decisions into our marketing strategies? etc. And when they ask these questions, they’re starting to understand that all answers are in the data, not in Tarot cards, not in the movement of celestial bodies, and not in coffee grounds. They’re starting to turn to data to help them make the right decisions. And for that, they need to understand how to find the right data, how to access it, how to analyze it and how to store it. And the right technology should be there to help them with all those things. But it’s not there yet.
Technology is key to successful operations. And logically, as Revenue Management is gaining in importance in our industry, as the main data-driven discipline – Revenue Management technology will become the centerpiece of the hotel tech stack once it gains the necessary amount of functionality described further in this article. Revenue Management technology will be reimagined and possibly also renamed. Something like Revenue and Profit Optimization Platform seems like a more suitable term. Further I explain why.
RM tech providers are now challenged to do more, faster and be more innovative. A few of these 30 vendors will keep up with the evolution of the industry and the transformed needs of the modern hotelier, but many won’t. I have my opinion about which ones will make it (no, I won’t share it in this article). I want to believe that this opinion is somewhat objective because it’s based on the most recent and most thorough industry research that anybody has ever conducted.
There are a number of Revenue Management software solutions being offered on the global hospitality tech market today. They are all aimed at solving the same problem – to assist hotels with strategic revenue optimization decisions and improve operational efficiency. But none of them, in my opinion, have what it takes to be called a next-generation Revenue and Profit Optimization Platform. Not yet at least.
Here’s a list of 7 items that most solutions are missing. Though I wouldn’t dare to consider this list entirely comprehensive.
I’m not going into discussing how some stakeholders in our industry only care about the top line room revenue, it is outside of the scope of this article. But the main problem is that those who do care about profit (the actual business owners) don’t really have a way to properly track and maximize their bottom line because we don’t have the right technology to help them with that. That’s our reality and it’s kind of sad.
Some of you may remember the times when hotels were targeting occupancy in their revenue strategy (that was before “dynamic pricing” became a thing). Then, at the next stage of its evolution, the Revenue Management discipline started revolving around RevPAR. And now is the time to move on to another level by accepting the drawbacks of the old RevPAR-centric approach and embracing the new profit-oriented paradigm.
As a result of the pandemic, proper cost control became a matter of survival for many. The industry was also forced to start innovating by developing new sources of revenue, improving efficiencies, while at the same time, it also incurred additional costs related to employee and guest health concerns. Unfortunately, it took a major disruptive force to get us on the right track when it comes to properly running our businesses.
Whether we like it or not, every single decision Revenue Managers take on a daily basis has an impact on the bottom line. That dictates the need for the Revenue Management discipline to not just concentrate on optimizing the room revenue stream, but ultimately on increasing profitability. That’s why Revenue Management has to be the central piece of the profitability puzzle, as it has the power to solve the problem of profit maximization.
Here are major gaps that exist in the current Revenue Management technology pertaining to profit optimization (or lack thereof):
- Algorithms (every single one of them) target RevPAR maximization, not profit. It is a huge problem because those are 2 very different metrics and they can actually go in opposite directions.
- Variable costs are not taken into account during pricing and inventory optimization decisions (this pertains to both: operating and distribution costs)
- Ancillary revenues are also ignored
In summary, the way RMSs were built and have been functioning is not yet adapted to the profit optimization needs of hotel owners. Some vendors have made steps in the right direction but none actually solve for it properly. The new-generation RMS (or RPOP rather) needs to be able to finally address this.
The lack of the profit-oriented functionality also contributes to the problem of different departments of hospitality businesses working in silos as they don’t use the same metrics to assess their performance and often contradict each other in their initiatives. We lack tools that aid different operating departments in understanding what actions to take in their daily activities that will lead to profit maximization, which is the ultimate goal of running a business.
And that leads us to the next topic.
Collaboration between departments
As we have already established, we can’t keep running our businesses the same way we were before. And one mistake we can’t repeat is not having any synergy between departments (operations, marketing, sales, revenue management, finance, etc.).
You might recognize a typical scenario in a traditional hotel company: RM department targets RevPAR, Marketing drives room nights for stay dates that don’t correspond to need dates, Sales team books groups over high demand periods without checking with RMs, Operations worry about cutting costs, while the owner cares about cash flow. Everyone is pulling the cart in their own direction and there’s no synergy whatsoever. This has been happening in many organizations in our industry for many, many years.
Revenue and Profit Optimization technology of the future needs to help hospitality businesses to solve the problem of departmental misalignment and aid in collaboration of those departments by becoming a Platform instead of just another siloed piece of the puzzle. Revenue and Profit Optimization Platform.
How will this happen?
Again, it’s all about data. And analytics is our future. And due to the growing importance of data, technology, and analytics, what we are witnessing today is the role of the Revenue Management department is being redefined and reimagined to become a more central discipline that drives the decision-making for the entire hospitality business. The Revenue Management (aka Revenue and Profit Optimization) department is becoming a critical piece of the puzzle as will Revenue Management technology that needs to help “glue” everything together and feed the information and decisions to other parts of the organism (where in most cases, profitability is the ultimate goal) with all departments working towards the same metric. To illustrate:
So helping build a revenue and profit optimization culture in each hospitality organization with the help of technology is crucial as it is crucial to ensure that all “elements” are working in sync towards the same goal (or goals).
While we have (somewhat) solved for aligning RM with Sales via add-ons used for group pricing quotes or corporate business assessments, the links are still missing between RM and everything else.
For example: how many modern RMS systems incorporate historic marketing campaigns data into forecasting projections? I’m sure I’m not the only person in the industry who understands that running a promo or a marketing campaign affects the property’s demand patterns, which means that this data needs to be taken into account to adjust future forecasts and also suggest parameters for future campaigns with the ultimate goal of profit maximization. But nobody has solved for that (yet).
Another major missing link is between RM and Operations. For some reason, existing RMS systems don’t incorporate functionality to assist with optimal staff scheduling, optimizing occupancy that would lead to maximum profits by minimizing operating costs, and everything else that would have to do with maximizing operating efficiency of the business.
To summarize, the new-generation Revenue and Profit Optimization technology needs to be viewed as a Platform that unites different departments and aids in overall business optimization rather than just another “add-on” that sits on top of a pile of other tools.
Intelligent automation of meta CPC/CPA/CPS bids
In line with the overall trend of different departments merging and starting to work closer together, DORMs (directors of revenue management, as they’re currently called) are starting to take on more tasks that previously were delegated to marketers. Here’s how MSEs (metasearch engines) fit in this picture, with Google of course being the most prominent player.
As you know, metasearch works with a number of different models: CPC (cost-per-click), CPA (cost-per-acquisition), and recently – CPS, aka PPS (commission-per-stay or pay-per-stay).
Today, as Google’s share in the search engine market reached about 92 percent, making it an absolute leader (travel sector included) – Revenue Management technology vendors can’t continue ignoring the fact that it will soon become our main distribution channel.
Here’s the thing. I believe all readers are familiar with Google’s vertical search products – Google Hotels and Google VRs, right? So while Google is not ready to crawl down the reservation funnel and start handling transactions between the consumer and the supplier (like traditional OTAs do), their main goal and the ultimate North Star is to have “the best place for travelers to make their booking decision”. And the way they’re planning to achieve that is by having the best, most comprehensive, most up-to-date, and most accurate information about the availability and prices in the market on those vertical search pages.
With that ambition in mind, Google is actively reaching out to hotel companies and independent booking engine providers asking for direct integration and bypassing OTAs. As more and more of them get connected directly to Google Hotel search, the more the scale will lean towards this MSE giant and away from OTAs.
It won't be long before we start noticing the change. Google has a very strong potential to start helping hoteliers funnel more traffic to direct channels in the very near future. As I’m sure you’re aware (and this is very important) that listing a hotel on Google Hotel or Google VR vertical search page is FREE. Remember, their goal is to have the most comprehensive marketplace and that’s the only way they can achieve that.
And for those who would like to boost visibility and increase conversion, Google offers an option to pay for ads via CPC/CPA/CPS. The main difference between Google’s commission (or any other meta channel for that matter) and that of an OTA is that it is flexible and is fully controlled by the bidder. What does it mean? It means that intelligent fluctuation of meta bids will become part of the next-generation RMS optimization decisions.
The sooner this happens – the better for hospitality businesses. Because Google will become the ultimate travel decision-making platform, and nobody will be able to compete. Google will own metasearch, because they own the search, period. Other metasearch engines like Tripadvisor and Trivago still rely on search traffic coming through Google.
Considering the above, that model (Google as the main distribution channel) may prove to be much more advantageous for hospitality businesses as it provides more control to the hotelier. But what’s more important is that we need to start considering how we can bring the Revenue Management discipline and the marketing discipline together as Hotel Ads become a part of our revenue and profit optimization strategy
in the same way Revenue Managers have been overseeing OTA distribution for the last two decades.
The Revenue and Profit Optimization Platform of the future needs to incorporate algorithms for intelligent automation of CPC/CPA/CPS bids on meta channels that would be tied to the forecasted demand levels with the ultimate goal of targeting profit optimization.
Forward-looking destination data incorporated into forecasting
As you may be aware, being able to anticipate demand levels for every day in the future (365 days out or even further) is the basis for any revenue and profit optimization strategy and budget planning.
The pandemic made it obvious (and painful) to hoteliers that in any situation that poses uncertainty, it is crucial to quickly develop and deploy strategies to adapt to both short- and long-term shifts in demand. But here’s the thing. Travel demand has always been uncertain, and history never repeats itself. Recent events just highlighted this fact for all of us and have been pushing the industry towards more innovations in the areas of forecasting and optimization. But very few RMS vendors seem to be able to catch on with that.
Now that the industry has come to this understanding, it’s time to build a better “model of our reality” that can incorporate the uncertainty in a more optimal manner. It’s time to rebuild our forecasting methods altogether. Last year I published an article on this subject where you can find more details.
As you may be aware, the traditional method of constrained and unconstrained demand forecasting estimates the quantity of rooms to be sold, using historic reservation data. There are two major problems with this approach that is used in most “traditional” RM systems:
- This approach is not about predicting true demand, it’s about predicting occupancy. It is absolutely ignoring the hotel’s pricing strategy, and this is a big problem because in real life, the price set by the hotel fully controls the resulting occupancy levels. This is a basic principle that most RMS algorithms are currently not taking into account. Forecasting occupancy irrespective of pricing is irrelevant in today’s world. In our current reality, when prices change every day (and in many cases, every hour) occupancy no longer correlates with market demand because it’s affected by our pricing strategy.
- This approach relies on the repetitive nature of historic reservation patterns. At this point, I don’t think I should go on explaining what is wrong with this. It must be obvious to anyone who’s been paying attention to recent global events.
While the traditional approach to forecasting served us well for a few decades, it’s time to let it go and build a new one because it is no longer relevant.
Because proper forecasting is the foundation of revenue and profit optimization, the discipline (and the technology together with it) can’t continue evolving optimally until we realize that we need a new way to forecast that reflects our new reality. The following needs to happen:
- First of all: demand measurement and demand forecasting need to take into account price expectations and price elasticity. So we need to move from measuring “my hotel’s booking volumes” to “all hotels’ booking volumes and customers’ price expectations”.
- Second: true market Demand measurements are only possible when external forward-looking market data is available. Relying on consistent patterns of historic internal booking curves is the main reason why most RMS algorithms fell apart during the pandemic.
External destination data is the upper funnel, forward-looking data that is gathered from the market, outside of the hotel. And it’s not just compset rates. What I’m talking about here is comprehensive market data that allows you to get as close to measuring market potential (and as far away from internal booking curves) as possible.
Examples of such data could be (in addition to the traditional published rates of all hotels in the area/region, which is still valuable): observed volumes of online searches/bookings for future dates in the market (obtained from OTAs or MSEs), events data, air searches and booking volumes, car rental searches and booking volumes, competitive performance, including alternative accommodations, etc. To date, this data has not been properly utilized in RMS forecasting algorithms. Thankfully, due to the development of cloud computing in recent years, more and more market data is becoming available from various providers.
One major source that is still very much underutilized is MSE (metasearch engines) upper funnel search volumes. There is a lot of potential to use it for proactively and dynamically measuring forward-looking market demand. Being able to access this data presents a unique opportunity for building adequate demand patterns, aid in developing much more accurate forecasts, and significantly improving performance. Those who get their hands first on Google hotels’ search volumes will have a significant competitive advantage. New possibilities are infinite for Revenue Management technology vendors.
The main moral of the story: Revenue and Profit Optimization technology vendors of the future will not be using the old “occupancy-based” forecasting approach. True estimations of demand are only possible when utilizing external forward-looking market data and then adaptively adjusting as it changes. This leads to reaching your maximum revenue and profit potential. After all, the goal of running a hotel business is not hitting occupancy targets. The goal is maximizing profit.
AI and ML-based algorithms
We are all aware that overall adoption of AI in our industry is still on a very rudimentary level, but one would hope that at least the geekiest tech players who deal with data analysis on a daily basis had it figured out… but that’s not really the case.
Believe it or not, only a very small number of existing RMS vendors’ algorithms are truly AI-based, and those are mostly the newest ones. But for the most part, true AI is still very much underutilized in our Revenue Management technology.
Utilizing modern machine learning science should be imperative for any modern RMS (RPOP). When it comes to revenue and profit management, AI and ML make the most sense when applied for the purpose of forecasting (mainly demand forecasting but really anything you want to predict) and optimization (dynamic pricing and other decisions that influence revenue and bottom-line profit).
What’s also worth noting is that RMS algorithms should never be considered fully done. They're living and breathing things and they always need to get better. Once AI is implemented, it needs to continue being tweaked, and ML needs to continue learning. There’s no such thing as a finished product when it comes to those algorithms, which means RMS companies need to continue investing in enhancing them to ensure they keep up with constant transformations in our industry and changing consumer trends.
But the reality is that many legacy RMS solutions are refusing to invest in upgrading their “brains” while taking advantage of the fact that it’s practically impossible for the consumer (a hotelier) to verify the quality of the algorithm before the system is actually installed. Many claim they use elements of AI in their products while that is not really the case. Most still use the pricing mathematics that were invented in the 1950s.
Now is the time for AI and machine learning to take over. And it becomes even more critical as we start incorporating more and more data sources we discussed above (“big data”) into our forecasting and optimization decision-making. We can’t do it successfully using our old mathematics, this is where the value of AI and ML is maximized.
There is no doubt Artificial Intelligence will reach wide adoption in our industry in the near future, and especially in the area of data analysis. There’s no way to stop that trend. And those companies that ignore that trend, will fall behind.
Real-time integration with the system of record (PMS or CRS)
Currently, there is only one Revenue Management System vendor that claims to have real-time integration with the system of record (which is normally PMS). Everyone else operates on a set schedule where data exchange happens either once a day or a few times a day. The limitations of existing technologies that result in slow processing of data (on both ends: RMS and PMS) is the main reason for this.
It’s quite obvious that these limitations have a significant impact on hotels’ ability to optimize revenue and profits because these systems do not provide up-to-date information, which can result in incorrect pricing decisions and reduced guest satisfaction. An RMS that is updated only a couple times a day doesn’t reflect real-time changes in demand, availability, and room rates, leading to missed opportunities to maximize revenue and profits.
In addition, the limitations on the PMS side can also impact the accuracy of the data used by revenue management systems. If the PMS is unable to provide the necessary information in real-time, the revenue management system doesn’t have access to the most recent and accurate data, which can lead to incorrect decisions and reduced profitability.
Moreover, slow processing of data can also impact the guest experience, as incorrect information about room rates and promotions may be communicated to guests. This can result in frustrated guests and a negative impact on guest satisfaction and repeat business.
Therefore, it is crucial for the next-generation Revenue and Profit Optimization Systems (Platforms) to support real-time integrations with PMS/CRS providers in order to ensure accurate and up-to-date data, efficient operations, and improved guest satisfaction.
This will provide a competitive advantage to those vendors that want to stay ahead in a constantly evolving market.
I have no doubt that one day (very soon) somebody will figure out how to incorporate open AI from ChatGPT or similar algorithms into revenue and profit optimization decision-making.
The capabilities of ChatGPT are mind blowing. It can be used to drive revenue by upselling and cross-selling hotel services and amenities, suggesting dining options or spa services to guests based on their preferences and past behaviors. It can provide real-time insights and predictions to help hotels optimize pricing and inventory. By analyzing guest behaviors and market trends, ChatGPT can help hotels make informed decisions about room rates, availability, and promotions. Furthermore, the tool can also be integrated into booking and distribution channels, allowing hotels to personalize pricing and promotions for individual guests, provide targeted promotions and discounts to guests based on their past behavior, preferences, and loyalty status. The list goes on…
It is clear that ChatGPT or similar AI tools have the potential to completely revolutionize the Revenue Management discipline and our industry altogether. The possibilities are infinite and the first RMS vendor to figure out how to utilize this disruptive force will have a huge competitive advantage.
And yes, a portion of this article was written with ChatGPT. Ideas are all mine.
As the Revenue and Profit Optimization discipline evolves and the way we manage our businesses is being completely reimagined, existing RMS vendors are feeling more pressure to provide more comprehensive solutions to ensure they’re aligned well with the new model of our reality (what I call Hospitality 2.0, which some of you may be familiar with if you have read my book).
That means that in order to keep up with the demands of a modern hotelier, these technology providers need to close the gaps outlined above, to help achieve closer collaborations between departments, support profit-centric approach, be agile and support continuous innovation, including disruptive AI-based solutions.
I’m very excited about what the future of hospitality technology holds for us, especially in the field of Revenue and Profit Optimization, which is very dear to my heart. Looking forward to seeing existing vendors and new entrants step up and respond to these challenges by introducing innovations that completely redefine the way we manage our businesses. And it will happen sooner than you think.