Why AI-Powered Hotel Revenue Management Is Taking The Hospitality Industry By Storm

Automation has become the driving force in the evolution of
revenue management. Leveraging advances in artificial intelligence
and machine learning, the best of today’s solutions make pricing
decisions and rate updates automatically. This allows revenue
managers to focus their time on tactics and strategy rather than
spending it crunching data and punching numbers into spreadsheets.
The speed and complexity of the pricing decisions, and financial
outcomes they generally produce, are unmatched by the most seasoned
revenue manager using the most advanced solutions on the market
only a few years ago. Such has been the blindingly rapid pace of
technology innovation.

The ability to integrate new sources of data has also played a
key role in driving smarter pricing decisions. Advanced revenue
management solutions leverage not only the repository of historic
data that resides in a hotel’s property management system, but
also, in many cases, a vast array of market intelligence and other
data, from competitor rates data to booking trends data. This makes
it possible to more accurately forecast demand, and, as a result,
increase hotel revenue and profitability in unprecedented ways.

That being the case, it’s no surprise that
next-generation, AI-powered revenue management has taken the
industry by storm. Some of the leading AI-powered solutions, often
replacing legacy solutions that use a hands-on, rules-based
approach for generating pricing decisions, now automatically
generate in excess of a 100 million decisions across tens of
thousands of properties each day. The results are impressive, with
major hotel brands seeing their revenue numbers increase by
millions of dollars a year. Smaller properties, too, are seeing
substantial gains, in some cases driving incremental sales lift by
more than 15 percent.

Interestingly, AI-powered solutions sometimes produce pricing
decisions that revenue managers may view as overly aggressive,
irrational, or just plain wrong. Therein lies the power of big data
and machine learning compared to the data processing and analytical
capabilities of mere mortals. Even the most experienced revenue
managers report that they have sold rates recommended by AI-enabled
solutions that they would not have published in the past.

AI-powered revenue management is all about smart pricing. It’s
about using demand forecasts, competitor rates, and price
sensitivities — while taking into account any number of other
inputs, including demand drivers like seasonality, special event
dates, and day-of-week differences —to maximize room occupancy at
the best possible price. Smart pricing also means considering other
factors, such as the type of room, the length of stay, and the
extent to which a discounted price promotion could potentially
dilute revenue and profits in the long run. The combinatorial
complexities involved in smart pricing are nothing to sneeze

Smart pricing is channel agnostic. Rather than thinking in terms
of “OTA booking versus direct booking,” for example, smart
pricing considers the relative value of all distribution channels,
weighing how much each channel drives guest room demand and will
help achieve the overriding objective, which is to maximize the
profitability of hotel inventory. Smart pricing calculates demand
from all sources, including OTAs. In an ideal world, algorithms
then automatically apply the right tactics and strategy to funnel
business through the most profitable channels.

The goal of maximizing profitability holds true not only for
guest rooms but also for other property assets and revenue sources.
Banquet and event function space, in particular, now increasingly
factors into the equation. According to “The 2019 Global Meetings
Forecast,” published by American Express, demand for function
space was expected to grow by 3.2% this year. For some hotels,
function space revenue now accounts for almost half of their total
revenue. It only stands to reason, then, that hotels would be eager
to apply revenue management strategies to their group sales and
catering activities.

Total revenue management, as this bigger-picture approach to
revenue optimization is often called, takes into account a
guest’s potential spend on recreational facilities, restaurants,
spas, and various other ancillary revenue streams when making
pricing decisions. For hotels with casino operations, even the
“theoretical loss” (the amount of money a specific category of
player can be expected to lose during their stay) should ideally
factor into guest room and group sales pricing decisions.

Empowering a hotel with the ability to make smart pricing
decisions in an automated fashion makes the business case for
investing in an AI-powered revenue management solution compelling.
It is compelling in terms of driving increased profitability. It is
also compelling in terms of averting potential revenue loss that
can result when a hotel fails to maximize occupancy or, worse,
experiences a loss in occupancy. Consider: A mere $2 reduction in
the ADR for a 500-room hotel with a 75 percent occupancy rate would
cost it more than a quarter million dollars in lost profit in a
single year.

Other benefits abound. The business intelligence gleaned from
the reporting capabilities, for example, can help improve sales
effectiveness, generate competitive intelligence, and provide
valuable insights into occupancy trends, guest demographics, market
positioning, and channel profitability. A marketing department can
use the forecasts as a guide for determining when to increase
promotional spend to spur demand. An operations team can know when
to increase (or decrease) staffing based on projected occupancy. In
short, the benefits tend to go well beyond the department known as
“revenue management,” ultimately transcending all parts of the

Source: https://www.hotelnewsresource.com/article107444.html

Source: FS – All-Hotels-Blogs
Why AI-Powered Hotel Revenue Management Is Taking The Hospitality Industry By Storm