Beginners Guide to Hotel Revenue Management 2017

Your Customers are willing to pay different prices for the same product.

The timing, the urgency of the need, and many other factors all influence a person’s perception of product value.

How a business can capitalize on this behavior and optimize their business forms the foundation of Revenue Management. So how does modern Revenue Management work?

A Brief History

40 years ago, British Airways (originally BOAC) and American Airlines figured out that they could charge customers more or less depending on inventory levels, demand, and timing. This practice not only guaranteed that all the seats on a flight were filled, but also that the seats were filled by the most profitable customers. American Airlines increased their revenues by 14.5% and profits shot up by 47.8% the year after they implemented Revenue Management.

Other industries quickly took notice. By 2000, almost all the major airlines, hotel chains, cruise lines, and rental car companies had implemented sophisticated Revenue Management Systems that tried to forecast demand and optimize prices. Marriot exemplified this success by generating an additional $200 million in revenues the year after they implemented their system.

Today, these sophisticated, complex, and often very expensive Revenue Management Systems are being distilled, simplified, and automated to make them more accessible for everyone.

Goal of Revenue Management

To sell the right product to the right customer at the right time at the right price.

Revenue Management Process

Revenue Management is generally comprised of 4 processes.

  1. Data Collection – Historical data + Competitor data + Market data
  2. Data Analysis – What does the data mean?
  3. Forecasting – What will the customer do?
  4. Optimization – What should the business do?

An experienced Revenue Manager or Pricing Specialist with a background is statistics, math, or finance was traditionally required to perform these 4 processes. However, with the advent of technology solutions these processes can now be automated.

Technology Solutions

Rate Intelligence

Rate intelligence products are offered by 3rd parties (RateGain, Travelclick, Yieldplanet) or offered directly by the Online Travel Agencies OTAs (Booking.com’s Booking Suite RateIntelligence, Ctrip’s JointWisdom). These products provide competitor pricing data as well as general market data.

3rd parties obtain this data by interfacing with Property Management System (PMS) and OTA systems while OTAs have this data intrinsically in their system.

Rate Intelligence solutions still require an experienced manager to interpret and make use of the data.

These systems are generally priced from Free to $5,000 USD annually.

Traditional Rule-Based Revenue Management Systems

These are the big boys of Revenue Management Systems. Systems such as HiltonGro, One Yield (Marriot), IDeaS, and Duetto provide systems to analyze data, forecast models, and create pricing optimization strategies.

These systems are comprehensive, powerful, and complex. They require an experienced Revenue Manager to operate and use effectively.

They are also expensive. Most of these systems cost about $10,000 to $50,000 just in implementation fees. This limits the availability to larger enterprises.

New Cloud Algorithm Based Systems

Cloud-based Algorithm Revenue Management Systems are the industry’s solution to the complexity and expense of traditional Rule-Based Revenue Management Systems. These systems are light-weight, simple, and affordable. They take data from the PMS or OTA and use advanced self-learning algorithms to automatically output price recommendations.

Available providers in China include Booking.com’s BookingSuite (acquired PriceMatch), Ctrip’s JointWisdom, and local Shanghai firm HongQue. The empirical evidence demonstrating the efficacy of these systems compared to traditional systems does not yet exist. That said, Booking.com’s BookingSuite has been around since 2013 and there are many anecdotal success stories across multiple market segments and countries.

These systems are easy to use. Most simply require a historical data upload from a hotel’s PMS to get started. This simplicity does have a downside. Because of the “black box” nature of these self-learning algorithms, it is difficult to figure out the logic behind a price recommendation.

Their costs typically range from $1,000 USD to $5,000 USD.

Lots of Data Required

Data is the fuel that powers Revenue Management Systems. Like any other Big Data system, Revenue Management Systems cannot function without data. Data mostly comes from 2 sources.

  1. Property Management Systems (PMS) contains all the historical reservations, transactions, room availability and pricing data. This all needs to be uploaded into a Revenue Management System.
  2. Distribution Channels such as OTAs contain market and competitor data.

China’s Revenue Management Trends

Trend 1 –  Increase in Pricing Strategies

Nicole Yan, Regional Director of Revenue for Cachet Hotel Group in Shanghai, notes that “Many domestic hotels are using a one-size-fits-all pricing approach when in reality, each customer requires their own uniquely catered price strategy.”

Domestic hotels are slowly catching on. One-size-fits-all pricing strategies, although simple to manage, are negatively impacting potential revenues. Hotels need separate pricing strategies for leisure, business, and group travelers. Likewise, travelers who book directly, book for longer stays, or pay deposits all require different rates.

Trend 2 – Empowerment of Staff

Melody Chen, Consultant at Korn Ferry Hay Group the leader in HR Consulting, explains that “Management styles in China are influenced by culture and are paternalistic in nature. Decisions and actions are often given in the form of directives that may not contain the actual rationale. There is little room for debate.”

This works very well for specific task-oriented goals. This style has problems when there are complex and constant operational adjustments that have to be made on a rapid-basis. These adjustments require independent decision-making by the operations staff.

Traditionally, only top-level management have been able to set the prices for domestic hotels. However, with daily and sometimes hourly rate adjustments needed, these enterprises are starting to empower their operations staff with more independent decision-making powers.

Trend 3 – Accessibility of High Tech Solutions

“China’s businesses are very lucky. They get all the newest technologies at a fraction of what it would cost in the West”, states Jason Zhang, Account Manager Connectivity for Booking.com. He explains that “Hoteliers have affordable access to powerful systems that were previously limited to large hotel chains.”

Indeed, the simplicity and pricing of these systems allow any hotel to implement Revenue Management.

Disclaimer

Don’t Be Evil  

Yes, a store can sell million-dollar priced water to a man dying of thirst. However, that man will likely never go back to the store again and the village will likely burn the store down after finding out.

Uber learned this lesson in December 2014, Sydney, Australia. There was a terrorist attack that caused a massive demand for Taxis. Uber raised price 400% to cope with this demand. The public outrage was immediate and Uber’s brand took a huge hit. To Uber’s credit, they quickly realized their mistake and refunded all the additional charges while offering additional free rides.

When price changes, customer’s perception of the brand also changes. There are situations where it may be mathematically correct to use extraordinarily high prices, but be wrong from a logic, brand, and moral perspective.

Humans Still Required

While much of Revenue Management can now be automated with technology solutions, it still requires human oversight.

Market forces are important. Revenue Management strategies need adjustments if a country is going through an economic crisis. Other variable data are also important. Data such as weather conditions, city-wide events, and non-standard events are all still relevant. Although supercomputers can process and compute this type of data, most businesses don’t have supercomputers.

Humans can’t be replaced…yet.

TL;DR (太长;没看) Summary– Customers will pay different prices for the same thing, taking advantage of this is called Revenue Management, Revenue Management Systems can automate this, they used to be expensive and complex, new ones are cheaper and easier to use, be careful raising prices too high or customers will be angry, still requires human oversight.

 

About Michael Li

Michael Li, Director at Luopan, is responsible for product development, international business development, and he’s also the chief coffee maker. He has worked on creating hotel technology solutions such as PMS, Channel Managers, Websites, Booking Engines, and Mobile APPs. He has also led large hospitality project implementations and software integrations.

Michael has a BS in Cognitive Science from the University of California, Los Angeles. For more information, contact Michael at mli@luopan.com.

About Luopan

Luopan is Asia’s most trusted provider for cloud-based hospitality management solutions including PMS, Channel Manager, Website, Mobile APPs, and more. Learn more at www.luopan.com.