Industry Update
Opinion Article 3 November 2020

The ‘New Normal’: Reimagining Revenue Management in a COVID-19 World

Advertorial by Erik Muñoz, Chief Commercial Officer (CCO) at Lybra.tech

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The hotel revenue management technology sector is an area where the biggest impact of the pandemic can be seen in a very clear way. Traditional RM technology was reliant upon algorithms, most often based primarily on historical demand patterns - such as booking lead times, booking pickup by segments and seasonal stay patterns by day, week or month - as a basis for determining the best possible room rate, at any given time. Of course, because of the pandemic, revenue management systems (RMS) reliant on historical data have now become obsolete, as hotels worldwide are experiencing unprecedented market conditions, which can't be ignored or treated as a temporary blip.

To best understand why historical data becoming obsolete is such a game-changing factor in the 'new normal' of revenue management, imagine that an RMS algorithm is like a recipe for your favourite meal, which has several ingredients and a sequence of steps in order to achieve the optimal result. Now imagine that your recipe's key ingredient (historical data) has become spoiled, making it impossible for you to make the correct portions all of for your dinner guests (demand forecast), you will now need to prepare your meal (RM algorithm) with other ingredients (the right data) to ensure that your dinner party is a success.

So, let's look at these new (revenue management) ingredients and examine their impact on hotel demand:

Real-time market demand indicators

Real-time market demand indicators are important to ensure every potential new booking can be captured at the optimal price. While there are many sources for hotel pricing data, it's important that hotels have a complete picture of the competitor landscape to price competitively; hotel prices must be examined 365 days ahead, for every room type, as well as the individual options available for each room type - including room-only, breakfast inclusive rates, non-refundable vs. refundable prices. Online bookings can be finalized 24 hours a day based on the time zone of your potential guests, so it's important to review and/or revise your prices more than once per day.

Macro-View of Demand

In addition to your specific hotel competitor prices, it's important to take a macro-view of the demand pressure for your destination. There are many factors that contribute to the demand pressure for your city, including travel agent hotel booking searches, frequency of hotel price changes, hotel cluster search analytics and trends in flight search data.

Hotel cluster search analytics is a very valuable insight into the micro-demand for hotels in your locale. Integrating your RMS with hotel booking engines that encompass the range of hotels in your destination will give you much deeper insights than your standard price shopping data.

Online Reputation Score

In revenue management data analysis, the actual guest selection/booking process is often overlooked. Even if you have the best quality data, with the highest frequency of data updates and interfaces with the PMS or Channel Manager, none of that matters if potential customers' perception of value of your property is lower than your hotel's actual position in the marketplace.

Your hotel competitors will have online reputation scores visible across most online booking platforms and your relative ranking won't change too much across those channels. While you have direct control over your pricing, you don't have direct control over your online reputation score; your guests will determine how well your hotel matched, exceeded or failed to meet their expectations, resulting in an online review and a score for their stay with you.

That being said, you do have indirect control over these results, in the sense that your guests will rank their experience of various elements of their stay - including cleanliness, comfort, location, facilities, staff, free WiFi and value for money; the majority of these factors can be influenced by your hotel's service delivery standards.

When considering booking a room at a hotel, most guests will compare the relative value across a shortlist of hotels, which is, effectively, a combination of pricing and reputation scores; it's important that your revenue management technology provides reputation data analytics directly within the RMS, or else your revenue manager is missing an entire dataset that is very important to potential guests.

Flight Search Data

Flight search data is particularly important in the current and future 'post-COVID' era, as "overall capacity is down nearly 50 million seats or 47%, globally," and border closures have created highly volatile travel restrictions in many markets.

Of course, in most cases, flight travel is highly correlated with hotel stays; therefore, flight search data is a leading indicator for travel intent and, in turn, for hotel booking intent. Knowing about flight search patterns, broken down by country of origin, targeted destination, and with a weekly or monthly trend summary, is very useful for all hotels, particularly those where a majority of their guests arrive via airports.

Having all the right data is a fantastic way to improve your hotel revenue management analysis and strategy; however, it's not enough. There are two other vital elements to a successful - and profitable - revenue management strategy, no matter the level of demand in your market or worldwide:

Automation

Your property also needs to have your core systems integrated and automated in order to ensure optimal efficiency and speed to market. Gathering demand data should be an automated feature of your revenue management system, including flight data, hotel competitor prices, online reputation data and more.

Once you have decided upon your strategic direction, based on the insights gathered from your RMS, those decisions should be automatically sent to your hotel PMS and in some cases, also sent to your hotel CRS or Channel Manager (depending how your online distribution is structured). Your time is valuable and you shouldn't have to manually enter any pricing updates into the PMS or your online distribution systems.

The Knowledge & Experience of a Revenue Manager

Finally, when we talk about revenue management technology and automation, it's important to remember how necessary the human element is to a property's revenue management success, even when using an AI-based system. Here's why…

An RMS on 'autopilot' uses raw data (complete data, or incomplete data in some cases), which it analyses to solve a price-demand calculation. On the other hand, strategy is often a decision based on emotion or instinct, either on the part of potential guests or the hotel's competitor; in other words, strategy is a human trait. If your system operates in a fully automated manner (without human input), you will be missing out on the valuable opportunity to apply revenue management strategy, which is something only an experienced revenue manager can apply, not an algorithm.

Your revenue management system - like Lybra's Assistant RMS does - should fully support the combination of human input and advanced analytics to ensure the best possible results for your property. Only by balancing both artificial intelligence and human revenue management strategy can a hotel survive - and thrive - in the current and post-COVID world.

So, to return to our analogy from the beginning of this article, now that all of your human and technological elements are in line… Dinner is served. Bon appétit!

Related Product

Lybra's Assistant Revenue Management System (RMS)

Lybra"s real-time, machine learning, demand-centric Assistant RMS is a sophisticated, flexible, module-based machine learning revenue management system, which will simplify and automate your property"s daily revenue management operations to boost occupancy, ADR and RevPAR – even in times of depressed demand, like the COVID-19 pandemic.

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Erik Muñoz

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    About Lybra (Formerly Lybra.Tech)
    Lybra is a leading global hospitality technology company, offering an innovative, machine learning revenue management system (RMS) for the global hospitality industry. Lybra's Assistant RMS was designed to improve the quality of hoteliers' lives, by simplifying and automating daily operations to skyrocket their property's bookings and revenue - even in times of decreased demand, like the current COVID-19 pandemic.

    In May 2020, Lybra was acquired by The Zucchetti Group, a leading international technology company offering software, hardware and ITC services to many global sectors, including hospitality, education, transport and logistics, manufacturing, among others. As part of The Zucchetti Group, Lybra is even more well-positioned to offer hotel clients the most accurate pricing suggestions because of the wealth of international market and demand data - compiled by the global hospitality technology companies that are owned by The Zucchetti Group - that is now integrated into the company's Assistant RMS. To learn more about Lybra, visit lybra.tech.

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