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Retos de los RMS para construir la estrategia de precios perfecta de nuestro hotel

por Nuria García

RMS Aims to Build the Perfect Pricing Strategy for Hotels

The aim of revenue management is to pull together large amounts of third-party data available on the web. Efficient marketing and distribution of your hotel’s room supply is a latent necessity and technology is the best remedy for this.


The knowledge that RMS provides at the market level helps you determine your competitive position and direct competitors. RMS can synthesize large volumes of data. It can also work with past, present and future rates and room availability, as well as present information in a way that is easy to understand, allowing you to run your hotel more efficiently.


Apply business intelligence to hotel management to improve hotel profitability. Traditionally, revenue managers worked with figures such as ADR and RevPAR to measure hotel occupancy, but today the keyword is GOPPAR, which measures gross operating profit per available rooms. According to the market, an RMS must offer the following features and benefits:


  • A flexible tool that can integrate all kinds of market situations. We are used to working with revenue management tools that are fixed or have limited flexibility that do not track hotel room reservations or if they do, it’s done in a very standard way. Some challenges experienced by hoteliers involve structuring data and tracking segmented travelers. The solution-determine demand channels, such as:

    • Groups

    • Wholesale

    • Corporate negotiations

    • GDS

    • OTA’s and third party bookings

    • Direct booking

    • Booking center

Hoteliers need a solution that will help them make time-sensitive pricing decisions that accurately reflect market conditions. If an RMS places limitations on the hotel, chances are that that system will not meet the hotel´s needs.


By having an unrestricted perception of demand, hoteliers can increase profitability and experience the following advantages:  


  • Improvements in forecasting. Data demand without constraints shows high and low demand periods of hotel room occupancy for future arrival dates for your hotel’s competitive set.

  • Optimize ADR. Adapt this rate and future demand to traveler behavior.

  • Highest  level of certainty. Unconstrained demand is important for future booking patterns because it offers levels of certainty during uncertain times.

  • RMS as a tool that allows revenue management, marketing and sales departments to work together. The information provided by the solution is vital for developing strategic marketing actions. An RMS compiles and interprets valuable information, allowing marketing departments to identify segments and anticipate demand trends. Valuable information like:

    • Types of travelers according to demographics, interests and types of reservation.

    • Significant geographical sources regarding product consumption.

    • Price sensitivity is a factor that varies according to source markets and demographics.

    • Traveler responsiveness to changes in competitors’ prices.

This information can be perfectly adapted to the ad campaigns developed in Google Adwords, Facebook Ads or any other tool that allows social ads to be segmented.


  • Understand forecasting and room availability for your competitive set. The data an RMS provides about supply and demand is highly valuable information, and having access to this knowledge makes it easier for revenue managers to plan sales strategies. Features such as real-time updates and the ability to implement changes, based on business rules, offer flexibility.

  • Understand competitors from different booking portals- beyond conventional ones. The rise of new and competitive online hospitality marketplaces such as Airbnb or Windu has generated the need to consider their rates within the hotel’s pricing strategy. Currently, there’s no real comparative analysis that allows hoteliers to compare their rates versus the rates from Airbnb or Windu.

We won’t see any innovation with the way historical data is used for budgeting and forecasting since that has already been done. Instead, we’ll see breakthroughs in predictive analytics, allowing  hotels to directly influence consumption.

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