Improving Room Rate Yield at a Luxury Hotel

The Challenge

At one of the luxury hotels where I was general manager, the weekly revenue strategy meetings were proving painful and wasting a lot of time. 

It was extremely difficult to analyse and finalise our room rate strategy and forecasts.

My team had to rely on information provided by the sales and reservation team members, which changed frequently, meaning that the information we needed was often either inaccurate or not available at all.

The Solution

I changed the existing business process, designing a room rate yield management system which we implemented with support from a well-known technology company.

In order to develop the new system, we had to share the last two years’ actual historic data of room sales, average room rates and RevPar. 

To give us some market data, we identified our six main competitors and six secondary competitors and gathered information on their room rates.

We then highlighted special events, public holidays, low, medium, and high seasons, etc for the year ahead before indicating what rate we planned to sell each category of room at.

Once this work was completed, we only needed around one hour a week to review live data to decide our room rate strategy.

Depending on the business need at the time, we were able to deploy a variety of room rate strategies: 

  • Occupancy based pricing: This allowed us to set hotel room rates based on demand and supply.
  • Forecast based pricing: This was based on the booking history of the previous months, plus seasonality, events, demands, and promotions.
  • Market competition based pricing: The system constantly monitored our competitors’ room rates online to understand their pricing strategy.
  • Segment-based pricing: We were able to price by segments such as corporates, FITS (fully independent travellers), groups and OTAs, including data on volume, frequency of guests, cancellations, etc.
  • Length of stay based pricing: This was varied according to the duration of a guest’s stay. 
  • Guest type based pricing: By using accurate data, we were able to understand the different market segments and sell the same room at different prices for different guests. 
  • Cancellation policy based: Using a well-planned non-refundable cancellation policy enabled us to increase revenue. 
  • Upselling based pricing: This was very beneficial during the booking process. Upselling encourages guests to spend more at the time of booking. 
  • Cross-selling based pricing: This has now become popular and excites customers to make additional purchases like transportation, spa, dinners etc.
  • Loyal customer based pricing: This is an effective hotel pricing strategy if used in the correct manner. There are high chances of existing guests to visit again at your hotel.

At the same time the system showed us in green, orange and red which rates would be too low, too high or in the right range based on live occupancy data, as the system was also connected to the POS system we received booking status on a daily basis, which was automatically updated.

The Result

The first result was that we saved hours of time per week in forecasting room rates and had the reassurance that we were using accurate, timely data.

The new system also enabled the Sales and Reservation teams to spend more time on their jobs of selling and booking rooms. 

We saw impressive results: annual room revenues increased by 30%, ADR increased by 19% and RevPar increased by 9.2%

The owner’s investment in the technology that enabled us to achieve this was paid back within 8 months.

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