We all know that demand forecasting is the holy grail of revenue generation for hotels. As hoteliers, you need to measure room and hotel demand at various levels and for different market segments to develop profit-making strategies. It involves gathering sizeable information of the market and integrate the efforts of different departments to enhance your business performance.
How do you go about measuring demand? You could be missing the benefits that a simple tweak to your approach can bring – focusing on city demand forecasting.
Unprecedented demand offers an opportunity to earn more revenue. However, with a new or a rare event coming to your city you need to create a new Revenue Strategy to tap this demand because you do not want to land up in a situation where there are not enough rooms to sell when the hotel demand is at its peak and you miss the opportunity to sell your rooms at a premium price.
Earlier, the hotel PMS provided all the data used for forecasting within a hotel. This system holds years of historical information across a variety data types like – room types, customer segments, the length of stays and more. With that data along with booking pace, hotels generated forecasts and thus made pricing strategy. But, were those pricing decisions ideal? Perhaps not. Here is why.
Big data is providing a new facet to the hotel demand forecasting. New data sources like air booking data, social reviews, ratings, and even weather—can help hotels better understand the opportunity of their upcoming demand.
Today, there is a lot of information available about consumer shopping habits. New data points include competitor-pricing, events in your town and macro-economic & geographic factors, air booking data, social reviews and ratings, weather, and web shopping data.
