While the emergence of revenue management and rate optimization is helping to demystify pricing practices, it is important that hoteliers around the world understand the demand characteristics of the various grades of rooms in their facility, along with how price affects demand and design a rate spectrum that is tuned to all of these. This allows hoteliers to take full advantage of their business opportunities, ensuring that they are capturing the maximum revenue at all levels.
Beyond the scope of regular revenue management practices – such as selecting the correct overbooking, rate restrictions and best available rate, lies the challenge of selecting the correct rates to choose from in the first place. Rate Optimization is the practice of selecting the room rates offered in a rate (or price) range based on the historical price sensitivity of demand. The goal of rate optimization is to understand the demand characteristics of rooms and the price sensitivity of demand and utilise the data to define room prices that will capture the maximum revenue over time.
‘Price Sensitivity of Demand’ is a measure of the change in demand relative to a change in price. If a small change in price is accompanied by a large change in demand, the product is said to be elastic (or responsive to price changes). However, a product is inelastic if a large change in price is accompanied by a small amount of change in demand.
Price sensitivity can have a dramatic impact on revenue. For example, if the price offered for a room in a hotel is too low, the demand for the product may be significant; however the revenues from the sale of the product will also be low. In turn, if a rate offered is too high, there is a risk that not enough demand will materialize, and both situations may result in a reduction of potential revenue.
Used as a complement to ‘Price Sensitivity,’ ‘Price Elasticity of Demand’ measures the effect of price changes on the quantity demanded. Sometimes a price increase causes quantity demanded to decrease significantly, other times it decreases only slightly. ‘Price Elasticity of Demand’ is important as it predicts the effects on revenue as demand and price change.
Price elasticity analysis must be augmented by accounting for real world factors. Hoteliers need to be able to adapt and learn to deal with non-quantifiable events such as major sporting events and random effects on demand. A change in demand occurs when one or more of the determinants of demand changes, even when the price is held constant.
Factors that influence demand include consumers’ preferences, income, economic and market conditions (including non-quantifiable events) and the prices of substitute goods. Many of these factors are inherent in historical data and need to be considered when analyzing demand sensitivity.
The elements that make up an effective rate optimization analysis are fundamental to a successful and profitable revenue management program. After gathering historical business data that includes capacity, occupancy and rate information for various products, a thorough analysis of the historical data must be conducted.
Following this analysis, an evaluation of the price sensitivity of demand is necessary to determine refined price points. Hoteliers can then estimate reference revenues under current and refined rate / price ranges, informing revenue managers about appropriate present pricing information, relative to their market segment. Typically, an effective rate optimization analysis requires a minimum of 12 months of historical data to truly recognize demand, occupancy trends and patterns.
Some examples of historical data which are important in a rate optimization analysis include room types; competitor information; total occupancy and revenue; occupancy by date and available capacity. Once the refined price range is introduced, an increase in hotel revenues across defined rate periods can be expected. After the refined rate spectrum has been in effect for 120 days, a comparison should be made by the hotel to determine the improved revenue performance.
Article Source Ideas.com To continue reading , please Click Here