Revenue Manager Pricing Strategy. CAESARS ENTERTAINMENT ® | PROPRIETARY AND CONFIDENTIAL 2 Elasticity Model Log linear regression model to estimate demand.

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Presentation transcript:

Revenue Manager Pricing Strategy

CAESARS ENTERTAINMENT ® | PROPRIETARY AND CONFIDENTIAL 2 Elasticity Model Log linear regression model to estimate demand elasticity –Use historical price/quantity data to understand demand patterns –Assumption is isoelastic demand (constant elasticity at all price points) –Coefficient of natural log of price represents elasticity estimate To improve model predictive power, we control for non own-price effects –External influences of Demand Changes to competitor prices (cross price elasticity) Changes to discretionary income (income effect) Macroeconomic effects (potential substitute effects) –Internal influences of Demand Changes to internal competitor prices (cross price elasticity) Changes to marketing campaigns OTB Pacing / mix changes by channel –Seasonal influences of Demand Weekday/Weekend effects Month/season effects Holiday effects 2 Time Series Data Internal Data External Data StrategyImplementationRecommendation

CAESARS ENTERTAINMENT ® | PROPRIETARY AND CONFIDENTIAL 3 Price Elasticity Strategy Price elasticity of demand –Price elasticity of demand is an economic measure to understand customer demand sensitivity to price changes –The formal definition is elasticity equals change in quantity divided by change in price For example, an elasticity = -2 = 2% divided by -1% => a 1% drop in price yields 2% increase in quantity –If elasticity is between 0 and -1, demand is “inelastic” (customer is relatively insensitive to price changes) –If elastic is smaller than -1, demand is “elastic” (customer is relatively sensitive to price changes) Implications for Hotel revenue opportunities –The table below represents increased revenue opportunities given an understanding of demand elasticity 3 Optimum Strategy: If demand is inelastic, raise prices. If demand is elastic, lower prices StrategyImplementationRecommendation