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Revenue Management
The science of maximizing revenue earned from a fixed supply
Price-Based Revenue Management
Single product, product assortment, competition (ex. Uber surge pricing)
Capacity-Based Revenue Management
Overbooking, protection limits
When is revenue management useful?
If there is data to predict WTP and demand, prices can be changed easily, or it’s possible to effectively segment customers with different WTPs
Markdown Pricing
Start with a high price so those with high WTP buy early in season and extract as much money from them, then markdown the price by x% and let the next segment of the market buy, continuously mark down with the next segments each time sales drop
What category of products is markdown pricing used for?
Seasonal price items that customers buy at most once in a season (ex. cars, phones, fashion items)
Fare Fences
Let customers segment themselves by what they’re willing to pay
What are the different types of fare fences?
Product-Based (ex. business vs economy class, “free” breakfast at hotels)
Transaction-Based (ex. requirements for advanced purchase, cancellation fees)
Others (ex. flagship stores in cities vs outlet stores in less populated areas)
Price Optimization
Choosing the right price to maximize revenue
Willingness-to-Pay (WTP)
The maximum cost a customer is willing to incur to obtain a unit of product or service
What does a customer receive when buying a product?
A utility (WTP - Price)
True or False: If the maximum net utility for a customer is $0, then they will choose to buy the corresponding product.
True
True or False: If multiple products give the highest net utility, the customer will only choose one of these products.
False
Protection Limits
A random variable representing customers willing to pay the full fare
Overbooking
A random variable for the number of no-shows