What is personalization, or personal value pricing, and how can it be used at the beginning of a product’s life cycle to increase revenues?

 

Personalization or personal value pricing is when merchants adjust prices based on their estimate of how much a customer truly values the product. For example, Web merchants may charge committed fans of a musician a higher price for the privilege of receiving a new CD before its official release to retail stores. It is a specific type of dynamic pricing in which merchants match their prices to the personal value that consumers will receive from a purchase by estimating what they believe any given consumer is willing to pay. 

It can be used at the beginning of a product’s life cycle to increase revenues because a certain consumer segment, the so-called early adopters, is willing to pay more for a newly released product.

Comments

Popular posts from this blog

Suppose that a data warehouse for Big-University consists of the following four dimensions: student, course, semester, and instructor, and two measures count and avg_grade. When at the lowest conceptual level (e.g., for a given student, course, semester, and instructor combination), the avg_grade measure stores the actual course grade of the student. At higher conceptual levels, avg_grade stores the average grade for the given combination. a) Draw a snowflake schema diagram for the data warehouse. b) Starting with the base cuboid [student, course, semester, instructor], what specific OLAP operations (e.g., roll-up from semester to year) should one perform in order to list the average grade of CS courses for each BigUniversity student. c) If each dimension has five levels (including all), such as “student < major < status < university < all”, how many cuboids will this cube contain (including the base and apex cuboids)?

Suppose that a data warehouse consists of the four dimensions; date, spectator, location, and game, and the two measures, count and charge, where charge is the fee that a spectator pays when watching a game on a given date. Spectators may be students, adults, or seniors, with each category having its own charge rate. a) Draw a star schema diagram for the data b) Starting with the base cuboid [date; spectator; location; game], what specific OLAP operations should perform in order to list the total charge paid by student spectators at GM Place in 2004?

Explain network topology .Explain tis types with its advantages and disadvantges.