The Impact of the Internet and Big Data on Price Discrimination:

In the era of big data, if the information collected by operators is comprehensive enough and the algorithms mastered are advanced enough to identify each consumer's willingness to buy and ability to pay, different prices can be set individually for consumers. With the support of big data technology, businesses can use big data algorithms to know which users can accept higher prices and which users should be appropriately priced down in order to get more users, thus giving birth to "big data ripening".

In which, the Internet enterprises, especially the industry giants with a certain monopoly position, use the massive data generated by users on the platform to store, analyze, and model the users, and then build the user's personal image to identify the demand curve of different consumers, the use of price discrimination strategy played to the extreme, so that has always existed in the theory of the first level of price discrimination in the Internet enterprises to develop and expand. Internet companies to flourish.

Price discrimination breakdown

First-degree price discrimination refers to the seller's determination of the upper limit of the buyer's willingness to pay as the selling price of goods. In this case, the seller maximizes profits in charging each buyer. In this case, the more comprehensive the operator's grasp of consumer information, the higher its ability to implement price discrimination, and the higher the profits it can make.

Second-degree price discrimination means offering different versions of the same good or service. In the case of second-degree price discrimination, the seller is often unaware of the characteristics of the buyer and offers the buyer a choice by offering a range of sales agreements that include prices and various terms and conditions.

Third-degree price discrimination, on the other hand, involves sellers setting different prices based on the elasticity of demand of different groups of buyers based on their categorization of buyers. Tertiary price discrimination is more common in reality, movie theaters or attractions charge different prices for students, seniors or minors can be classified as tertiary price discrimination.

Before the age of artificial intelligence, economics focused more on second- and third-degree price discrimination, which was less likely to occur because it was difficult for sellers to accurately grasp the reservation price of each consumer. However, now that data scale has increased and algorithmic analysis has been tightly integrated, first-tier price discrimination has become a real possibility, and has finally transformed from a traditional analytical model that remained on paper to a popular business strategy that has been put into practice.