How does big data create monopoly?

In the article “Big data is coming for your purchase history – to charge you more money“, the author talks about what role does big data play in price discrimination, and how does that give sellers market power that is greater than traditional monopolists.

Based on the extent to which a market is segmented, price discrimination can be ranked in three degrees. Group pricing, or third-degree price discrimination, divides the market in segments and charge the same price in each one. For instance, students are distinguished from adults by their student ID cards and are charged lower price in cinemas. Group pricing is an attempt to simplify the diverse market and is not very accurate. Product versioning, or second-degree price discrimination, uses slightly different versions of the same product to let consumers differentiate themselves. The difference can either be in quantity or quality of the product. For example, businesses usually have higher discount than individuals when they buy products in bulk. Operating systems usually have business version and personal one.

Perfect price discrimination, or first-degree price discrimination, allows a seller to charge the maximum willingness of each buyer. With big data, this has become possible. Netflix, for instance, has increased its profit by 1.4%, using data from web browsing history to recommend different streaming services to different users at  different prices. With enormous data collected from consumers’ browsing history, a market of one is created. Each consumer now face a far more knowledgeable and sophisticated seller.

Because big data allows a seller to charge personalized price, even a seller in a competitive market can become a price setter, just like a traditional monopolist. Maybe, one day market price will no longer matter since every single person is charged a personalized price that can be changed in a millisecond.

 

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