In a few weeks in Management 405, we will start a module entitled "Advanced Pricing". There, we will learn various techniques for extracting more surplus from our customer base by charging different prices to different customers or to different classes of customers. In economics, this is known as price discrimination. It can be done with auctions, with product versioning, or with prices tailored to certain classes of clients identified by characteristics that are hard to conceal.
A recent HBR article by Rafi Mohammed usefully summarized the ins and outs of price discrimination, applied to online selling. The author resorts to a nice euphemism to characterize price discrimination, one that entails a less pejorative connotation: he calls it personalized pricing. Who does not like personalization?
The article highlights a fundamental tension: with the advent of electronic transactions and big data, it becomes easier to tailor prices to different kinds of customers by generating empirical regularities on their willingness to pay from the wealth of transactions data that online sellers possess. Can you identify gullible customers? Customers whose opportunity cost of time is such that they won't shop for lower prices? Then charge them higher prices than you would to Mr. Scrooge! The temptation is obvious, but the tension arises due to the limits of these practices. One limit is that price discrimination has to be incentive compatible. If I can delete all my cookies and project an online footprint that makes sellers believe I am Mr. Scrooge, their price discrimination schemes may fail. After all, even a high willingness to pay customer likes a good deal! Second, ethics can come in the way. After all, you are treating different classes of consumers differently. Better make sure you don't run afoul the basic rules of human decency in the process. Finally, price discrimination can be illegal, especially if it results in a monopolistic outcome or if it based on traits over which it is illegal to charge different prices. We will discuss all this in much greater detail very shortly.
For referring me to this HBR article I thank your classmate Rafael V. Almeida.