Podcast – How to Turn Online Data into a Pricing Strategy That Works

If you’re a frequent online shopper, you already know you’re being watched. Companies collect reams of data based on your browsing and purchasing patterns. There’s so much data, in fact, that it’s easy to get lost in the numbers. That’s where Ken Moon comes in. A professor of operations, information and decisions at Wharton, Moon is researching how retailers can use online data to create effective pricing policies. He visited with Knowledge@Wharton to discuss his paper, "Randomized Markdowns and Online Monitoring," which was co-authored with Kostas Bimpikis and Haim Mendelson of Stanford University’s Graduate School of Business.

An edited transcript of the conversation follows.

How to Turn Online Data into a Pricing Strategy That Works