We describe the effect of social media advertising content on customer engagement using data from Facebook. We content-code 106,316 Facebook messages across 782 companies, using a combination of Amazon Mechanical Turk and Natural Language Processing algorithms. We use this dataset to study the...

Personalization is becoming ubiquitous on the World Wide Web. Such systems use statistical techniques to infer a customer’s preferences and recommend content best suited to him (e.g., “Customers who liked this also liked…”). A debate has emerged as to whether personalization has...

We investigate the moderating effect of product attributes and review ratings on {views, conversion|views (conversion conditional on views), final conversion} of a purchase-based collaborative filtering recommender system on an e-commerce site. We run a randomized field experiment on a top...

We investigate the impact of collaborative filtering recommender algorithms (e.g., Amazon’s “Customers who bought this item also bought”) commonly used in e-commerce on sales diversity. We use data from a randomized field experiment run on the website of a top retailer in North America...

This chapter presents a selective review of a literature in marketing that analyzes diffusion and pricing over the product life-cycle. I primarily focus on empirical work, and on papers that deal with the dynamics of pricing over time. I discuss how recent empirical work has linked outcomes to...

The erosion of high-end fashion brands by fast fashion copycats (e.g., Zara, H&M) has provoked ongoing controversies and unceasing legal attempts to copyright fashion designs. Despite this tension around the enforcement of copyrights and the purported negative impact of copycats, the effect of...