Gilt Groupe is an online destination offering flash sales for major brands by selling their clothing and accessories. It offers its members exclusive discounts on high-end clothing and other apparel. After registering with Gilt, customers are sent e-mails containing a variety of offers. Customers are given a 36-48 hour window to make purchases using these offers. There are about 30 different sales each day. While a typical department store turns over its inventory two or three times a year, Gilt does it eight to 10 times a year. Thus, they have to manage their inventory extremely well or they could incur extremely high inventory costs. In order to do this, analytics software developed at Gilt keeps track of every customer click—ranging from what brands the customers click on, what colors they choose, what styles they pick, and what they end up buying. Then Gilt tries to predict what these customers are more likely to buy and stocks inventory according to these predictions. Customers are sent customized alerts to sale offers depending on the suggestions by the analytics software.

Questions for Discussion
1. What makes this case study an example of Big Data analytics?
2. What types of decisions does Gilt Groupe have to make?