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Chapter 1 • An Overview of Business Intelligence, Analytics, and Decision Support 59

Application Case 1.7

Gilt Groupe’s Flash Sales Streamlined by Big Data Analytics
Gilt Groupe is an online destination offering flash software keeps track of responses to offers and sends
sales for major brands by selling their clothing and the same offer 3 days later to those customers who
accessories. It offers its members exclusive discounts haven’t responded. Gilt also keeps track of what
on high-end clothing and other apparel. After regis- customers are saying in general about Gilt’s prod-
tering with Gilt, customers are sent e-mails containing ucts by analyzing Twitter feeds to analyze sentiment.
a variety of offers. Customers are given a 36-48 hour Gilt’s recommendation software is based on Teradata
window to make purchases using these offers. There Aster’s technology solution that includes Big Data
are about 30 different sales each day. While a typical analytics technologies.
department store turns over its inventory two or three
times a year, Gilt does it eight to 10 times a year. Thus, Questions for Discussion
they have to manage their inventory extremely well 1. What makes this case study an example of Big
or they could incur extremely high inventory costs. Data analytics?
In order to do this, analytics software developed at 2. What types of decisions does Gilt Groupe have
Gilt keeps track of every customer click—ranging to make?
from what brands the customers click on, what colors
they choose, what styles they pick, and what they What We can Learn from this application
end up buying. Then Gilt tries to predict what these case
customers are more likely to buy and stocks inven-
tory according to these predictions. Customers are There is continuous growth in the amount of struc-
sent customized alerts to sale offers depending on the tured and unstructured data, and many organiza-
suggestions by the analytics software. tions are now tapping these data to make actionable
That, however, is not the whole process. The decisions. Big Data analytics is now enabled by the
software also monitors what offers the customers advancements in technologies that aid in storage and
choose from the recommended offers to make more processing of vast amounts of rapidly growing data.
accurate predictions and to increase the effectiveness Source: Asterdata.com, “Gilt Groupe Speaks on Digital Marketing
of its personalized recommendations. Some custom- Optimization,” asterdata.com/gilt_groupe_video.php (accessed
ers do not check e-mail that often. Gilt’s analytics February 2013).

1.10 plan oF the Book
The previous sections have given you an understanding of the need for using informa-
tion technology in decision making; an IT-oriented view of various types of decisions;
and the evolution of decision support systems into business intelligence, and now into
analytics. In the last two sections we have seen an overview of various types of analyt-
ics and their applications. Now we are ready for a more detailed managerial excursion
into these topics, along with some potentially deep hands-on experience in some of the
technical topics. The 14 chapters of this book are organized into five parts, as shown in
Figure 1.6.

part i: Business analytics: an overview
In Chapter 1, we provided an introduction, definitions, and an overview of decision sup-
port systems, business intelligence, and analytics, including Big Data analytics. Chapter 2
covers the basic phases of the decision-making process and introduces decision support
systems in more detail.

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