Chapter 12 Case studies
12.1 Opening Vignette: Sephora Excels with Chatbots
1. List and discuss the benefits of bots to the company.
Bots help Sephora by improving customer engagement and offering services 24/7 without
needing a human representative all the time. They reduce the workload on staff by handling basic
questions and tasks like appointment booking and product suggestions. This saves the company
time and money. Also, bots collect useful data about customer preferences, which Sephora can
use to improve marketing and product recommendations. They also make the shopping process
faster and easier, which can lead to more sales.
2. List and discuss the benefits of bots to customers.
Customers benefit from Sephora’s bots because they make the shopping experience more fun
and convenient. The bots help customers find the right products based on their preferences or
pictures they upload. They can book appointments, get beauty tips, and even try on makeup
virtually. This is especially helpful for people who like to shop online or use their phones.
Overall, it makes shopping more personal and enjoyable for customers.
3. Why were the bots deployed via Messenger and Kik?
Sephora chose Messenger and Kik because a lot of young people already use these messaging
apps. It’s easier to reach customers where they are already spending their time. This also makes
it more natural for users to talk to the bots like they are chatting with a friend. It helps Sephora
connect with a younger audience and provide services without asking customers to download
another app.
4. What would happen to Sephora if competitors use a similar approach?
If competitors also start using advanced bots, Sephora will need to keep improving its
technology to stay ahead. The market could become more competitive, and customers might go
to other brands if they offer better or more fun experiences. Sephora will have to continue
innovating and making sure their bots provide the best help and recommendations to keep
customers loyal.
Application Case 12.3 Netflix Recommender: A Critical Success Factor
1. Why is the recommender system useful? (Relate it to one-to-one targeted marketing.)
The recommender system is useful because it helps Netflix give each user personalized
suggestions based on their unique preferences, which is what one-to-one targeted marketing is all
about. Instead of sending the same message or offer to everyone, Netflix can show content that
matches what each person likes. This makes users feel like Netflix understands them, which
keeps them watching longer and makes them more likely to keep their subscription.
2. Explain how recommendations are generated.
Netflix creates recommendations by looking at what people have watched and liked before, and
then compares that data with what similar users enjoy. This is called collaborative filtering. They
also use deep learning and AI to look at large amounts of data and find patterns in viewing
habits. Over time, the system learns more about each user and improves the accuracy of its
suggestions. This helps Netflix recommend shows and movies people are more likely to enjoy.
3. Amazon disclosed its recommendation algorithms to the public but Netflix did not. Why?
Netflix did not share its recommendation algorithm because it sees it as a competitive advantage.
If they reveal how it works, other companies might copy it, which would reduce Netflix’s edge
in the market. By keeping it private, Netflix protects its technology and stays ahead of
competitors like Amazon and Google, especially since the recommendation system is a big part
of what makes users stay loyal.
4. Research the research activities that attempt to “mimic the human brain.”
Research activities that try to mimic the human brain are mostly part of a field called artificial
intelligence, especially deep learning and neural networks. These systems try to copy how the
brain works by using layers of algorithms that learn from data. They are used in things like
image recognition, speech recognition, and recommendation systems. Companies like Google,
Facebook, and Microsoft are also doing a lot of research in this area to make their AI smarter and
more human-like.
5. Explain the changes due to the globalization of the company.
When Netflix expanded to over 190 countries, they had to change their recommendation system
because people in different parts of the world have different tastes and cultures. The old system
only worked well in the country where the data was collected. The new system had to learn from
a global audience and understand what people from many backgrounds like to watch. It was
harder at first, especially in new regions, but over time, the system improved and gave better
recommendations worldwide.