A Comparative Analysis of Competitive Intelligence Practices among Leading Cosmetic Brands

Thesis title: A Comparative Analysis of Competitive Intelligence Practices among Leading Cosmetic Brands
Author: Ziaei Nafchi, Marjan
Thesis type: Diploma thesis
Supervisor: Černý, Jan
Opponents: Molnár, Zdeněk
Thesis language: English
Abstract:
One of the world’s largest industries is the cosmetic industry with millions of customers all around the globe. The industry is so vast that it includes all sorts of items from personal care and beauty products. The cosmetic industry is growing rapidly as the demand for such products never seems to vanish. Statistics show that the revenue of the cosmetic market worldwide is currently around 108 billion dollars and it will reach up to approximately 129 billion dollars in 2028 (Statista, 2024). With that being said, in such a huge market, the competition can be challenging, and it is necessary that any company who wants to survive in this growing industry would utilize a strategic approach to stay ahead. The use of Competitive Intelligence (CI) practices has been a necessity leveraged by industry players over the years to maintain their position in the dynamic nature of the industry. Such practices include effectively gathering, analyzing, and leveraging information about market trends, consumer behavior, and competitor strategies. All of which are crucial for making informed and data-driven decisions, developing innovative products, and maintaining a competitive edge in the ever-evolving cosmetic industry. The aim of this thesis is to shed light on CI practices used by three leading cosmetic companies namely L’Oreal, Beiersdorf, and Estée Lauder, while observing their business strategies and their alignment with the practices.
Keywords: Competitive Intelligence; Cosmetic Industry; Competitive Landscape
Thesis title: A Comparative Analysis of Competitive Intelligence Practices among Leading Cosmetic Brands
Author: Ziaei Nafchi, Marjan
Thesis type: Diplomová práce
Supervisor: Černý, Jan
Opponents: Molnár, Zdeněk
Thesis language: English
Abstract:
One of the world’s largest industries is the cosmetic industry with millions of customers all around the globe. The industry is so vast that it includes all sorts of items from personal care and beauty products. The cosmetic industry is growing rapidly as the demand for such products never seems to vanish. Statistics show that the revenue of the cosmetic market worldwide is currently around 108 billion dollars and it will reach up to approximately 129 billion dollars in 2028 (Statista, 2024). With that being said, in such a huge market, the competition can be challenging, and it is necessary that any company who wants to survive in this growing industry would utilize a strategic approach to stay ahead. The use of Competitive Intelligence (CI) practices has been a necessity leveraged by industry players over the years to maintain their position in the dynamic nature of the industry. Such practices include effectively gathering, analyzing, and leveraging information about market trends, consumer behavior, and competitor strategies. All of which are crucial for making informed and data-driven decisions, developing innovative products, and maintaining a competitive edge in the ever-evolving cosmetic industry. The aim of this thesis is to shed light on CI practices used by three leading cosmetic companies namely L’Oreal, Beiersdorf, and Estée Lauder, while observing their business strategies and their alignment with the practices.
Keywords: Competitive Intelligence; Cosmetic Industry; Competitive Landscape

Information about study

Study programme: Information Systems Management
Type of study programme: Magisterský studijní program
Assigned degree: Ing.
Institutions assigning academic degree: Vysoká škola ekonomická v Praze
Faculty: Faculty of Informatics and Statistics
Department: Department of Information Technologies

Information on submission and defense

Date of assignment: 18. 10. 2023
Date of submission: 1. 12. 2024
Date of defense: 30. 1. 2025
Identifier in the InSIS system: https://insis.vse.cz/zp/86083/podrobnosti

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