Market Segmentation Analysis

课程
en
英语
30 时
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  • 来自www.edx.org
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  • 5 序列
  • 等级 中级

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课程详情

教学大纲

Module 1: Introduction and Steps 1 and 2
We define market segmentation analysis, explain why it is the basis of marketing planning, and why it informs both strategic and tactical marketing decisions. We provide an overview of the ten-step process in market segmentation analysis. In Step 1, we explain the requirements for market segmentation, helping learners decide whether their organisation is ready to segment. In Step 2 we specify the ideal target segment, including segment evaluation criteria.

Module 2: Steps 3 and 4
In Step 3,we describe collecting data and define the segmentation variables and criteria, and discuss different sources of data. In Step 4 we explore the data and discuss data cleaning and how to pre-process categorical and numeric variables. We also demonstrate how to use R, to assist you with exploring the data.

Module 3: Step 5
In Step 5,we extract market segments and group consumers using distance-based, hierarchical, and partitioning methods; hybrid approaches; and model-based methods. We also explain data structure analysis.

Module 4: Steps 6 and 7
In Steps 6 and 7, we profile and describe segments. We use traditional approaches as well as visualisation techniques to identify key characteristics of market segments. In Step 7 we develop and visualise a complete picture of market segments; this includes testing and predicting segment differences in descriptor variables.

Module 5: Steps 8, 9 and 10
In Step 8, we select the target segments including the tasks targeting decision and market segment evaluation. In Step 9 we customise the marketing mix. We also discuss the implications of market segmentation for marketing mix decisions concerning product, price, place,and promotion. Finally, in Step 10, we evaluate the success of the segmentation strategy, and stability of segment membership. We conclude with a discussion of segment hopping and segment evolution.

先决条件

No experience or knowledge in a particular academic discipline is required, although an undergraduate degree in business or statistics is recommended.

讲师

Sara Dolnicar
ARC Laureate Fellow
The University of Queensland

Bettina Grün
Associate Professor in Applied Statistics
Johannes Kepler University, Linz

Friedrich Leisch
Professor and Head, Institute of Applied Statistics and Computing
The University of Natural Resources and Life Sciences, Vienna

编辑

昆士兰大学是一所公立研究型大学,主要位于澳大利亚昆士兰州首府布里斯班。昆士兰大学于 1909 年由昆士兰议会创立,是六所砂岩大学之一,是各州最古老大学的非正式称谓。

结合 2023 年最古老大学的三个世界排名,昆士兰大学在澳大利亚排名第二,在世界排名第 42 位。昆士兰大学还是澳大利亚领先的八所太平洋大学国际研究密集型协会 edX 的创始成员。

平台

EdX est une plateforme d'apprentissage en ligne (dite FLOT ou MOOC). Elle héberge et met gratuitement à disposition des cours en ligne de niveau universitaire à travers le monde entier. Elle mène également des recherches sur l'apprentissage en ligne et la façon dont les utilisateurs utilisent celle-ci. Elle est à but non lucratif et la plateforme utilise un logiciel open source.

EdX a été fondée par le Massachusetts Institute of Technology et par l'université Harvard en mai 2012. En 2014, environ 50 écoles, associations et organisations internationales offrent ou projettent d'offrir des cours sur EdX. En juillet 2014, elle avait plus de 2,5 millions d'utilisateurs suivant plus de 200 cours en ligne.

Les deux universités américaines qui financent la plateforme ont investi 60 millions USD dans son développement. La plateforme France Université Numérique utilise la technologie openedX, supportée par Google.

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