Market Segmentation Analysis

Course
en
English
30 h
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Source
  • From www.edx.org
Conditions
  • Self-paced
  • Free Access
  • Fee-based Certificate
More info
  • 5 Sequences
  • Intermediate Level

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Course details

Syllabus

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.

Prerequisite

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

Instructors

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

Editor

The University of Queensland is a public research university located primarily in Brisbane, the capital of the Australian state of Queensland. Founded in 1909 by the Queensland Parliament, UQ is one of six sandstone universities, an informal designation of the oldest university in each state. 

Combining the three world rankings of the most established universities in 2023, the University of Queensland is ranked 2nd in Australia and 42nd in the world. UQ is also a founding member of edX, Australia's leading group of eight and the international research-intensive association of Pacific universities.

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