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Market Segmentation Analysis

University of Queensland via edX

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Overview

Conducting market segmentation analysis and committing to a long-term market segmentation strategy is a complex and challenging journey for any organisation. This course will guide you through the entire process of market segmentation analysis and offers a ten-step process that makes customer segmentation efficient and organised.

We will start from the very beginning when the decision is first made to conduct market segmentation analysis, to the final stages of evaluating the success of the strategy and monitoring the market for possible changes highlighting segmentation variables such as geographic segmentation, psychographic segmentation, behavioural segmentation and demographic segmentation.

We will explore how to leverage statistical concepts such as the hierarchical clustering and partitioning methods, exploratory data analysis, biclustering, mixture models and regression models into the organisation’s segmentation strategy.

The concepts and skills you will gain in this course are relevant across a wide range of contexts in the for-profit and not-for-profit sectors.

This course will also allow you to conduct customer segmentation analysis. You will be able to replicate the calculations and visualisations demonstrated in the customer segmentation models by downloading the data and the R code (a free open-source statistical computing environment and widely acknowledged as the universal language of computational statistics).

This course is based on and taught by the authors of the book “Market Segmentation Analysis; Understanding It, Doing It, and Making it Useful”. You will have full access to this valuable resource when you enrol in this course.

Syllabus

Module 1: Introduction and Steps 1 and 2
We define market segmentation analysis and explain why it is the basis of marketing planning, informing both strategic and tactical marketing decisions. An overview of the ten-step process in market segmentation analysis is provided, progressing to Step 1, where the requirements for market segmentation are explained to help learners decide whether the organization is ready to segment. Step 2 specifies the ideal target segment, including segment evaluation criteria.

Module 2: Steps 3 and 4
Step 3 describes collecting data and includes defining the segmentation variables and criteria, as well as discussing different sources of data. Step 4 explores the data and includes data cleaning and pre-processing of categorical and numeric variables. To help you with exploring data, a demonstration on how to use R is also included.

Module 3: Step 5
Step 5  focuses on extracting market segments and includes grouping consumers using distance-based, hierarchical, and partitioning methods; hybrid approaches; and model-based methods. Data structure analysis is also explained.

Module 4: Steps 6 and 7
Profiling and describing segments are discussed in this module including Steps 6 and 7. We identify key characteristics of market segments using traditional approaches as well as visualization techniques used in profiling. In Step 7 we describe how to develop and visualize a complete picture of market segments including testing and predicting for segment differences in descriptor variables.

Module 5: Steps 8, 9 and 10
Step 8 describes selecting the target segments including the tasks targeting decision and market segment evaluation. In Step 9 you will learn about customizing the marketing mix and the implications of market segmentation for marketing mix decisions concerning product, price, place, and promotion. Finally, in Step 10, we will show you how to evaluate the success of the segmentation strategy and stability of segment membership, and introduce concepts such as segment hopping and segment evolution.

Taught by

Sara Dolnicar, Bettina Grün and Friedrich Leisch

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