Cluster Analysis

Wield Research based Insights on Market Segments to Build & Deliver superior Value
Overview of Data Analytics
Data-Driven Market Segmentation
Hierarchical Clustering and K- Means Clustering
Applying Cluster Analysis to Identify and Segment Markets
Market Segmentation Using Metric & Categorical Data
No previous experience required - I'll teach you everything you need to know

CLUSTER ANALYSIS

WIELD RESEARCH-BASED INSIGHTS ON MARKET SEGMENTS TO BUILD & DELIVER SUPERIOR VALUE

Craft customer profiles to conduct a deep dive into consumption behavior to generate foresight that aid marketing decision making.

In today’s competitive world, it is crucial to understand customer behavior and categorize customers based on their demography and buying behavior. This is a critical aspect of customer segmentation that allows marketers to better tailor their marketing efforts to various audience subsets in terms of promotional, marketing and product development strategies.

For example, in the case of customer data, even though we may have data from millions of customers, these customers may only belong to a few segments: customers are similar within each segment but different across segments. We may often want to analyze each segment separately, as they may behave differently (e.g. different market segments may have different product preferences and behavioral patterns).

In such situations, to identify segments in the data one can use statistical techniques broadly called Clustering techniques.

What will you Learn?

  • Overview of Data Analytics

  • Data-Driven Market Segmentation

  • Hierarchical Clustering and K- Means Clustering

  • Applying Cluster Analysis to Identify and Segment Markets

  • Market Segmentation Using Metric & Categorical Data

Top skills you will learn

  • Clustering with Categorical Data

  • Clustering Methods

  • Data Analytics tools & techniques

Ideal For

Product Managers, Marketing Professionals, Sales Professionals, anyone interested in Data Science

Introduction

1
1.1: Course Introduction
2
1.2: Course Objective

Chapter 2: Overview of Data Analytics Techniques

1
2.1: Overview of Data Analytics Tools
2
2.2: Data Analytics Techniques

Chapter 3: Data-driven Market Segmentation

1
3.1: Introduction to Data-driven Segmentation
2
3.2: Activity: Using Scatter Plot with MobiSmart Data
3
3.3: R 01 - Read Data
4
3.4: R 02 - Scatter Plot

Chapter 4: Cluster Analysis

1
4.1: What is Cluster Analysis?
2
4.2: Dendogram
3
4.3: R 03 - HAC
4
4.4: R 04 - Dendrogram
5
4.5: R 05 - Scree Plot
6
4.6: Similarity Measures

Chapter 5: Clustering Methods

1
5.1: Hierarchical Clustering
2
5.2: Linkage in Hierarchical Clustering
3
5.3: K-Means Clustering
4
5.4: Activity: K-Means solution for MobiSmart
5
5.5: R 06 - K-Means

Chapter 6: Segmenting Markets

1
6.1: Identifying Market Segments
2
6.2: Effective Segmentation
3
6.3: Activity: MobiSmart - Segment Data

Chapter 7: Clustering with Categorical Data

1
7.1: Clustering With Qualitative Data - Analysing Responses
2
7.2: Clustering With Qualitative Data - Measuring association

Chapter 8: Summary

1
8.1: Quiz
2
Summary
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1 hours on-demand video
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Certificate of Completion

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