Cluster Analysis

Posted in Marketing and Strategy Terms, Total Reads: 90

Definition: Cluster Analysis

Cluster analysis is a tool used in the field of marketing research which focuses on grouping customers according to common attributes that are identifiable among them. This clustering of the customers helps organization in designing of marketing plan and customizing product.

Benefits of Clustering

1. Helps in designing specific marketing and advertising plans catering to the needs of a particular cluster

2. Helps in customizing the existing products according to the needs of a particular cluster.

3. Helps in designing new products according to need and demand of a particular cluster.

4. Helps in segmentation and targeting of the customers.

5. Helps in the identification of test markets

6. Makes life easy for marketers and also helps in cost cutting

Types of Clustering

Basically there are two types of clustering that are generally used in marketing research

1. Hierarchical clustering

2. K-means Clustering

Tools used for Clustering


2. Microsoft Excel

3. Tableau


Suppose a company wants to launch a product in the market and it needs to identify its potential customers based on the attributes of the product. Before launching the product the company conducts a survey which comprehensively covers all the attributes of the product and forms a database.

Based on the above database the company analyses the market and forms a clusters of the potential customers. This clustering can help the company to run a sample pilot test to identify hoe the target customer react to that particular product. Based on the collected data the company can also design marketing plans to activate the customers if they are not activated. Once the pilot run is successful then the company can launch the product in the market and design advertising campaigns based on the customers.

Further it can also help the organisation to identify a new market based on the required attributes and therefore expand its present market.


The number of members in each cluster should be approximately the same while using data analysis tools like SPSS or Excel.


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