Cluster analysis – Part 1

Posted by : Vijay Seelam, Roll No:14059, Group C

Cluster analysis is a technique that is used in order to segment a market. The objective is to find out a group of customers in the market place that are homogeneous i.e., they share some characteristics so that they can be classified into one group. The cluster/group so found out should be large enough so that the company can develop it profitably, as the ultimate objective of a company is to serve the customer and earn profits.

Segmentation factors can be demographic (price, gender) and some are psychographic (occasion to use). This presents a problem to the market researcher/company, as to how to identify combination of factors that can be used to segment the market place. It is not always possible to segment a market on the basis of one single factor. Thus, a combination of factors must be used to segment the market place. And this is where Cluster Analysis technique specifically deals with how objects (people, places, products) should be assigned to groups, so that there should be similarity within the groups; and as much difference between the groups, as possible.

Example:

Grouping would help a travel and tourism company in the following ways:

·         The travel and tourism company can study the various clusters of customers that have emerged, and decide which customer group it would like to serve, depending upon the company's own resources and capabilities, the volume of business in each cluster group that will generate sufficient business for the company's own survival.

·         Once a cluster has been selected by the company, it can tailor various tour programmes for its cluster of customers.

·         The company can keep profile of its customers, and identify any new emerging group of cluster.

·         The company can decide to serve either only one group of customers (Niche marketing), or serve all groups of customers, at one and the same time, but having a range of travel and tour programmes.

The choice of variables that are to be used to cluster the objects is one of the most critical decisions analysis make. The best way is to select those variables that make sense conceptually, rather than using any or all variables. Ideally, the variables should be selected within the framework of an explicitly stated theory that is used for supporting the classification.

One extreme approach is to cluster respondents in terms of all available information about the respondent - although this is very thorough, but may lead to difficulty in interpretation and marked difference between groups i.e., the clusters or groups of respondents that are produced may be a jumble, rather than clearly marked description of the target population.

Another extreme approach involves grouping respondents only on data that is directly representing the specific consumer need. Eg - quality, price of a product. This has the advantage of clarity and accuracy, but may be quite limited in describing the target population.

The way one approaches, cluster analysis depends upon the objective of study. Suppose the objective of the company is physical development of an existing product, then the consumers’ needs regarding the product are the most suitable variables for forming cluster.

Suppose an advertisement for a product is to be developed, then the attitude of the consumer towards the product gains more importance, as there are groups of people who have positive, negative or neutral ^.attitude towards product/company. And the advertisement developed' would be targeting specific clusters of consumers, depending upon the product/communication need.

Suppose a company wishes to develop a new product concept/product changes in the existing product offering, then also attitude of consumer- towards product/company/product category gains more importance over other attributes when developing clusters. Therefore, depending upon the objective of study, various characteristics can be used to describe the consumer, his attitudes, needs, demographic characteristics.

A general principle followed: in cluster analysis is to omit behavioural and brand image data. One should concentrate on characteristics describing the consumer and the circumstances e.g., specific needs, demographic variables, general attitude and select any variables which would interact with each other to influence consumer behaviour. Once attributes are identified on the basis of which one is trying to form natural groupings of consumers; one has to scale the attributes, so that one has a basis to measure the similarity/differences between/within groups.

The next Installment contains types of cluster analysis and aspects to keep in mind while using cluster analysis method.