Category Archive for: Cluster Analysis

SAS learning Edition

The instructions given here and in all the data analysis chapters (14 to 22) will work with the SAS Learning Edition as well as with the SAS Enterprise Guide. For a point-and-click approach for performing cluster analysis, use the Analyze task within the SAS Learning Edition. The Multivariate>Cluster Analysis task creates hierarchical clusters from data…

Read More →

Clustering Marketing Professionals Based on Ethical Evaluations

Cluster analysis can be used to explain differences in ethical perceptions by using a large multi-item,multidimensional scale developed to measure how ethical different situations are. One such scale was developed by Reidenbachand Robin.This scale has 29 items that compose five dimensions that measure how a respondent judges a certain action. For illustration, a given respondent…

Read More →

Feelings-Nothing More Than Feelings

As it faced stiff competition in digital cameras, Nikon (www.nikon.com) was marketing its Coolpix line in 2009 with the taglines such as, “passion made powerful,” “brilliance made beautiful,” and “memories made easy.”.The campaign was designed to evoke emotional feelings in consumers. Nikon based this campaign or study conducted to identify feelings that are precipitated by…

Read More →

Segmentation with Surgical Precision

Cluster analysis was used to classify respondents who preferred hospitals for inpatient care to identify hospital preference segments. The clustering was based on the reasons respondents gave for preferring a hospital. The demographic profiles of the grouped respondents were compared to learn whether the segments could be identified efficiently. The k·Means clustering method (SPSS) was…

Read More →

It Is a Small World

Data for a study of U.S., Japanese, and British competitors were obtained from detailed personal interviews with chief executives and top marketing decision makers for defined product groups in90 companies. Tocontrol for market differences, the methodology was based upon matching 30 British companies with their major American and Japanese competitors in the U.K. market. The…

Read More →

Decide on the Number of Clusters

A major issue in cluster analysis is deciding on the number of clusters. Although there are no hard and fast rules, some guidelines are available. Theoretical, conceptual, considerations may suggest a certain number of clusters. For example, if the practical of clustering is to identify market segments, management may want a particular number of clusters.…

Read More →

Select a Clustering Procedure

Figure 20.4 is a classification of clustering procedures. Clustering procedures can be hierarchical, nonhierarchical, or other procedures. Hierarchical clustering is characterized by the development of a hierarchy or tree-like structure. Hierarchical methods can be agglomerative or divisive. Agglomerative clustering starts with each object in a separate cluster. Clusters are formed by grouping objects into bigger…

Read More →

Statistics Associated with Cluster Analysis

Before discussing the statistics associated with cluster analysis, it should be mentioned that most clustering methods are relatively simple procedures that are not supported by an extensive body of statistical reasoning. Rather, most clustering methods are heuristics, which are based on algorithms. Thus, cluster analysis contrasts sharply with analysis of variance, regression, discriminant analysis, and…

Read More →

The Vacationing Demanders, Educationalists, and Escapists

In a study examining decision-making patterns among international vacationers,260 respondents provided information on six psychographic orientations; psychological, educational, social, relaxational, physiological, and aesthetic. Cluster analysis was used to group respondents into psychographic segments.The results suggested that there were three meaningful segments based upon these lifestyles. The first segment (53percent) consisted of individuals who were high on nearly…

Read More →

Ice Cream Shops for “Hot” Regions

Haagen-Dazs Shoppe Co. with more than 850 retail ice cream shops in over 50 countries in 2009, was interested in expanding its customer base. The objective was to identify potential consumer segments that could generate additional sales. Geodemography, a method of clustering consumers based on geographic, demographic, and lifestyle characteristics, was employed for this purpose.…

Read More →

Back to Top