Introduction
Companies use multivariate statistical techniques to analysis both an independent and dependent variable. There is a wide range of multivariate techniques available today but the intentions of most companies who use these techniques is to collected and simplify information in some way so that clarification can be given between the relationship of two or more variables. The preferred method to use will depend on the kind of information needed, the kind of issue at hand and the goals of the statistical examination (Multivariate Analysis, 2006). With that being said, discussed below will be a factual company and/or companies that have used the multivariate techniques of factor analysis, cluster analysis, and multi-dimensional scaling for statistically analyzing a business issue or problem.
Factor Analysis
Factor analysis is often used by companies who intentions are to study their customer satisfaction. The customer satisfaction studies performed are used to identify underlying service dimensions by companies (B2B International, 2011). For example, as part of the consumer’s opinion on Dominos Pizza the franchise had consumers respond to survey questions regarding the satisfaction of their pizza. The survey included questions like thoughts on the delivery policy of the business, the look of their pizza, and the taste of their pizza. Factor analysis methods were utilized to determine whether these questions do in reality have an effect on the satisfaction of Dominos Pizza consumers (Taleo Corporation, 2007).
Cluster Analysis
Cluster analysis is broadly employed in market investigation to portray and measure consumer segments. By using cluster analysis marketers are more enabled to aim for consumers who are adapted to their wants instead of having one common marketing method (B2B International, 2011). For example, Travel Alberta performed a case study in which cluster analysis was used to sector out local based customers in relation to their decision making actions. This distinguished analysis illustrated that 93% of the respondents were acceptably organized into the correct cluster, and that a statistically noteworthy differentiation existed among the clusters (Hudson & Ritchie, n.d.).
Multi-dimensional Scaling
Multi-dimensional scaling might be regard as a factor analysis substitute. However, with multi-dimensional scaling the intention of the study is to identify important primary measurements which will permit the investigator to clarify practical connections or differences among the objects being investigated. For example, a case study was done on geographic information systems (GIS). A multidimensional theoretical outline was developed for evaluating authority and making use of it in observing the forces of GIS on society established groups who are connected with city preparations and neighborhood recovery (Elwood, 2001).
Conclusion
Multivariate technique enables a company to investigate relationships in their data that needs to be examined in order to come to a conclusion. All of the multivariate techniques spoken about above have particular kinds of issues or problems for which they are best suitable for a company. Also, it must be undoubtedly implicit to the forecaster of the company that each method has its strengths and weaknesses, and these must be plainly acknowledged by the forecaster before trying to understand the outcome of the examination. Doing this will make the outcome of the examination more adequate for the company in knowing which technique will work best for which problem or issue (Richarme, n.d.).
References
B2B International. (2011). Market Research with Intelligence. Retrieved from http://www.b2binternational.com/
Elwood, S. (2001). GIS use in community planning: A multidimensional analysis of empowerment. Retrieved from http://www.envplan.com/abstract.cgi?id=a34117
Hudson & Ritchie. (n.d.). Understanding the domestic market using cluster analysis: A case study of the marketing efforts of Travel Alberta. Retrieved from http://jvm.sagepub.com/content/8/3/263.abstract
Multivariate Analysis. (2006). In Collins Dictionary of Sociology. Retrieved from http://www.credoreference.com/entry/collinssoc/multivariate_analysis
Richarme, M. (n.d.). Eleven multivariate analysis techniques: Key tools in your marketing research survival kit. Retrieved from http://www.decisionanalyst.com/publ_art/multivariate.dai
Taleo Corporation. (2007). Dominos Pizza Case Study. Retrieved from http://www.taleo.com/sites/default/files/casestudy-dominos.pdf