At Silicon Valley Research Group, we employ custom leading edge technology and proprietary analysis techniques to provide the critical insights and strategic recommendations that give our clients a genuine competitive advantage for success in today’s challenging environment. These are just some of the marketing research statistical processes we employ:
A method of analysis for determining the level of statistical significance of differences among the means of two or more variables. It is similar in application to techniques such as t-test and z-test, in that it is used to compare means and the relative variance between them. However, analysis of variance (ANOVA) is best applied where more than 2 populations or samples are meant to be compared.
A statistical technique that helps in determining which category individuals of a population belong to. Multiple characteristics are used to determine the groups, and differences within a category need to be less than differences between categories. Cluster analysis is a good demographic tool for consumer segmentation in marketing research.
Correlation analysis is a method of statistical evaluation used to study the strength of a relationship between two, numerically measured, continuous variables (e.g. height and weight). This particular type of analysis is useful when a researcher wants to establish if there are possible connections between variables. It is often misunderstood that correlation analysis determines cause and effect; however, this is not the case because other variables that are not present in the research may have impacted on the results.
A multivariate technique for analyzing the predictive value of a set of independent variables. Discriminant analysis is a classification problem, where two or more groups or clusters or populations are known a priori and one or more new observations are classified into one of the known populations based on the measured characteristics.
Procedure for data simplification through reducing the many rating scales (or set of variables) used by the researcher to a smaller set of factors or composite variables by identifying dimensions underlying the data.
Any statistical procedure that simultaneously analyzes several measurements (variables). Multivariate analysis is conceptualized by tradition as the statistical study of experiments in which multiple measurements are made on each experimental unit and for which the relationship among multivariate measurements and their structure are important to the experiment's understanding.
Mathematical Analysis of Perception and Preference. A multivariate technique designed to represent consumers' product perceptions and preferences as visual representations or points on a map or graph. Also called multidimensional scaling or MAPPing.
A multivariate statistical technique applied to data to determine, for predictive purposes, the degree of correlation of a dependent variable with one or more independent variables. In other words, a technique to see if there is a strong or weak cause and effect relationship between two or more things.
Involves putting a prototype or application in the hands of potential users in order to observe and gain feedback on how the design can be improved. Usability testing is a way to see how easy to use something is by testing it with real users. Users are asked to complete tasks, typically while they are being observed by a researcher, to see where they encounter problems and experience confusion. If more people encounter similar problems, recommendations will be made to overcome these usability issues.