At StarMarc, we employ Advanced Analytics techniques to simplify our research. Notable techniques used include:

Conjoint/Choice-Based Conjoint (CBC) Analysis

We use this to determine how well a new product will compete with other products in the market and how it can be more competitive. We employ logistic regression in realistic purchase scenarios and develop models that can be applied to a wide variety of issues including product features, profitability implications, market consequences of product price or design change, price elasticity within a product category and price elasticity for different brands.

Factor Analysis

We use this to combine highly correlated variables into a limited number of themes. In our Market research studies, we often explore satisfaction levels on a large number of service aspects so that specific problems can be identified. The vast number of items being rated can limit the practicality of further techniques such as regression analysis. We use factor analysis to reduce the number of items into a much smaller set of factors, each explaining a unique area of service.

Perceptual Mapping

We use this in our market research due to summarise large quantities of data into a simple graphical format. We use it to identify related activities, to assess brand perception and competition, and to assess niche versus general appeal in a graphical format anyone can interpret.

Cluster Analysis: Know Your Target

We use this as a market segmentation tool. We can also use this technique to group experiences that are similar, providing insight as to how brands cluster and how different brands compete with each other.

Derived Importance Analysis

We often use this technique to provide results that are both different and more sensitive than traditional measures of stated importance.

GIS Technology

We use GIS Mapping to plot data on an actual geographic map. Many layers of information can be added to the map including spending, attitudes, likelihood of purchase, etc. Combining GIS mapping techniques with cluster analysis allows StarMarc to present target-marketing opportunities in an uncomplicated graphical format.

Bivariate and Multivariate Statistical Techniques

We use this to determine the relationship between two variables or many variables simultaneously. Regardless of the type of analysis selected, we use this analysis is to find patterns and exceptions in the data.