While many suppliers can ask questions, what is done with the answers makes the real difference in the project. Using advanced data analytics can help uncover insights and add high value to your market research.
A key differentiator for CRA is our capability in advanced analytics and statistical analyses with two top-notch in-house statisticians. To remain on the cutting edge, we are continually investing in new software packages and developing statistical techniques.
What will statistical data analysis tell you?
Conjoint/Choice-Based Conjoint (CBC) Analysis
Analytical product research can determine how well a new product will compete with other products in the market and how it can be more competitive. Choice based conjoint is a sophisticated analysis technique that employs logistic regression in realistic purchase scenarios. Models based on conjoint analyses 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.
Bivariate and Multivariate Statistical Techniques
Bivariate analysis examines the relationship between two variables, whereas multivariate analysis considers many variables simultaneously. Regardless of the type of analysis selected, the basic function of analysis is to find patterns and exceptions in the data. Techniques of this type commonly include regression analysis, conjoint analysis, correlational analysis and other modeling techniques.
This statistical analysis is useful for combining highly correlated variables into a limited number of themes. Market research studies 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. Factor analysis reduces the number of items into a much smaller set of factors, each explaining a unique area of service.
Perceptual mapping is a multivariate mapping technique that simultaneously represents the relationship between two sets of variables such as importance and satisfaction with services. This technique involves plotting two or more variables on the same grid. Perceptual mapping is very appealing in market research due to the ease with which large quantities of data can be summarized into a simple graphical format. There are many reasons to be interested in perceptual maps. Most prominent are the ability to immediately identify related activities, to assess brand perception and competition, and to assess niche versus general appeal in a graphical format anyone can interpret. Many of our clients have found the perceptual maps to be a useful technique for describing their particular constellation of service attributes, especially as they relate to the competitive marketplace.
Cluster Analysis: Know Your Target
Cluster analysis defines how groups, or “clusters,” of similar individuals differ from other groups of individuals. Most typically used as a market segmentation tool, this technique can also group experiences that are similar, providing insight as to how brands cluster and how different brands compete with each other. This procedure was integral in the development of CRA’s LifeClusters®, our proprietary segmentation of Atlantic Canadians.
Derived Importance Analysis
Derived importance analysis determines what aspects of service drive changes in overall satisfaction, without asking what is important! Unlike stated importance, this type of analysis requires a series of specific satisfaction questions, as well as one overall satisfaction question. Through various multivariate analysis techniques, CRA can determine which of the specific questions have the strongest association with overall satisfaction. This type of advanced analytics often provides results that are both different and more sensitive than traditional measures of stated importance.
GIS Mapping allows data of any kind to be plotted on an actual geographic map at any of several different levels of geography. Levels could be fine-grained in scale, depicting streets or municipalities, or much broader pictures, such as the county, provincial, or national level. 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 CRA to present target-marketing opportunities in an uncomplicated graphic.