One of the most commonly used forms of Brand mapping is correspondence analysis. Brand maps are often used to illustrate customers’ images of the market by placing products and attributes together on a map together on a graph. This allows close interpretation of company perceptions with a variety of product and service attributes that are closest to them on the map. If products are placed close to each other on the graph, it means they have a similar image or profile in the market. This helps to inform strategy, like where to take the client’s product in the future.
Some questions that can be answered with a correspondence analysis are:
- What attributes does the brand own?
- What attributes do competitors own?
- Are there gaps in the market that may be filled by the client brand?
- How should the brand be positioned to be both relevant to the market and differentiated from the competition?
Correspondence analysis is an exploratory data analytic technique that allows rows and columns of a cross-tabulation (two-way and multi-way) to be displayed as points in two-dimensional space. The information from the cross-tab, as seen in the example below, is usually collected using simple multi-coded grid questions or semantic rating scales (typically 5 or 10 point scales).
It reduces a complicated set of data to a graphical display that is immediately and easily interpretable. The graph contains a point for each row and each column of the cross-tab. Rows with similar patterns of counts produce points that are close together, and columns with similar patterns of counts also produce points close together.
Running a correspondence analysis on the above cross-tab yields the following graphical display:
In this example, McDonald’s is more synonymous with Low Prices. Pizza Hut and El Pollo Loco can be associated with Overall satisfaction, as well as Taste of the Food and Quality of Food for the Money.
Correspondence analysis is a valuable tool that can be applied to many situations.