Contrasting Attitude with Behavior (Basic Brand Vulnerability Matrix)

The final analysis framework focuses on identifying gaps between preference and behavior, and understanding how to exploit them.

The basic brand vulnerability matrix is typically created by contrasting strength of attitude with frequency or usage. It is typically created as a matrix with nine segments, but there is nothing magical about this number (e.g., a 2 by 2 matrix can work as well).

The basic premise of the matrix is that “Loyal customers may be faithful for different reasons, and similarly lack of loyalty can be attributed to a variety of reasons”.[1]  Discrepancies between attitude and behavior can highlight important characteristics of markets.  For example, in markets containing relatively high levels of price sensitivity we often observe that premium brands have more consumers in the segments at the bottom right corner of the matrix than store brands.

The basic brand vulnerability matrix has several desirable properties.  The strategy implications are relatively straightforward.  The brand attitude of some segments needs to be re-enforced or changed, while for other segments the focus should be more on re-enforcing or removing barriers (e.g., lack of awareness and distribution problems). 

Each of the cells in the matrix is then examined to see how it differs from the general population, with a particular focus on:

• Loyalists
• Customers that don’t like the brand
• Non-customers that like the brand

[1] Yoram Wind (1978), “Issues and Advances in Segmentation Research”, Journal of Marketing Research, Vol. 15, No. 3 (Aug), pp. 317-337.

Creating variables measuring behavior and attitude

The first step is to create one variable that measures behavior and a second variable that measures attitude. There are lots of different ways of doing this, from using questions that directly collect this data in a survey, to computing new variables that are constructed from other data. In the examples presented in this chapter, for example, behavior is based on the number of visits to Burger Chef in the past month, and attitude is based on the number of positive attributes that they assigned to Burger Chef.

Case study

The Basic Brand Vulnerability Matrix for the Burger Chef case study is shown on the next page. It contains quite a few interesting insights (this is just a subset: all the insights would have required a much bigger diagram):

• Only 13% of the market is defined as being loyal (the top-right quadrant).
• 10% of the market is buying Burger Chef, despite disliking or being ambivalent towards the brand. These customers are more likely than average to:
  • Be dining at breakfast or late at night
  • Drive-through
  • Be in a group of 2
  • Buy a chicken product
  • Buy a snack box or meal deal
• 13% of the market like Burger chef, but didn’t consume at all in the last month. These customers are more likely to:
  • Be eating dinner
  • Eat at Southern Fried Chicken or Mexican
  • Eating chicken or burritos
  • Buy a family box