The Customer Loyalty Matrix

In the past few months we’ve described some of the key tools for the Define, Measure and Analysis phases of a modified DMAIC that will shift your Six Sigma process improvement initiatives from an internal focus on cost cutting to an external focus on market share and top-line revenue. This month we’d like to extend the tools of the Analysis phase of DMAIC to include a detailed look at Customer Loyalty. We’ll continue with our example drawn from a manufacturer of tractors targeting hobby farmers.

The Customer Loyalty Matrix

Market share is a function of three factors: retaining current customers, increasing the buying rates of your current customers and acquiring new customers. Your initial focus should be on the first two of these because it’s far less expensive to keep current customers than it is to acquire new ones. The principal tool for driving this initiative is the Customer Loyalty Matrix. (Click on diagram to enlarge.)

The Customer Loyalty Matrix is similar to the Competitive Value Matrix with one exception: instead of plotting competitors on the matrix, groups of customers are plotted on the matrix. These customer groups (circles) are plotted on the basis of their ratings on the two key drivers of value, quality and price, using a grouping technique called cluster analysis. In the Customer Loyalty Matrix example shown, 24 percent of this company’s customers report that they are receiving outstanding value; 39 percent report receiving "average" value; 18 percent report that the quality they receive is not very good, but they are relatively satisfied with the price they are paying for that quality; 15 percent and 4 percent, respectively, report that they are the recipients of poor value from their current provider.

In this particular case, only 24 percent of XYZ’s customers are receiving outstanding value. As shown in the accompanying table, these are the organization’s "sticky" customers—the least likely to switch, even for price discounts, the most likely to repurchase, and the group with the highest Net Promoter Score (NPS). (Click on diagram to enlarge.)

The "Average Value" group represents 39 percent of the organization’s customers. These are passive shoppers—they are not necessarily seeking alternatives, but they would certainly consider competitive alternatives when making their next tractor purchase.

The other three groups of customers, representing 37 percent of XYZ’s customer base, will be actively seeking alternative brands when shopping for their next tractor. Net Promoter Scores for each of the groups are negative, meaning that there are significantly more detractors in each group than promoters. These customers are continually telling others about the poor quality they are receiving, even though one group (the Discount Relationship Group) feels that they aren’t paying too much for that poor quality.

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The bottom line is that about 76 percent of this company’s future revenue is at risk, with 37 percent of that revenue almost certain to go to a competitor. With an average tractor price of about $32,000, it’s a simple matter to calculate the cost of poor quality to this organization! The challenge they face, then, is to create more "sticky" customers. How do they move customers from the "Average Value" group into the "Outstanding Value" quadrant? What buttons must be pushed in order to get the "Discount Relationship" group to realize higher levels of quality?

Changing these situations requires understanding what is underlying these specific value positions. And for that, we have to go back to the Critical to Quality factors (CTQs) identified in the Measure phase of our modified DMAIC, and profile each of the value groups based on those CTQ scores. (Click on diagram to enlarge.)

A quick review of the group profiles reveals that the greatest improvements to customer loyalty within both the Average Value Group and the Discount Relationship Group will accrue by improving processes associated with Dealer Service, Trial and Training, Dealer Sales and Machine Deliveries. Notice that all of these are processes that extend into the channel of distribution, and none require changes to the equipment itself. In other words, Six Sigma projects designed to improve customer loyalty will need to cross the artificial boundary between manufacturing and distribution to ensure that value at the point of production translates into value at the point of consumption.

Again, additional insight into the specific focus for Six Sigma projects can be provided by drilling down into the underlying attributes associated with each of the CTQs. By way of example, take a look at the value group profiles on a few of the attributes associated with Dealer Service. (Click on diagram to enlarge.)

From this additional drill-down, it’s apparent that the biggest boosts to customer loyalty will come from improvements in dealer responsiveness, and in completing work when promised. Those are obviously the areas where business process improvements should be focused in order to increase the loyalty of 57 percent of those customers (39 percent plus 18 percent) who are currently at risk.

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One final observation: The overall Net Promoter Score (NPS) for this manufacturer among the Hobby Farmers was approximately 10.5, which means that there are just a few more promoters than detractors for XYZ within this strategically important market segment—clearly not a desirable long-term position! If you were a category manager at this company and were told that you need to improve that Net Promoter Score, how would you go about achieving that? Would you focus on product innovation? process improvements? training? How would you know where to begin without knowing how your targeted segment defines value and quality? Where would you focus your initiatives if you were unable to quantify your competitive performance on the most important CTQs? Are you ready to shift from internal quality conformance benchmarks to customer-focused, value-driven benchmarks to drive your improvement initiatives? Take the Six Sigma Marketing challenge to find out.

This article was originally posted on Six Sigma IQ.