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Simplifying Loyalty Driver Analysis

Customer Experience Management (CEM) programs use customer feedback data to help understand and improve the quality of the customer relationship. In their attempts to improve systemic problems, companies use these data to identify where customer experience improvement efforts will have the greatest return on investment (ROI). Facing a tidal wave of customer feedback data, how do companies make sense of the data deluge? They rely on Loyalty Driver Analysis, a business intelligence solution that distills the feedback data into meaningful information. This method provides most of the insight you need to direct your customer experience improvement efforts to business areas (e.g., product, service, account management, marketing) that matter most to your customers.

The Survey Data

Let's say our customer experience management program collects customer feedback using a customer relationship survey that measures satisfaction with the customer experience and customer loyalty. Specifically, these measures are:

  1. Satisfaction with the customer experience for each of seven (7) business areas: Measures that assess the quality of the customer experience. I focus on these seven customer experience areas: 1) Ease of Doing Business, 2) Account Management, 3) Overall Product Quality, 4) Customer Service, 5) Technical Support, 6) Communications from the Company and 7) Future Product/Company Direction. Using a 0 (Extremely Dissatisfied) to 10 (Extremely Satisfied) scale, higher ratings indicate a better customer experience (higher satisfaction).
  2. Customer Loyalty: Measures that assess the likelihood of engaging in different types of loyalty behaviors. I use three measures of customer loyalty: 1) Advocacy Loyalty, 2) Purchasing Loyalty and 3) Retention Loyalty. Using a 0 (Not at all likely) to 10 (Extremely likely) scale, higher ratings indicate higher levels of customer loyalty.

Summarizing the Data

You need to understand only two things about each of the seven business areas: 1) How well you are performing in each area and 2) How important each area is in predicting customer loyalty:

  1. Performance:  The level of performance is summarized by a summary statistic. Different approaches provide basically the same results; pick one that senior executives are familiar with and use it. Some use the mean score (sum of all responses divided by the number of respondents). Others use the "top-box" approach which is simply the percent of respondents who gave you a rating of, say, 9 or 10 (on the 0-10 scale).  So, you will calculate seven (7) performance scores, one for each business area. Low scores reflect a poor customer experience while high scores reflect good customer experience.
  2. Impact:  The impact on customer loyalty can be calculated by simply correlating the ratings of the business area with the customer loyalty ratings. This correlation is referred to as the "derived importance" of a particular business area. So, if the survey has measures of seven (7) business areas, we will calculate seven (7) correlations. The correlation between the satisfaction scores of a business area and the loyalty index indicates the degree to which performance on the business area has an impact on customer loyalty behavior. Correlations can be calculated using Excel or any statistical software package. Higher correlations (max is 1.0) indicate a strong relationship between the business area and customer loyalty (e.g., business area is important to customers). Low correlations (near 0.o) indicate a weak relationship between the business area and customer loyalty (e.g., business area is not important to customers).

Figure 1. Loyalty Driver Matrix is a Business Intelligence Solution

Graphing the Results: The Loyalty Driver Matrix

So, we now have the two pieces of information for each business area: 1) Performance and 2) Impact. Using both the performance index and derived importance for a business area, we plot these two pieces of information for each business area.

The abscissa (x-axis) of the Loyalty Driver Matrix is the performance index (e.g., mean score, top box percentage) of the business areas. The ordinate (y-axis) of the Loyalty Driver Matrix is the impact (correlation) of the business area on customer loyalty.

The resulting matrix is referred to as a Loyalty Driver Matrix (see Figure 1). By plotting all seven datapoints, we can visually examine all business areas at one time, relative to each other.

Understanding the Loyalty Driver Matrix: Making Your Business Decisions

The Loyalty Driver Matrix is divided into quadrants using the average score for each of the axes. Each of the business areas will fall into one of the four quadrants. The business decisions you make about improving the customer experience will depend on the quadrant in which each business area falls:

  1. Key Drivers: Business areas that appear in the upper left quadrant are referred to as Key Drivers. Key drivers reflect business areas that have both a high impact on loyalty and have low performance ratings relative to the other business areas. These business areas reflect good areas for potential customer experience improvement efforts because we have ample room for improvement and we know business areas are linked to customer loyalty; when these business areas are improved, you will likely see improvements in customer loyalty (attract new customers, increase purchasing behavior and retain customers).
  2. Hidden Drivers: Business areas that appear in the upper right quadrant are referred to as Hidden Drivers. Hidden drivers reflect business areas that have a high impact on loyalty and have high performance ratings relative to other business areas. These business areas reflect the company’s strengths that keep the customer base loyal. Consider using these business areas in marketing and sales collateral in order to attract new customers, increase purchasing behaviors or retain customers.
  3. Visible Drivers: Business areas that appear in the lower right quadrant are referred to as Visible Drivers. Visible drivers reflect business areas that have a low impact on loyalty and have high performance ratings relative to other business areas. These business areas reflect the company’s strengths. These areas may not impact loyalty but they are areas in which you are performing well. Consider using these business areas in marketing and sales collateral in order to attract new customers.
  4. Weak Drivers: Business areas that appear in the lower left quadrant are referred to as Weak Drivers. Weak drivers reflect business areas that have a low impact on loyalty and have low performance ratings relative to other business areas. These business areas are lowest priorities for investment. They are of low priority because, despite the fact that performance is low in these areas, these areas do not have a substantial impact on whether or not customers will be loyalty toward your product/company.

Example

Figure 2. Loyalty Driver Matrix for Software Company

A software company wanted to understand the health of their customer relationship. Using a customer relationship survey, they collected feedback from nearly 400 of their customers. Applying driver analysis to this set of data resulted in the Loyalty Driver Matrix in Figure 2. The results of this driver analysis shows that Account Management is a key driver of customer loyalty; this business area is the top candidate for potential customer experience improvement efforts; it has a large impact on advocacy loyalty AND there is room for improvement.

While the Loyalty Driver Matrix helps steer you in the right direction with respect to making improvements, you must consider the cost of making improvements. Senior management needs to balance the insights from the feedback results with the cost (labor hours, financial resources) of making improvements happen. Maximizing ROI occurs when you are able to minimize the costs while maximizing customer loyalty. Senior executives of this software company implemented product training for their Account teams. This solution was inexpensive relative to the expected gains they would see in new customer customer growth (driven by advocacy loyalty). Additionally, the company touted the ease of doing business with them as well as the quality of their products, customer service and technical support in their marketing and sales collateral to attract new customers.

Although not presented here, the company also calculated two additional driver matrices based on the results using the other two loyalty indices (purchasing loyalty and retention loyalty). These three Loyalty Driver Matrices provided the foundation for making improvements that would impact different types of customer loyalty.

Summary

Loyalty Driver Analysis is a business intelligence solution that helps companies understand and improve the health of the customer relationship. The Loyalty Driver Matrix is based on two key pieces of information: 1) Performance of the business area and 2) Impact of that business area on customer loyalty. Using these two key pieces of information for each business area, senior executives are able to make better business decisions to improve customer loyalty and accelerate business growth.

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