Customer Loyalty and Goal Setting

All companies who use customer loyalty surveys strive to see increases in their customer loyalty scores. Improving customer loyalty has been shown to have a positive impact on business results and long-term business success. Toward that end, executives implement various company-wide improvements in hopes that improvements in customer loyalty scores will follow.

One common method for improving performance is goal setting. There is a plethora of research on the effectiveness of goal setting in improving performance. In the area of customer satisfaction, what typically occurs is that management sees that their customer loyalty score is 7.0 (on a 0-10 scale) at the start of the year. They then set a customer loyalty goal of 8.0 for the end of the fiscal year. What happens at the end of the year? The score remains about 7.0. While their intentions are good, management does not see the increases in loyalty scores that they set out to attain. What went wrong? How can this company effectively use goal setting to improve their customer loyalty scores?

Here are a few characteristics of goals that improve the probability that goals will improve performance:

Specific. Goals need to be specific and clearly define what behaviors/actions are going to be taken to achieve the goal and in what time-frame or frequency these behaviors/actions should take place. For example, a goal stating, “Decrease the number of contacts with the company a customer needs to resolve an issue” does little to help employees focus their efforts because there is no mention of a rate/frequency associated with the decrease. A better goal would be, “Resolve customer issues in three or fewer contacts.”

Measurable. A measurement system needs to be in place to track/monitor progress toward the goal. The measurement system is used to determine whether the goal has been achieved and provides a feedback loop to the employees who are achieving the goal.

A common problem with using customer loyalty scores as the metric to track or monitor improvements is that satisfaction goals are still vague with respect to what the employees can actually do to impact satisfaction/loyalty scores. Telling the technical support department that the company’s customer loyalty goal is 8.0 provides no input on how that employee can affect that score. A better measure for the technical support department would be “satisfaction with technical support” or other technical support questions on the survey (e.g., “technical support responsiveness,” technical support availability”). We know that satisfaction with technical support is positively related to customer loyalty. Using these survey questions for goal setting has a greater impact on changing their behaviors compared to using vague loyalty questions. Because satisfaction with technical support is related to customer loyalty, improvements in technical support satisfaction should lead to improvements in loyalty scores.

An even better measure would be to use operational metrics for goal setting. The company must first identify the key operational metrics that are statistically related to customer satisfaction/loyalty. This process involves in-depth research via linkage analysis (e.g., linking satisfaction scores with operational measures such as hold time, turnaround time, and number of transfers) but the payoffs are great; once identified, the customer-centric operational metrics can be used for purposes of goal setting.

Difficult but attainable. Research has shown that difficult goals lead to better performance compared to goals that are easy. Difficult goals focus attention to the problem at hand. Avoid setting goals, however, that are too difficult and, consequently, not achievable. One way to set difficult and attainable goals is to use historical performance data to determine the likelihood of achieving different performance levels.

Relevant. Goals for the employees should be appropriate for the employees’ role; can the employee impact the goal? Additionally, the goal should be relevant to both the employee and the organization. Holding employees to be responsible for goals that are outside of their control (e.g., technical support representatives being responsible for product quality) is unfair and can lead to low morale.

Accepted (or mutually set). For goal setting to increase performance, employees should be allowed to participate in setting their goals. Goals that are not accepted by the recipient are not likely to be internalized and motivating. A good approach would be to get employees involved early in the process of goal setting. Let them help in identifying the problem, selecting (or understanding) the key measures to track, and setting the goal.

Customer Loyalty 2.0, Part 6 - Advocacy and Purchasing Loyalty: Company Comparisons and Predicting Business Growth

The measurement of customer loyalty has been a hot topic lately. With the latest critiques of the Net Promoter Score coming in from the both practitioners and academic researchers, there is much debate on how companies should measure customer loyalty. I wanted to formally write my thoughts on this topic to get feedback from this community of users. Much of what I will present here will be included in the third edition of my book, Measuring Customer Satisfaction. I welcome your thoughts and critiques. Due to the length of the present discussion, I have broken down the entire discussion into several parts. I will post each of them weekly. Below is Part 5 of the discussion. If you missed them, read Part 1, Part 2, Part 3, Part 4 and Part 5.


The earlier analyses provided evidence of the reliability and validity of the the new loyalty measures, Advocacy Loyalty Index (PLI) and the Purchasing Loyalty Index (PLI). These measures had excellent measurement properties with respect to reliability (e.g., measurement precision and validity (e.g., appeared to be measuring distinct and meaningful constructs). The following analyses will extend the present findings to examine the use of the ALI and PLI across different companies. These analyses will help us determine if the new loyalty measures, ALI and PLI, have adequate measurement precision to be able to:

• detect loyalty differences across companies


• identify reasons for loyalty/disloyalty

Additionally, I will examine the degree to which the loyalty indices are predictive of future business growth. I will explore this possibility by correlating the subjective loyalty indices with objective loyalty metrics. This sort of analysis will help us identify the extent to which these loyalty indices are predictive of future business growth due to both new and existing customers.

Detect Loyalty Differences on Advocacy Loyalty and Purchasing Loyalty

For the two studies cited earlier, we are able to rank each of the companies surveyed within their industries on both advocacy loyalty and purchasing loyalty. To do so, we simply calculate the Advocacy Loyalty Index and Purchasing Loyalty Index by averaging the ALI and PLI over each of the company's respective respondents. Figure 9 contains the averages of the ALI and PLI for each of the PC Manufacturers and Figure 10 contains the averages of the ALI, PLI and RLI (Retention Loyalty Index) for each of the Wireless Service Providers.

Figure 9. Bar Graph of Loyalty Scores for PC Manufacturers

Figure 10. Bar Graph of Loyalty Scores for Wireless Service Providers

The results showed that the loyalty indices are able to detect meaningful difference across the companies. There were statistically significant differences across the companies within each of the industries. Specifically, the PC Manufacturer that ranks at the top for advocacy loyalty and purchasing loyalty is Apple. Among the remaining manufacturers, Hewlett-Packard, Compaq, and Dell have higher levels of advocacy loyalty among their customers compared to the rest. After considering Apple’s dominance in purchasing loyalty, the difference among the remaining PC providers is relatively small. Hewlett-Packard, however, has significantly higher levels of purchasing loyalty compared to Dell. Additionally, Gateway reported the lowest levels of purchasing loyalty.

The wireless providers that rank at the top for advocacy loyalty are Alltel and Verizon. The difference in the ALI among the top four providers, however, is not statistically significant. Advocacy loyalty for all four of these providers, however, is significantly higher than advocacy loyalty of Sprint/Nextel. Similar to the findings using advocacy, while Alltel and Verizon have the highest purchasing loyalty score, the top four providers (Alltel, Verizon, T-Mobile, and ATT) do not differ significantly amongst each other. However, Alltel, Verizon and T-Mobile have higher purchasing loyalty than Sprint/Nextel, suggesting that Alltel, Verizon and T-Mobile have customers who are more likely to increase their purchasing behavior compared to the customers of Sprint/Nextel. Results showed that Verizon, Alltel, and ATT have customers who are the least likely to switch to a different provider; about 25% of their customers say are likely to switch providers within the next 12 months). A higher percentage of T-Mobile and Sprint/Nextel customers say that they are likely to defect to their provider’s competition within the year.

The analyses show that the loyalty indices, ALI and PLI, are sensitive enough to detect differences across the different companies; it appears that the measurement precision of each of the loyalty scales allows researchers and practitioners the ability to understand differences across different groups of customers (in this case, the groups are companies).

Hayes Loyalty Grid and Potential Business Growth

The ALI measures the degree to which customers are advocates of the company. The PLI measures the degree to which customers are likely to increase their purchasing behavior. The two loyalty metrics, ALI and PLI, assess the types of potential business growth that companies are likely to experience in the future. The ALI assesses potential new customer growth while the PLI assesses potential purchasing growth. The Hayes Loyalty Grid charts the ALI and PLI which visually displays the different types of relative growth potential for each of the companies. Two examples of the Hayes Loyalty Grid appear in Figures 11 and 12. Figure 11 represents the Hayes Loyalty Grid for the PC industry and Figure 12 represents the Hayes Loyalty Grid for the wireless service provider industry industry.

PC Manufacturers

As is seen in Figure 11, there is considerable variability across PC manufacturers with respect to their growth potential. Clearly, Apple Computers have high levels of both advocacy loyalty and purchasing loyalty. They, compared to other PC manufacturers, should expect to see faster growth with respect to acquiring new customers and increasing the purchase behavior of existing customers.

As you can see in the Hayes Loyalty Grid, HP (HP) and Apple appear in the upper right quadrant, suggesting that both PC manufacturers are poised to experience faster growth with respect to customer acquisition and increased purchases from existing customers. HP (Compaq) and Dell’s growth potential are on par with the industry average. Located in the lower left quadrant, Gateway, Toshiba and emachines, relative to their competitors, will experience slower growth in both customer acquisition and increased purchases from existing customers.

Figure 12. Hayes Loyalty Grid for the PC Industry

Wireless Service Providers

As you can see in the Figure 12, Alltel and Verizon appear in the upper right quadrant, suggesting that they are poised to experience faster growth with respect to customer acquisition and increased purchases from existing customers. Additionally, T-Mobile customers indicate that they are likely to increase their purchase behavior at the rate comparable to the customers of Alltel and Verizon.

ATT's new customer growth potential is on par with their industry average. Located in the lower left quadrant, Sprint/Nextel, relative to their competitors, will experience slower growth in both customer acquisition and increased purchases from existing customers.

Figure 12. Hayes Loyalty Grid for the Wireless Industry

To understand how well the ALI and PLI predicted future growth, objective loyalty metrics for the Wireless Service Providers were collected for Q3 2007 (fiercewireless.com and quarterly reports from provider's respective Web sites). Each of the loyalty indices were correlated with each of the following objective loyalty metrics:

• Average Revenue Per User (ARPU) Growth (Q2-Q3 2007)


• Churn for Q3 2007 (*reverse coded so higher scores reflected better retention)


• % Total of New Customer Growth (Q2-Q3 2007) - estimated from churn rate and net new customers

These data are located in Table 5.

Table 5. Objective Loyalty Metrics for Wireless Service Providers

The correlations for each of the loyalty indices with each of the objective loyalty metrics are located in Figure 13. As we can see, survey data from Q2 2007 was closely linked to objective Q3 2007 business metrics, suggesting that survey data are predictive of future business growth. For example, ALI and PLI were both predictive of Average Revenue Per User (ARPU) growth. That is, companies who had higher ALI and PLI scores also reported greater ARPU growth from Q2 to Q3 2007.  Additionally, The Retention Loyalty Index was highly predictive of actual churn rates for Wireless Service Providers. That is, companies who had higher RLI scores had lower churn rates compared to companies who had lower RLI scores. Finally, all loyalty indices were related to the acquisition of new customers. Companies who had higher scores on they loyalty indices also experienced greater new customer growth than customers who had lower loyalty indices. While the present results are only based on the wireless industry, the findings showing the predictive power of the ALI and PLI are very compelling and deserve future research.

Figure 13. Relationship of Loyalty Indices with Objective Loyalty Metrics

Companies are not static entities; they can change business practices to address customer loyalty issues, which could ultimately impact their growth potential. The above results of the Hayes Loyalty Grid assume a static world. The results do not suggest that companies will not change their business practices to address customer loyalty issues. It is likely that these companies are currently enhancing their business processes to better manage their customers in order to provide a better customer experience and, consequently, enhance customer loyalty. The next section will use the loyalty indices to help us identify which business attributes are responsible for customer loyalty/disloyalty for each company. By identifying the top drivers of customer loyalty, specific companies will understand why their customers are loyal/disloyal and how they might be able to increase the loyalty of their customer base.

Identify Reasons for Loyalty/Disloyalty

We have seen an effective way of identifying the the business attributes that are responsible for customer loyalty/disloyalty. With the use of customer surveys, we are able to ask customers to rate the quality of the customer experience across a variety of business attributes as well as rate the level of their customer loyalty. With these data, we can calculate the correlation between each of the customer experience business attributes with customer loyalty ratings. The correlation coefficient reflects the degree to which the customer experience is responsible for customer loyalty. A high correlation indicates the business attribute is very important in ensuring customer loyalty. A low correlation indicates the business attribute is not important in ensuring customer loyalty. This correlation is referred to as derived importance.

Using the PC Manufacturer study, we can see how the different business attributes are relatively more or less important in driving customer loyalty across different companies and across the two loyalty indices. Two measures of the quality of the customer experience were calculated and used as drivers of loyalty. They were:1) PC Quality (average of three PC-related questions), and 2) Technical Support Quality (average of 5-technical support-related questions).

In general, I found that the importance of these two customer experience measures in predicting customer loyalty varied over different companies as well as the different types of customer loyalty. Specifically, in the PC Manufacturer study (See Figures 14 and 15), I found that, across all PC Manufacturers, Advocacy Loyalty is driven more by PC Quality than Technical Support Quality. Conversely, Purchasing Loyalty is driven equally by PC Quality and Technical Support Quality.

Drivers of customer loyalty varied over PC Manufacturer; PC Quality was a big driver of Advocacy Loyalty for all the PC Manufacturers except for Apple. Technical Support Quality was seen as a moderate driver of Advocacy Loyalty for most of the companies except for Apple and Toshiba.

Figure 14. Drivers of Advocacy Loyalty for PC Manufacturers

Figure 15. Drivers of Purchasing Loyalty for PC Manufacturers

Using the Wireless Service Provider study, we can see how the different business attributes are relatively more or less important in driving customer loyalty across different companies and across the three loyalty measures. Three measures of the quality of the customer experience were calculated and used as drivers of loyalty. They were: 1) Coverage/Reliability, 2) Handset Quality, and 3) Customer Service Representatives (average of four CSR-related questions).

In general, I found that the importance of these three customer experience measures in predicting customer loyalty varied over different companies as well as the different types of customer loyalty. Specifically, I found that, across all Wireless Service Providers, Coverage/Reliability and Customer Service Representatives, compared to Handset Quality, are top drivers of Advocacy and Purchasing Loyalty. Conversely, top drivers of Retention Loyalty vary greatly by the provider.

Figure 16 illustrates the impact of these attributes on Advocacy Loyalty. As we can see, while the three business attributes have a relatively large impact on advocacy loyalty for many of the providers, they have a significantly smaller impact on advocacy loyalty for Verizon Wireless. Additionally, both Coverage/Reliability and Customer Service Representatives have a larger impact on Advocacy Loyalty compared to Handset Quality (with the exception for Verizon Wireless).

Figure 16. Impact of Business Attributes on Advocacy Loyalty for the Wireless
Service Providers

Figure 17 illustrates the impact of the business attributes on Purchasing Loyalty. Overall, the business attributes tend to have a lesser impact on Purchasing Loyalty than on Advocacy Loyalty (exception is Verizon Wireless). For the majority of the providers, both Coverage/Reliability and Customer Service Representatives have a larger impact on Purchasing Loyalty than does Handset Quality. Interestingly, while business attributes had a greater impact on advocacy loyalty for Alltel compared to other companies, they had a relatively lesser impact on purchasing loyalty for Alltel compared to the other companies; in fact, handset quality had no appreciable impact on Alltel customers' purchasing behavior.

Figure 17. Impact of Business Attributes on Purchasing Loyalty for the
Wireless Service Providers

Figure 18 illustrates the impact of business attributes on Retention Loyalty. Overall, the business attributes have the lowest impact on Retention Loyalty. However, for Verizon Wireless, we see that Coverage/Reliability has a greater impact on Retention Loyalty than it does on Advocacy or Purchasing Loyalty.

Figure 18. Impact of Business Attributes on Retention Loyalty for the Wireless Service Providers

Summary

Some general conclusions can be drawn from the analysis above. These are general conclusions but, as we know, there are always exceptions to these general rules.

• Customers report higher levels of advocacy loyalty than purchasing loyalty. That is, people are more likely to be advocates of a company (e.g., recommend a company) than they are to increase their purchasing behavior toward that company.


• Advocacy loyalty, compared to purchasing loyalty, is more closely associated with the customer experience. The derived importance of the business attributes were more highly related to advocacy loyalty than purchasing or retention loyalty.
  
  
  • Other factors beyond the control of the company (e.g., customer needs, expendable income) likely play a role in the degree to which customers increase their purchasing behavior.
  
  
  • Improving the customer experience will likely improve Advocacy Loyalty more than it will improve Purchasing Loyalty
  
  
  
  


• The loyalty indices are predictive of future levels of objective loyalty metrics, suggesting that surveys are an effective way of measuring and managing customer loyalty.

For more information about the Advocacy Loyalty Index and the Purchasing Loyalty Index and more detailed information about the driver analyses in the studies reported here, you can download a free copy of executive reports on the two studies (Wireless Service Providers and PC Manufacturers) at Business Over Broadway.