Customer Loyalty 2.0, Part 4: Measurement and Meaning of Customer Loyalty; Advocacy Loyalty and Purchasing Loyalty

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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 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 4. Here is Part 4 of the discussion. If you missed them, read Part 1, Part 2 and Part 3.

 

Validity of Loyalty Indices

As we saw, one form of reliability, internal consistency reliability, can be indexed by Cronbach’s alpha estimate. This estimate tells us the degree to which the items in the scale are correlated with each other. Scales that have items that are highly correlated with each other have higher reliability compared to scales that have items that are not highly related to each other. Validity, on the other hand, involves a process of understanding what the scale is actually measuring. Now that we have scales that are highly reliable, the next step is to gather evidence that helps us identify what the scales are actually measuring. Establishing the validity of scales is a more complex process than establishing the reliability of scales.

Content-related Evidence

Content-related evidence is concerned with the degree to which the items in the scale are representative of a “defined universe” or “domain of content.” The domain of content typically refers to all possible items that could have been used in the scale. The goal of content-related validity is to have a set of items that best represent the defined universe.



Our initial set of loyalty questions appears to be a good representation of our "defined universe" of possible customer loyalty items. We set out to measure customer’s behaviors/attitudes that help companies grow. Company growth occurred in two general ways: 1) through acquiring new customer and 2) increasing purchasing behaviors of existing customers. While our set of loyalty items might not be exhaustive of all possible loyalty items that could have been asked in the survey, they do appear to be a representative sample of all loyalty questions.

Criterion-related Evidence

Criterion-related validity involves demonstrating the statistical relationship between the loyalty indices and other variables. Based on customer loyalty theory and research, we expect that our measures of customer loyalty would be related to certain types of variables (e.g., customer satisfaction). Previous loyalty models support the notion that customers who perceive the customer experience as good (e.g., good product and service quality) would report higher levels of customer loyalty compared to customers who perceive the customer experience as poor.

In this section, I will explore criterion-related evidence of the loyalty indices. First, I will present the descriptive statistics of and correlations among the loyalty indices. Second, I will examine the relationships of the customer loyalty indices with other variables (e.g., customer tenure, number of prior recommendations). In addition to helping us determine the quality of these loyalty indices, examining these relationships provides a practical vehicle by which we can better understand how companies can better manage the customer relationship and improve customer loyalty.
Descriptive Statistics of and Correlations among Loyalty Indices

The descriptive statistics of and correlations among the loyalty indices are presented for both the Wireless Service Provider study and the PC Manufacturer study below.


Table 1. Descriptive Statistics and Correlations for Wireless Service Provider Study

 


Table 2. Descriptive Statistics and Correlations for PC Manufacturer Study

We see that Advocacy Loyalty was substantially higher than Purchasing Loyalty for the Wireless study (7.29 vs. 5.63) and PC study (7.34 vs. 5.79). Customers generally report higher levels of advocacy loyalty compared to purchasing loyalty.
Next, let us examine the relationship among the customer loyalty indices. Although the loyalty indices are distinct constructs (as determined by the factor analysis), they are correlated with each other. Specifically, the correlation between the ALI and PLI is .64 and .67 for the Wireless study and PC study, respectively. This correlation shows us that customers who are advocates are also somewhat more likely to increase their purchase behavior compared to customers who are not advocates. Additionally, for the Wireless study, Retention Loyalty is more strongly related to the ALI (r = .61) than the PLI (r = .31).

In the next set of analyses, I wanted to understand how the ALI and PLI were related to three customer variables: 1) the number of years they have been a customer, 2) the number of people to which customers recommended in the past 12 months, and 3) age of the customer. The results appear below for the wireless service provider study.

Customer Tenure and Customer Loyalty

There is no statistically significant relationship between customer tenure and advocacy loyalty or purchasing loyalty (see Figure 1). Both advocacy and purchasing loyalty remain flat over customer tenure. Retention loyalty, however, is significantly related to customer tenure; Customers who have been with their providers for three or fewer years are less likely to defect compared to customers who have been with their providers for five or more years. Conversely, long-tenured customers are more likely to remain.

The extent to which customers will advocate or increase their purchasing behavior seems to be independent of the length of the customer relationship (a longitudinal study would be a better test of this hypothesis, though). The extent to which customers will switch to another provider, however, is related to the length of the customer relationship. This result might be indicative of the impact of the wireless service contracts on retention loyalty; Short-term customers who were likely to switch providers likely did so after their contract expired (two-year contract lengths are typical). Consequently, the remaining customers (those who become long-term customers), by the very definition of their segment, are made up of customers who are less likely to defect.

Figure 1. Relationship between Customer Tenure and Customer Loyalty



*Retention Loyalty is the reverse coded response to likelihood to switch question; so higher scores mean a lower likelihood of switching wireless service providers.

Number of Recommendations and Customer Loyalty

The next set of analyses looked at the relationship between each of the loyalty indices and the number of people customers recommend in the previous 12 months. In the survey, customers were asked to indicate the number of friends/colleagues they recommended the provider to in the past 12 months. As you can see in Figure 2, the number of previous recommendations is strongly related to both advocacy loyalty and purchasing loyalty and is weakly related to retention loyalty. Customers who did not recommend their wireless service provider to anybody showed lower levels of advocacy and purchasing loyalty compared to customers who did recommend their wireless service provider. Retention loyalty, however, showed less of a relationship to the number of recommendations; while there is a slight increase in customer retention for customers who recommend their provider to 1 to 5 friends, retention drops back down for those customers who recommended their provider to 6 or more friends.

Figure 2. Relationship between Number of Prior Recommendations and Customer Loyalty

*Retention Loyalty is the reverse coded response to likelihood to switch question; so higher scores mean a lower likelihood of switching wireless service providers.

Surprisingly, the extent to which customers recommended their service provider has a substantial impact on their future purchase behaviors. It appears that, to increase purchasing behavior, a company should not only improve the customer service delivery system, but should also find ways to simply encourage customers to recommend them to their friends. Humans tend to behave in ways that are congruent with their beliefs. The mere act of recommending a given service provider may have the ultimate impact on purchasing behavior (“If I am recommending them, I should be purchasing from them.”).

Wireless service providers should continue to find ways to encourage customers to recommend them to their friends. The current findings strongly suggest that customers who recommend their service provider to friends may not only improve financial performance through helping grow the customer base, but also through their own increased purchasing behavior.

Customer Age and Customer Loyalty

There was no significant relationship of age with advocacy loyalty. However, customers’ age was significantly related to purchasing loyalty and retention loyalty. Younger customers have higher levels of purchasing loyalty and retention loyalty compared to older customers. Purchasing loyalty is at its highest for customers between the ages of 26-30 years. The lowest is for customers who are 51+ years. Conversely, retention loyalty is at its highest for customers who are 51+ years and lowest for customers who are 31-40 years (see Figure 3).

The relatively greater likelihood that younger customers will increase their purchase behavior may be driven by characteristics of the younger customers (e.g., keeping up with friends) or marketing that is targeted at younger customers to purchase additional features from their service provider (e.g., text messaging, ring tones, Web access). These same same reasons may encourage customers to switch to providers who offer seemingly more attractive service packages.

Figure 3. Relationship between Age and Customer Loyalty

*Retention Loyalty is the reverse coded response to likelihood to switch question; so higher scores mean a lower likelihood of switching wireless service providers.

Summary

The evidence from two separate studies show that the Advocacy Loyalty Index (ALI) and the Purchasing Loyalty Index (PLI) measure two different types of loyalty. Even though the two types of loyalty are correlated (advocates tend to be purchasers), the relationship between the ALI and PLI is not perfect, suggesting that these loyalty indices measure unique constructs. We have good evidence that the loyalty indices are each measuring some unique aspect of customer loyalty.



Customer loyalty is not a unidimensional construct, but rather a multidimensional construct that can help reliably measured. When we say a customer group has high vs. low loyalty, we need to clarify to which loyalty we are referring. It is possible that a given customer group can have different levels of loyalty (e.g., high advocacy, low purchasing). It is clear that a blanket statement about levels of "customer loyalty" can be ambiguous.

Customers are more willing to sell their friends on the merits of their wireless service provider than they are to spend more of their own money on their wireless service provider. Perhaps purchasing loyalty is lower than advocacy loyalty due to other constraints that might limit the degree to which customers are able to purchase more (e.g., limited need, limited financial resources) yet not impact the degree to which customers could be advocates for a company/product/brand.

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

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