Customer Loyalty Measurement

Customer Loyalty Measurement

Imagine you have been hired to develop a research study for a company evaluating the impact on customer loyalty of a recent change in their customer service protocols.

Discuss the following with your classmates.

• Based on the method you would choose to evaluate this question, what kind of variable would you be working with? Is it nominal, ordinal, interval, or ratio?
• Describe how this variable is nominal, ordinal, interval, or ratio, and how affects how you would evaluate the data you collected.

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APA

Customer Loyalty Measurement

Customer Loyalty Measurement refers to the process of evaluating how likely customers are to continue engaging with a business, often assessed through surveys or behavioral metrics. It helps organizations understand the effectiveness of service strategies and their influence on customer retention and satisfaction.

To evaluate the impact of a recent change in customer service protocols on customer loyalty, I would likely choose a quantitative research method, such as a survey-based approach using a Likert scale (e.g., 1 = very unlikely to 5 = very likely to return or recommend the company). The variable I would be working with is:

Type of Variable: Ordinal

Explanation:

• Customer loyalty measured on a Likert scale is considered ordinal because the responses represent a meaningful order (e.g., from low loyalty to high loyalty), but the intervals between the points are not necessarily equal.

• For example, the difference between “very unlikely” and “unlikely” may not be perceived the same as the difference between “likely” and “very likely.”

How This Affects Evaluation:

• Since ordinal data does not assume equal spacing between categories, I would use non-parametric statistical tests to evaluate the data.

• Appropriate analysis techniques might include median or mode for central tendency, and tests like the Mann-Whitney U test or Kruskal-Wallis test to compare loyalty levels between groups (e.g., before vs. after protocol change).

• I would avoid using means or standard deviations, which are more appropriate for……..