When Walmart categorizes customer responses to analyze shopping experiences, what analytical method are they employing?

Walmart's practice of categorizing customer responses to analyze shopping experiences involves identifying themes, patterns, and insights from customer feedback. This analytical approach is known as content analysis.

Content analysis enables organizations to systematically interpret and quantify textual information, such as customer comments and survey responses, by categorizing the feedback into meaningful themes or categories. This method allows Walmart to gain a deeper understanding of customer sentiments, preferences, and areas for improvement in their shopping experiences.

In contrast, qualitative analysis generally focuses on understanding personal experiences and subjective interpretations without necessarily categorizing or quantifying responses in a structured manner. Descriptive statistics provide a way to summarize and describe the basic features of data, often in numerical form, but do not delve into interpreting customer sentiments. Inferential statistics involve making predictions or generalizing conclusions about a larger population based on a sample but do not focus on the categorization of qualitative responses like customer feedback directly.

Therefore, content analysis is the most appropriate choice, as it directly relates to the systematic categorization and interpretation of customer responses to derive meaningful insights about shopping experiences.