Which of the following is a common use case for clustering algorithms?

Customer segmentation is indeed a common use case for clustering algorithms, as these algorithms excel at grouping similar data points based on their features. In the context of customer segmentation, businesses often aim to identify distinct groups within their customer base to tailor marketing efforts, product recommendations, or services more effectively. By clustering customers according to variables such as purchasing behavior, demographics, or preferences, organizations can develop targeted strategies to enhance customer engagement and satisfaction.

While other uses such as time series forecasting, text analysis, or neural network training involve different methodologies or problem domains, clustering specifically focuses on discovering inherent groupings within a dataset without predefined labels. This makes it particularly well-suited for understanding patterns in customer data, ultimately leading to insights that drive strategic business decisions.