Which type of analytics would be best for understanding patterns in past customer behaviors?

Descriptive analytics is the most suitable choice for understanding patterns in past customer behaviors because it focuses on summarizing historical data to uncover insights and trends. This type of analytics provides context by explaining what has happened, allowing businesses to analyze aspects such as customer buying patterns, frequency of purchases, and demographic insights derived from past transactions. By diving into historical data, organizations can identify key trends, such as peak purchase times or changes in customer preferences over time.

In contrast, predictive analytics is concerned with forecasting future behaviors based on historical data but does not explicitly address the past patterns themselves. Prescriptive analytics goes a step further by suggesting actions to optimize outcomes, which involves more complex decision-making processes. Diagnostic analytics focuses on understanding the causes behind past behaviors rather than merely identifying the patterns, making descriptive analytics the most direct approach to gain insights from historical data.