There are four primary types of retail analytics: descriptive, diagnostic, predictive, and prescriptive. Here is more detail on each of these approaches.
Descriptive Analytics: The foundation for more sophisticated analytics types, including the other types in this list; descriptive analytics addresses fundamental questions of how many, when, where, and what to reflect and explain past performance.
Diagnostic Analytics: Helps ecommerce businesses identify and analyze challenges that can hinder performance; it combines data from multiple sources, such as customer feedback, operational metrics, and financial performance, to offer a more comprehensive understanding of a given problem.
Predictive Analytics: Allows ecommerce businesses to anticipate future events based on multiple factors, such as weather, supply chain disruptions, economic trends, and competitive pressures; it often takes the form of a what-if analysis to forecast future results such as customer behavior and which products will become popular.
Prescriptive Analytics: By combining big data and artificial intelligence, prescriptive analytics takes predictive analytics outcomes and recommends specific actions to maximize your ROI; it can anticipate demand changes, supply shocks, and consumer sentiment to help you make necessary adjustments.