Deciphering Business Transactions from Point Process and Time Series Perspectives

Abstract

This article explores the application of point process and time series models in analyzing business transactions. Point processes excel in modeling event timing (such as customer arrivals), while time series models are effective for forecasting aggregated data (such as sales). Using examples from an online retail platform, the article highlights the importance of choosing the right model based on data characteristics and research goals, suggesting a synergistic blend for comprehensive insights into optimizing business transactions.