Optimizing E-commerce Dynamic Pricing Using Aggregated Market Data and Cloud-Based Analytics

Dynamic pricing is a key strategy in e-commerce, enabling businesses to adapt to market trends and consumer demand.This paper proposes a framework for optimizing pricing strategies using aggregated market data and cloud-based analytics.By leveraging Google Cloud services like BigQuery and Google Cloud Storage (GCS), the framework processes large-scale pricing datasets to identify trends and predict optimal price points.This study demonstrates an average accuracy of 92.5% for optimal price predictions and an 18% revenue increase during simulated promotional events.Challenges in data quality and model interpretability are addressed, paving the way for scalable cloud-native pricing strategies [1][2][3].