CJ Logistics Develops E-commerce Order Volume Forecasting System

CJ Logistics employees are holding a business meeting using the e-commerce order volume forecasting system.

[Asia Economy Reporter Dongwoo Lee] CJ Logistics announced on the 17th that it has developed and started operating an "e-commerce order volume prediction system."

The system provides advance predictions of how many products will be ordered the next day for client companies using CJ Logistics' e-fulfillment services. The average prediction accuracy is 88%.

With the ability to predict product order volumes in advance, client companies can establish more precise sales, inventory management, and marketing plans, which is expected to lead to various cost reductions and increased efficiency. Clients can check the order volume prediction information through eFLEXs, CJ Logistics' integrated e-commerce logistics management system.

CJ Logistics can also secure appropriate workforce to ensure stable product shipment and timely delivery. In particular, when product orders surge due to events, the system can identify expected quantities and timing, enabling more flexible responses.

CJ Logistics applied a combination of eight machine learning and deep learning analysis models based on big data from 19 fields, including order-related information, various promotional events, and meteorological data, as well as 31 variables such as consumer sentiment, weather, and product quantity fluctuations. Going forward, they plan to compare predicted order volumes with actual orders and accumulate data to further refine and enhance the AI analysis models.

A CJ Logistics official stated, "We will accelerate the development and adoption of advanced technologies such as AI and big data-based data analysis to support the growth of our client companies and provide better services to consumers."

This content was produced with the assistance of AI translation services.