7/8/2025

 7/8/2025

While analyzing historical sales data today, I discovered an interesting and important pattern: sales often surge before a price increase. This phenomenon is likely due to consumers stocking up in advance upon learning or sensing an impending price increase, leading to a short-term surge in sales.

Based on this insight, I added price-starting price-related features to my XGBoost model, such as flagging a special variable for a few days before the price-starting date or introducing a dummy time window to reflect this tendency for early demand release. By incorporating this feature, the model can better capture the impact of price changes on consumer behavior, thus reflecting the sales increase before the price-starting price in its predictions.

评论

发表评论

此博客中的热门博文

10/6/2025

 10/6/2025 Today, i successfully completed the construction of the SARIMA model and began to apply it to the prediction of actual sales data. After model training, i generated sales forecasts for the next few days and compared them with the actual data to evaluate the accuracy of the model.
阅读全文

22/5/2025

 22/5/2025 Continue to modify the analysis content based on the feedback from Supply Chain Executive, including optimizing the data display format, supplementing missing data fields, and reorganizing the analysis logic. While completing the modifications, also start preparing for the report to be given tomorrow and organize the required forecast model results.
阅读全文