Forecasting and Analysis of Contribution channel for e-commerce

Abstract

E-commerce business is a new type of business in the modern times which can reach many groups of consumers and generate a lot of revenue for entrepreneurs. However, E- Commerce entrepreneurs have not been successful in evaluating the distribution channels efficiently. This research aims to study the distribution channels in E-Commerce businesses to analyze and forecast the distribution channels of products in E- Commerce business Including creating models and evaluating the effectiveness of the models. This research methodology uses K- Mean clustering algorithm to segment E- Commerce entrepreneurs using Linear Regression Analysis in forecasting of sales channels and using the Cross-Validation in evaluating the effectiveness of the model. The research results show that the segmentation of large E- Commerce entrepreneurs uses product distribution channels as Facebook, Shopee, and Weloveshopping significantly need to sell food and beverages, sports equipment, travel equipment and miscellaneous products. Medium- sized E-Commerce entrepreneurs uses product distribution channels as Weloveshopping, and JD Central significantly need to sell sports equipment, travel equipment, stationery, office equipment and miscellaneous products. Small E- Commerce entrepreneurs uses Facebook, Shopee, JD Central significantly need to sell food and beverages, stationery, office equipment, and cosmetics. The results of the evaluation of the efficiency of the model for forecasting sales channels in E-Commerce businesses has an accuracy of 96.25%.