Precise Marketing Classification of Agricultural Products for E-Commerce Live Broadcast Platform Using Clustering

Author:

Shi Yuxian1,Li Xinhui2,ZhouGong Shuchen1,Li Xiaoqian1,Wang Hongbing13ORCID

Affiliation:

1. School of Management, Jeonju University, Jeonju 55068, Republic of Korea

2. Department of Management, Huaxin College of Hebei Geo University, Hebei, Shijiazhuang 050000, China

3. Shijiazhuang Information Engineering Vocational College, Hebei, Shijiazhuang 050000, China

Abstract

Live delivery of goods is a novel type of marketing model that has injected new vitality into the development of agricultural e-commerce. It is only in the last few years that live streaming has become a popular e-commerce marketing approach. Agriculture e-commerce in China has a new lease on life thanks to the advent of a new marketing model. This article comprehensively surveys the live broadcast delivery models in the e-commerce era. The comprehensive survey includes the significance and current state of the live broadcast delivery models and identifies the factors impeding the integration and development of agricultural products. The review includes the new marketing model of live broadcast delivery and makes pertinent recommendations. The article presents a novel model for precise marketing classification of agricultural products for e-commerce live broadcast platforms using clustering. Moreover, this article uses customer development space to achieve precise marketing for the e-commerce live broadcast platform. The article enhances K-means with local density and information entropy and proposes an improved TFA customer segmentation method. The results demonstrate that the proposed method is capable of efficiently classifying customers, accurately reflecting their value, and optimizing the algorithm’s efficiency by optimizing the clustering technique.

Publisher

Hindawi Limited

Subject

Computer Networks and Communications,Computer Science Applications

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