Precision marketing method and strategy of e-commerce platform based on clustering algorithm

In the ever-changing community e-commerce, it is crucial to comprehend the complex connection between quality of a community e-commerce platform and the behavior of consumers in order to maintain growth and competitiveness. This study empirically examines the influence of community e-commerce platforms’ quality, including system quality, information quality, and service quality, on consumers' intention to repurchase, with a specific focus on daily necessities. Stimulus-Organism-Response (SOR) paradigm is adopted to examine how the perception of hedonic and utilitarian values influence the connection between platform quality and repurchase intentions. The results of an online survey conducted with 181 users of community e-commerce platforms demonstrate significant impact of system quality and service quality on repurchase intention. This study particularly emphasizes the key role of the clustering algorithm in precision marketing. Clustering algorithm helps to organize and collect user behavior models and related information, and segment consumer groups, thus laying a solid foundation for precision marketing. During the process of users segmentation, it explores the similarities and differences of different groups, combines market and product development strategies, and targets the selection and integrattion of user markets. This improves the accuracy of market strategies, ensures the full implementation of consumer-ccentric service concept, fully meets the needs of different consumer groups, tracks the status of target customers in real-time, and carries out marketing work.This enhancement is predominantly mediated by perceived hedonic and utilitarian values, highlighting their crucial importance in the process of consumer decision-making. The study also reveals that the impact of information quality on repurchase intentions is limited, and its indirect effect through perceived utilitarian value is also minimal. This sheds light on the complex relationship between platform quality and consumer perceptions. This study enriches the existing literature by providing a detailed understanding of the factors that influence customer loyalty in the digital market. It also provides strategic advice to community ecommerce platforms that seek to increase consumer engagement and enhance their competitive position by implementing qualitative improvements in systems, services, and information distribution.

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Publication Details

Journal
SHS Web of Conferences
Published
2025-01-01
DOI
https://doi.org/10.1051/shsconf/202521501026
Primary Topic
Consumer Retail Behavior Studies
Type
article
Field-Weighted Citation Impact
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article

Precision marketing method and strategy of e-commerce platform based on clustering algorithm

He Yu, Xiaobing Yang
SHS Web of Conferences
Consumer Retail Behavior Studies
article

Precision marketing method and strategy of e-commerce platform based on clustering algorithm

He Yu, Xiaobing Yang
article en

Abstract

In the ever-changing community e-commerce, it is crucial to comprehend the complex connection between quality of a community e-commerce platform and the behavior of consumers in order to maintain growth and competitiveness. This study empirically examines the influence of community e-commerce platforms’ quality, including system quality, information quality, and service quality, on consumers' intention to repurchase, with a specific focus on daily necessities. Stimulus-Organism-Response (SOR) paradigm is adopted to examine how the perception of hedonic and utilitarian values influence the connection between platform quality and repurchase intentions. The results of an online survey conducted with 181 users of community e-commerce platforms demonstrate significant impact of system quality and service quality on repurchase intention. This study particularly emphasizes the key role of the clustering algorithm in precision marketing. Clustering algorithm helps to organize and collect user behavior models and related information, and segment consumer groups, thus laying a solid foundation for precision marketing. During the process of users segmentation, it explores the similarities and differences of different groups, combines market and product development strategies, and targets the selection and integrattion of user markets. This improves the accuracy of market strategies, ensures the full implementation of consumer-ccentric service concept, fully meets the needs of different consumer groups, tracks the status of target customers in real-time, and carries out marketing work.This enhancement is predominantly mediated by perceived hedonic and utilitarian values, highlighting their crucial importance in the process of consumer decision-making. The study also reveals that the impact of information quality on repurchase intentions is limited, and its indirect effect through perceived utilitarian value is also minimal. This sheds light on the complex relationship between platform quality and consumer perceptions. This study enriches the existing literature by providing a detailed understanding of the factors that influence customer loyalty in the digital market. It also provides strategic advice to community ecommerce platforms that seek to increase consumer engagement and enhance their competitive position by implementing qualitative improvements in systems, services, and information distribution.

SHS Web of ConferencesVol. 215
Anhui Xinhua University (CN)
Openalex Percentile: Top 88%
Consumer Retail Behavior Studies
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