Research on the Influencing Factors of Online Mobile Phone Sales using Linear Regression

The main objective of this study was to comprehensively explore the factors affecting online mobile phone sales using linear regression models. In recent years, the mobile phone market has developed rapidly, the competition is increasingly fierce, the popularity has gradually increased, and the mobile phone has become a necessary product. This paper aims to explore the key factors affecting online mobile phone sales, including market background, platform and channel, products, marketing strategy, consumer behavior, price, customer service and case analysis, and empirically analyze the specific impact of each factor on sales results. Then, the Kaggle dataset is used to analyze the impact of mobile phones with different functions on sales, and which types of mobile phones are most favored by customers. Based on this, this paper puts forward a series of targeted optimization strategies to improve the effect of online mobile phone sales. Based on the above analysis, there are many factors affecting online mobile phone sales. If an enterprise wants to stand out in the fiercely competitive market, it must start from the market background and comprehensively consider various factors such as platform and channel, product, marketing strategy and customer service. At the same time, with the continuous development of science and technology, enterprises also need to continue to pay attention to the market dynamics, constantly innovate and improve sales strategies, to adapt to the changing market environment.

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Publication Details

Journal
Highlights in Science Engineering and Technology
Published
2024-08-15
DOI
https://doi.org/10.54097/8v11ea21
Primary Topic
Consumer Retail Behavior Studies
Type
article
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article

Research on the Influencing Factors of Online Mobile Phone Sales using Linear Regression

Enqi Zhou, Yixuan Liu, Chutong Huang
Highlights in Science Engineering and Technology
Consumer Retail Behavior Studies
article

Research on the Influencing Factors of Online Mobile Phone Sales using Linear Regression

Enqi Zhou, Yixuan Liu, Chutong Huang
article en

Abstract

The main objective of this study was to comprehensively explore the factors affecting online mobile phone sales using linear regression models. In recent years, the mobile phone market has developed rapidly, the competition is increasingly fierce, the popularity has gradually increased, and the mobile phone has become a necessary product. This paper aims to explore the key factors affecting online mobile phone sales, including market background, platform and channel, products, marketing strategy, consumer behavior, price, customer service and case analysis, and empirically analyze the specific impact of each factor on sales results. Then, the Kaggle dataset is used to analyze the impact of mobile phones with different functions on sales, and which types of mobile phones are most favored by customers. Based on this, this paper puts forward a series of targeted optimization strategies to improve the effect of online mobile phone sales. Based on the above analysis, there are many factors affecting online mobile phone sales. If an enterprise wants to stand out in the fiercely competitive market, it must start from the market background and comprehensively consider various factors such as platform and channel, product, marketing strategy and customer service. At the same time, with the continuous development of science and technology, enterprises also need to continue to pay attention to the market dynamics, constantly innovate and improve sales strategies, to adapt to the changing market environment.

Highlights in Science Engineering and TechnologyVol. 107
Multichannel (China) (CN), Shanghai Jinyuan Senior High School (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 82%
Consumer Retail Behavior Studies
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Research on the Influencing Factors of Online Mobile Phone Sales using Linear Regression — Enqi Zhou, Yixuan Liu, et al. · Highlights in Science Engineering and Technology (2024) | TGRS Research Map | TGRS