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Research on the big data collection mode of consumers for innovative products and brand value factors

Published: 20 April 2023 Publication History

Abstract

The collection of machine learning and big data can help us understand consumers more clearly. However, in today's increasingly serious product homogeneity, consumers' perception of brands and product demands cannot be really clearly analyzed. Although the brand has become the basis for the image, popularity and reputation of the enterprise. However, it also reflects that the brand value will develop wrong products due to a temporary data misjudgment; therefore, building brand influence has become the goal of reducing the depth of the company's operations, and its evaluation results are expected to help the industry improve itself and provide the main reference for brand strategy.
Through structural reconstruction and value chain inductive analysis, this research will provide the core value of products that should be paid attention to when designing and positioning products in the future and what should be paid attention to when collecting big data, and should be able to fully comply with the positioning strategy of the entire product brand, so as to avoid causing brand damage. value. and consumer perception. Through the construction of these data, market-related researchers can also focus on the balance and value chain between brand value and product positioning through this research, and provide reference and product development positioning for relevant education researchers or market data collectors.

References

[1]
Lin, Meng-Yan (2010). "Marketing Strategy" and "Brand Positioning". MANAGER today, 70(9), 120-127
[2]
Viewider, What is a brand definition? Practical brand positioning strategy 7 steps to find your product market positioning strategy and build a well-known brand (Dec 9, 2018). Retrieved from https://www.viewider.com.tw (Dec.1, 2019)
[3]
Zhang, Xing (2018). Pesticide Marketing Management. China: China Agricultural Press.
[4]
Tai, Yong-Xin (2005). An analysis on factors influencing brand orientation. Journal of Liaoning Technical University Social Science Edition, 11(1), 58-59.
[5]
Xiao-Qing Feng (2010). Research on Tactics for Brand Positioning of Enterprises. Contemporary Economic Management, 32(5), 23-26
[6]
Zhu, Li-Ming, & Xu, Chun-Zhen (2004). Modern marketing principles .China: China Business Press
[7]
Daily headlines, How to position products in brand planning (Aug 6, 2017). Retrieved from https://kknews.cc/zh-tw/tech/zxymleq.html (Dec.10, 2019)

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    AICCC '22: Proceedings of the 2022 5th Artificial Intelligence and Cloud Computing Conference
    December 2022
    302 pages
    ISBN:9781450398749
    DOI:10.1145/3582099
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 20 April 2023

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    Author Tags

    1. Brand value learning model
    2. consumer mental model
    3. strategy
    4. user demand product data

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