IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/3317234.html
   My bibliography  Save this article

Accurate Marketing Algorithm of Network Video Based on User Big Data Analysis

Author

Listed:
  • Yan Su
  • Fuli Zhou

Abstract

Due to the continuous progress of the era of mega data, it is more and more important to carry out accurate marketing of online video. Based on the analysis of users’ big data, this paper proposes and implements an online video precision marketing algorithm, which provides a reference for the precision marketing strategy of video websites. This paper introduces the concept and characteristics of precision marketing and analyzes the application forms of precision marketing of video websites. It also summarizes the operation system, operation mode of precision marketing, and the influence of online video advertising on enterprises and users. In order to realize the accurate marketing of big data, it needs to be carried out from three parts: data collection, data analysis, and marketing plan formulation and implementation. Through continuously collecting customer data, it gradually and clearly acquires the characteristics of customers and constantly dynamically adjusts the marketing strategy to customers, so as to accurately conduct video marketing to customers and greatly improve the marketing efficiency. In order to test the effectiveness of the marketing algorithm in this paper, we conducted an experiment. The research in this paper has important practical value and reference significance for reducing the cost of video advertising of enterprises and improving the communication effect of online video advertising.

Suggested Citation

  • Yan Su & Fuli Zhou, 2022. "Accurate Marketing Algorithm of Network Video Based on User Big Data Analysis," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-10, May.
  • Handle: RePEc:hin:jnlmpe:3317234
    DOI: 10.1155/2022/3317234
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/mpe/2022/3317234.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/mpe/2022/3317234.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2022/3317234?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:jnlmpe:3317234. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.