DYNAMIC BEHAVIORAL SEGMENTATION IN THE DIGITAL ECONOMY
DOI:
https://doi.org/10.5281/zenodo.19186970Abstract
Due to the rapid growth of digital economy, the firms have changed the way they understand and segment consumers. The conventional models of segmentation that consider the user behavior as static demographic or geographic variables are gradually becoming inadequate in the digital world where the user behavior keeps on evolving. This paper examines the dynamic behavior segmentation concept, which is based on real-time, digital footprints, and adaptive analytics that classify consumers based on dynamic behaviors. The paper is a review of the literature on digital marketing analytics, behavioral data mining, and customer relationship management to provide theoretical concepts and real-life examples of implementing the concept of dynamic segmentation. The evidence indicates that online platforms allow companies to keep on optimizing customer groups with behavioral cues like browsing behavior, buying behavior, engagement intensity, and engagement history. This dynamic strategy enables businesses to serve them individually, enhance target marketing and enhance marketing effectiveness. The article concludes that dynamic behavioral segmentation is a paradigm change in customer analytics of the digital economy..
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
By submitting a paper to the conference organized by Academic Publishing House, the author(s) agree to the following license terms and conditions:
1. Copyright and Licensing
-
The author(s) retain the copyright of their article.
-
The author(s) grant Academic Publishing House a non-exclusive license to publish, distribute, and archive the submitted material in both electronic and print formats.
-
The work will be published under the Creative Commons Attribution (CC BY 4.0) license, allowing others to share and adapt the material for any purpose, provided proper credit is given to the original author(s).
2. Author’s Responsibilities
-
The author(s) guarantee that the submitted work is original, does not infringe any existing copyrights, and has not been published or submitted elsewhere.
-
The author(s) confirm that all co-authors have approved the final version of the manuscript and agree with its submission and publication.
-
The author(s) are fully responsible for the accuracy of the data, citations, and references provided in the article.
3. Publisher’s Rights
-
Academic Publishing House reserves the right to edit, format, and make minor grammatical or layout corrections to the paper without altering its core content.
-
The publisher has the right to include the article in indexing databases, archives, and repositories such as Google Scholar, Zenodo, OpenAIRE, and other partner platforms.
-
The publisher may promote the paper through its website and official social media channels.
4. Open Access Policy
All conference papers are published as open access, ensuring free and permanent online access to the full text of all articles immediately upon publication.
5. Withdrawal and Retraction
If ethical misconduct, plagiarism, or data manipulation is detected, Academic Publishing House reserves the right to withdraw or retract the publication at any stage.
6. Acceptance of Terms
Submission of a manuscript to the conference implies that the author(s) have read, understood, and accepted these License Terms.
