Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
This research synthesizes a decade of evolution in marketing science, detailing the shift from static econometric analysis to high-velocity predictive modeling between 2015 and 2025. As consumer interactions moved toward digital-first ecosystems, the implementation of stochastic processes, game theory, and deep learning emerged as the primary drivers of corporate strategy. This review evaluates the efficacy of these mathematical frameworks in mapping non-linear behavioral trajectories, optimizing real-time engagement, and balancing the demand for personalization with stringent data privacy mandates. By auditing the transition from aggregate market observations to individual-level behavioral simulations, the study offers a strategic roadmap for researchers navigating an increasingly algorithmic global marketplace.
Keywords:
Predictive Analytics, Customer Lifetime Value (CLV), Stochastic Modeling, Algorithmic Marketing
Cite Article:
"MATHEMATICAL MODELING IN MARKETING AND CONSUMER BEHAVIOR: A COMPREHENSIVE REVIEW OF TRENDS (2015–2025)", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 2, page no.b151-b154, March-2026, Available :http://www.ijrti.org/papers/IJRTI2602118.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator