Deep Learning-Based Digital Marketing Decision Support Model

Vaidehi Soni

Deep Learning-Based Digital Marketing Decision Support Model

Author(s)	Ms. Vaidehi Soni
Country	India
Abstract	The rapid expansion of digital commerce platforms and social networking ecosystems has significantly transformed the structure of modern marketing systems. Organizations continuously collect enormous volumes of customer interaction data through online purchases, browsing activities, advertisement responses, mobile applications, and social media communication. Extracting meaningful business intelligence from such heterogeneous and dynamic datasets has become a major challenge for enterprises seeking effective customer engagement and strategic decision-making. Conventional marketing analytics approaches often face limitations in handling large-scale unstructured information and generating adaptive personalized recommendations. This research introduces an intelligent deep learning-oriented decision support architecture designed for digital marketing analytics and customer-centric business optimization. The study presents an integrated analytical environment combining Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Long Short-Term Memory (LSTM) mechanisms for intelligent customer analysis and marketing strategy generation. The architecture is intended to support customer behavior interpretation, engagement prediction, sentiment evaluation, recommendation generation, and adaptive campaign management within digital business ecosystems. The presented analytical structure emphasizes intelligent feature extraction, customer interaction modeling, recommendation optimization, and automated marketing intelligence generation. The study further discusses how AI-assisted marketing systems can theoretically improve customer targeting, engagement quality, and return on investment compared with conventional machine learning approaches. Additionally, the paper explores the future role of Generative Artificial Intelligence in automated marketing communication and personalized promotional content generation. The research contributes toward the development of scalable intelligent marketing analytics systems suitable for future AI-enabled business environments.
Keywords	Deep Learning, Digital Marketing, Artificial Intelligence, Decision Support System, Customer Analytics, ANN, CNN, LSTM, Recommendation System, Sentiment Analysis, Marketing Automation, Generative AI, Personalized Marketing.
Field	Computer Applications
Published In	Volume 8, Issue 3, May-June 2026
Published On	2026-06-06

View / Download PDF File

About IJFMR Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us		+91-9687-828-838	editor@ijfmr.com

International Journal For Multidisciplinary Research

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Deep Learning-Based Digital Marketing Decision Support Model

Share this