Thanks for dropping in. I am a chemical engineer turned business person with MBA and 26 years work expertise in Sales and Operations. I teach in business schools- entrepreneurship, operations, S4 HANA, and Marketing. My research interest is on Digital Marketing. As such, I am following evolving technology and it’s impact on business. My any clarification, do not hesitate to contact me at
EDUCATION
Ph.D (p)- Dr. K N Modi University, Rajasthan
MBA- SP Jain Institute of Management & Research, Mumbai
BE (Chemical Engineering)- Jadavpur University, Kolkata
RESEARCH, TEACHING, or OTHER INTERESTS
Business, Management and Accounting, Management of Technology and Innovation, Marketing, Information Systems and Management
Predicting OTT Subscription Behavior Using Deep Learning: A Multi-Class Classification Approach with Feature Engineering and Class Imbalance Handling Prasenjit Chakrabarty, Raj Sinha International Conference on Engineering Technology and Management Icetm 2025, 2025 With the introduction of different OTT streaming platforms like Netflix, Amazon Prime Video, and Disney+ Hotstar, subscription user behavior has become important factors in building customer retention, pricing, and content recommendations. These methodologies do not address the non-linear relationships that exist between important variables like pricing, quality of content, discount availability, and payment options. This study forms the basis for developing a deep learning approach to predicting subscription behavior for OTT platforms based on a multi-layer perceptron (MLP) model. Preprocessing of the survey data for feature selection, label encoding, and normalization will include addressing the class imbalance on the dataset using SMOTE for balanced learning. The architecture contains batch normalization and dropout regularization, with training carried out using Adam optimizer for 500 epochs. Model application achieved a very high accuracy of $97 \%$, which is further validated on various classification metrics as well as confusion and accuracy-loss plots. The study pinpoints pricing, promotions, and satisfaction with content as the prominent factors responsible for subscription choices.
A Hybrid Deep Learning and XGBoost Framework for Predicting OTT Subscription Timing Based on User Behavior Analysis Prasenjit Chakrabarty, Raj Sinha 2025 IEEE 4th World Conference on Applied Intelligence and Computing Aic 2025, 2025 The rapid expansion of Over-the-Top (OTT) streaming services has resulted in growing competitive pressures on platforms to better understand their subscribers and retain them. In this study, we outline a hybrid predictive framework; a deep-learning based feature extractor integrated with an XGBoost classifier for predicting the timing of users' last OTT subscription. The data is collected through an online structured survey that contained questions on viewing habits, preferred platforms, and influential factors. To manage class imbalance to improve the models performance, we applied the Synthetic Minority Oversampling Technique (SMOTE) to the training data. We trained a deep neural network with focal loss to produce meaningful intermediate feature representations for training a multi-class XGBoost classifier. The proposed model produced a test accuracy of approximately 93%. In-depth visualizations of the generated model including class distribution, confusion matrix, and recall at the class distribution level allowed us to evaluate and understand the model performance. This combined predictive framework is able to enhance classification accuracy and now characterizes user behavioral trends. The framework is applicable in areas such as individualized marketing, assessing churn, and analyzing subscription cycle; which is of great use for OTT service providers seeking to best utilize user engagement initiatives.
Exploring Machine Learning's Impact on Digital Marketing Mamta Kumari, Raj Sinha, Prasenjit Chakrabarty, Md Gauhar Hasnain, Neshat Qamar, Sandeep Gupta 2024 15th International Conference on Computing Communication and Networking Technologies Icccnt 2024, 2024 This survey paper investigates the profound influence of machine learning (ML) on reshaping digital marketing strategies and practices. As ML technologies evolve rapidly, they are revolutionizing how marketers understand, engage with, and convert consumers. The paper comprehensively analyzes the key ML algorithms and their applications in the digital marketing landscape, including predictive analytics, personalized recommendation systems, sentiment analysis, and customer segmentation. It explores how ML-driven approaches empower marketers with actionable insights, enhance customer experiences, and drive business growth. Additionally, the paper discusses emerging trends, challenges, and future directions in the integration of ML with digital marketing strategies, highlighting the importance of ethical considerations, privacy protection, and ongoing innovation to harness the full potential of ML in shaping the future of marketing.
Retracted: Exploring Machine Learning's Impact on Digital Marketing (2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT) DOI: 10.1109/ICCCNT61001.2024.10724818) Mamta Kumari, Raj Sinha, Prasenjit Chakrabarty, Md Gauhar Hasnain, Neshat Qamar, Sandeep Gupta 2024 15th International Conference on Computing Communication and Networking Technologies Icccnt 2024, 2024 This survey paper investigates the profound influence of machine learning (ML) on reshaping digital marketing strategies and practices. As ML technologies evolve rapidly, they are revolutionizing how marketers understand, engage with, and convert consumers. The paper comprehensively analyzes the key ML algorithms and their applications in the digital marketing landscape, including predictive analytics, personalized recommendation systems, sentiment analysis, and customer segmentation. It explores how ML-driven approaches empower marketers with actionable insights, enhance customer experiences, and drive business growth. Additionally, the paper discusses emerging trends, challenges, and future directions in the integration of ML with digital marketing strategies, highlighting the importance of ethical considerations, privacy protection, and ongoing innovation to harness the full potential of ML in shaping the future of marketing.
Enhancing Digital Currency Pricing with Machine Learning Models Mamta Kumari, Raj Sinha, Prasenjit Chakrabarty, Yamini Bhardwaj, Sannu Priya, Sandeep Gupta 2024 15th International Conference on Computing Communication and Networking Technologies Icccnt 2024, 2024 Machine learning has emerged at the forefront of technological innovation with vast potential to transform and disrupt various industries and landscapes, particularly digital pricing and cryptocurrency. This paper has examined the futuristic impacts of machine learning on these landscapes, focusing on dynamic pricing strategy, personalized pricing, fraud detection, market analysis, algorithmic trading, risk mitigation, and regulation compliance. ML improves the dataset’s efficiency and data processing rate. This advanced technology helps companies develop better pricing plans, detect fraud and theft, predict market trends, automate trading strategies, develop risk management, and assist with other compliance regulations. Ultimately, this work has uncovered the various opportunities and challenges of the implications of ML on digital pricing and cryptocurrency landscapes.
Predicting the Effectiveness of B2B Marketing Strategies Using Deep Learning: A Multi-target Regression and Classification Approach RS Prasenjit Chakrabarty Data Science and Applications (ICDSA 2025); Lecture Notes in Networks and … , 2026 2026
Driving Digital Financial Literacy in India: A Review of the Regulatory Landscape and Educational Marketing Strategies for Mitigating Cybersecurity and Data Protection Risks 1 Arijit Maity, Prasenjit Chakrabarty, Oyyappan Duraipandi, Babasaheb Jadhav ... SGS Initiative, : LGPR 1 (NO .1 (2026)) , 2026 2026
Driving Digital Financial Literacy in India: A Review of the Regulatory Landscape and Educational Marketing Strategies for Mitigating Cybersecurity and Data Protection Risks DA Maity, P Chakrabarty, O Durai Pandi, B Jadhav, A Mitra, P Das Available at SSRN 6008096 , 2025 2025
An Analysis of Rising Security and Privacy with Technological Advancement R Sinha, PC Sandeep Gupta International Conference on Future Power Network and Smart Energy Systems … , 2025 2025 Citations: 2
A Hybrid Deep Learning and XGBoost Framework for Predicting OTT Subscription Timing Based on User Behavior Analysis RS Prasenjit Chakrabarty 2025 IEEE 4th World Conference on Applied Intelligence and Computing (AIC … , 2025 2025
Data-Driven Strategies in Digital Marketing: Evaluating Performance M Kumari, P Chakraborty, R Sinha Proceedings of International Conference on Paradigms of Communication … , 2025 2025
A Hybrid Deep Learning and XGBoost Framework for Predicting OTT Subscription Timing Based on User Behavior Analysis P Chakrabarty, R Sinha 2025 IEEE 4th World Conference on Applied Intelligence and Computing (AIC … , 2025 2025
Predicting the Effectiveness of B2B Marketing Strategies Using Deep Learning: A Multi-target Regression and Classification Approach P Chakrabarty, R Sinha International Conference on Data Science and Applications, 12-23 , 2025 2025
Digital Marketing Evolution and its Societal Impact on India’s Software and Allied Industries RS Prasenjit Chakrabarty Academy of Marketing Studies Journal (Print ISSN: 1095-6298; Online ISSN … , 2025 2025 Citations: 4
Decoding the Marketing Mix: A Systematic Review of Its Influence on Consumer Purchase Decisions P Chakrabarty, D Pandey Journal of Emerging Technologies and Innovative Research 12 (7), f684-f699 , 2025 2025 Citations: 3
Comparative Analysis of Indian Legal Text Documents Using Large Language Models R Sinha, M Kumari, R Rallan, P Chakrabarty, MG Hasnain, N Qamar Fifth Congress on Intelligent Systems (CIS 2024), part of the Lecture Notes … , 2025 2025 Citations: 1
Investigating the Effects of Emerging Technologies on AIDA and Marketing Mix in Indian Digital Marketing RS Prasenjit Chakrabarty Advances in Consumer Research 2 (4(2025)), 1227 , 2025 2025 Citations: 2
Predicting OTT subscription behavior using deep learning: a multi-class classification approach with feature engineering and class imbalance handling P Chakrabarty, R Sinha 2025 International Conference on Engineering, Technology & Management (ICETM … , 2025 2025 Citations: 4
Cross-Disciplinary Collaboration: Bridging Management and Computer Engineering for Innovation SS Prasenjit Chakrabarty, Debashreet Das, Neetu Singhwal, P. Geetha, J ... https://www.jisem-journal.com/ 10 (3), 1764-1775 , 2025 2025
Exploring The Digital Marketing Dynamics Of MSME Technology Services Companies In India RS Prasenjit Chakrabarty https://www.jisem-journal.com/ 10 (15s), 598-612 , 2025 2025
Winning Strategies: HOW TOP BRANDS LEVERAGE AI & ML TO DELIVER EXCEPTIONAL CUSTOMER EXPERIENCES IN DIGITAL MARKETING R Sinha Notion Press , 2025 2025
Data-Driven Strategies in Digital Marketing: Evaluating Performance Metrics in the Indian Market M Kumari, P Chakraborty, R Sinha, MG Hasnain, N Qamar, S Kavita International Conference on Paradigms of Communication, Computing and Data … , 2025 2025
Stimulating Sales Through AIDA: A Review Of Theoretical And Empirical Insights P Chakrabarty, D Pandey International Journal of Creative Research Thoughts (IJCRT) , 2025 2025
AI-Powered Digital Marketing: The Future of Personalized Experiences P Chakrabarty, R Sinha SCITEPRESS – Science and Technology Publications, Lda 3, 206-213 , 2025 2025
Predicting OTT Subscription Behavior Using Deep Learning: A Multi-Class Classification Approach with Feature Engineering and Class Imbalance Handling RS Prasenjit Chakrabarty Proceedings of the International Conference on Engineering, Technology … , 2025 2025
MOST CITED SCHOLAR PUBLICATIONS
Enhancing digital currency pricing with machine learning models M Kumari, R Sinha, P Chakrabarty, Y Bhardwaj, S Priya, S Gupta 2024 15th International Conference on Computing Communication and Networking … , 2024 2024 Citations: 19
Digital Marketing Evolution and its Societal Impact on India’s Software and Allied Industries RS Prasenjit Chakrabarty Academy of Marketing Studies Journal (Print ISSN: 1095-6298; Online ISSN … , 2025 2025 Citations: 4
Predicting OTT subscription behavior using deep learning: a multi-class classification approach with feature engineering and class imbalance handling P Chakrabarty, R Sinha 2025 International Conference on Engineering, Technology & Management (ICETM … , 2025 2025 Citations: 4
Decoding the Marketing Mix: A Systematic Review of Its Influence on Consumer Purchase Decisions P Chakrabarty, D Pandey Journal of Emerging Technologies and Innovative Research 12 (7), f684-f699 , 2025 2025 Citations: 3
An Analysis of Rising Security and Privacy with Technological Advancement R Sinha, PC Sandeep Gupta International Conference on Future Power Network and Smart Energy Systems … , 2025 2025 Citations: 2
Investigating the Effects of Emerging Technologies on AIDA and Marketing Mix in Indian Digital Marketing RS Prasenjit Chakrabarty Advances in Consumer Research 2 (4(2025)), 1227 , 2025 2025 Citations: 2
Exploring The Digital Marketing Dynamics Of MSME Technology Services Companies In India P Chakrabarty, R Sinha 2024 Citations: 2
Comparative Analysis of Indian Legal Text Documents Using Large Language Models R Sinha, M Kumari, R Rallan, P Chakrabarty, MG Hasnain, N Qamar Fifth Congress on Intelligent Systems (CIS 2024), part of the Lecture Notes … , 2025 2025 Citations: 1
Study and Analysis of the Impact of Social Media Advertisement on Digital Marketing for Building New Brands P Chakrabarty, S Tanwar, H Mahawar 2023 Citations: 1
Predicting the Effectiveness of B2B Marketing Strategies Using Deep Learning: A Multi-target Regression and Classification Approach RS Prasenjit Chakrabarty Data Science and Applications (ICDSA 2025); Lecture Notes in Networks and … , 2026 2026
Driving Digital Financial Literacy in India: A Review of the Regulatory Landscape and Educational Marketing Strategies for Mitigating Cybersecurity and Data Protection Risks 1 Arijit Maity, Prasenjit Chakrabarty, Oyyappan Duraipandi, Babasaheb Jadhav ... SGS Initiative, : LGPR 1 (NO .1 (2026)) , 2026 2026
Driving Digital Financial Literacy in India: A Review of the Regulatory Landscape and Educational Marketing Strategies for Mitigating Cybersecurity and Data Protection Risks DA Maity, P Chakrabarty, O Durai Pandi, B Jadhav, A Mitra, P Das Available at SSRN 6008096 , 2025 2025
A Hybrid Deep Learning and XGBoost Framework for Predicting OTT Subscription Timing Based on User Behavior Analysis RS Prasenjit Chakrabarty 2025 IEEE 4th World Conference on Applied Intelligence and Computing (AIC … , 2025 2025
Data-Driven Strategies in Digital Marketing: Evaluating Performance M Kumari, P Chakraborty, R Sinha Proceedings of International Conference on Paradigms of Communication … , 2025 2025
A Hybrid Deep Learning and XGBoost Framework for Predicting OTT Subscription Timing Based on User Behavior Analysis P Chakrabarty, R Sinha 2025 IEEE 4th World Conference on Applied Intelligence and Computing (AIC … , 2025 2025
Predicting the Effectiveness of B2B Marketing Strategies Using Deep Learning: A Multi-target Regression and Classification Approach P Chakrabarty, R Sinha International Conference on Data Science and Applications, 12-23 , 2025 2025
Cross-Disciplinary Collaboration: Bridging Management and Computer Engineering for Innovation SS Prasenjit Chakrabarty, Debashreet Das, Neetu Singhwal, P. Geetha, J ... https://www.jisem-journal.com/ 10 (3), 1764-1775 , 2025 2025
Exploring The Digital Marketing Dynamics Of MSME Technology Services Companies In India RS Prasenjit Chakrabarty https://www.jisem-journal.com/ 10 (15s), 598-612 , 2025 2025
Winning Strategies: HOW TOP BRANDS LEVERAGE AI & ML TO DELIVER EXCEPTIONAL CUSTOMER EXPERIENCES IN DIGITAL MARKETING R Sinha Notion Press , 2025 2025
Data-Driven Strategies in Digital Marketing: Evaluating Performance Metrics in the Indian Market M Kumari, P Chakraborty, R Sinha, MG Hasnain, N Qamar, S Kavita International Conference on Paradigms of Communication, Computing and Data … , 2025 2025
