PREDICTIVE ANALYTICS FOR MARKETING CAMPAIGN OPTIMIZATION

Authors

  • Dr. Sridevi, Dr. R. Ramki, Dr.Ramandeep Saini, Dr A Sulthan Mohideen , Dr Sundarapandiyan Natarajan , M.Rajalakshmi Author

Abstract

In the increasingly competitive landscape of digital marketing, the application of predictive analytics has emerged as a powerful tool for optimizing marketing campaigns. By leveraging historical data, statistical algorithms, and machine learning techniques, businesses can forecast customer behavior, segment audiences, and personalize marketing efforts with unprecedented precision. This paper explores key predictive analytics applications in marketing, including customer segmentation, churn prediction, customer lifetime value estimation, and campaign response modeling. These techniques enable marketers to tailor campaigns to individual preferences, allocate budgets more efficiently, and enhance overall customer engagement and retention. The integration of predictive analytics into marketing strategies not only maximizes return on investment (ROI) but also facilitates a more data-driven approach to decision-making. As businesses continue to adapt to rapidly changing consumer behaviors, the adoption of predictive analytics will be essential for maintaining a competitive edge and driving sustained growth.

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Published

2024-08-20

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Section

Articles