Leveraging Artificial Intelligence and Machine Learning for Data-Driven Marketing Strategy: A Framework for Marketing Managers

Abstract

In the ever-evolving landscape of modern business, harnessing the power of Artificial Intelligence and Machine Learning has become imperative for crafting effective data-driven marketing strategies. In this study marketing strategy with a thorough framework to help them maximize the potential of AI and ML tools to strengthen their data-driven marketing strategies. The framework includes important steps like skillful Data Collection, Data Preprocessing, which handles data cleansing, handling missing values, and normalization, then Feature Extraction, and unique Feature Selection using the Particle Enriched Pelican Optimizer. The integration of hybrid Deep Learning models such as Convolutional Neural Networks (CNN) and Bidirectional Long Short-Term Memory (BiLSTM) follows the use of Dimensionality Reduction as well. The combination of these factors yields much improved prediction accuracy, enabling marketing professionals to make more smart judgments in the fluid environment of modern marketing. The proposed model demonstrates exceptional performance across various metrics, outshining existing methods. With high acc (0.9763), pre (0.9766), and spec (0.9816), it excels in correctly identifying positive cases.