Leveraging Artificial Intelligence and Machine Learning for Data-Driven Marketing Strategy: A Framework for Marketing Managers |
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| © 2024 by IJCTT Journal | ||
| Volume-72 Issue-8 |
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| Year of Publication : 2024 | ||
| Authors : Vishvesh Soni | ||
| DOI : 10.14445/22312803/IJCTT-V72I8P130 | ||
How to Cite?
Vishvesh Soni, "Leveraging Artificial Intelligence and Machine Learning for Data-Driven Marketing Strategy: A Framework for Marketing Managers ," International Journal of Computer Trends and Technology, vol. 72, no. 8, pp. 208-220, 2024. Crossref, https://doi.org/10.14445/22312803/IJCTT-V72I8P130
Abstract
AI is the ever-evolving landscape of modern business; harnessing the other AIs of Artificial Intelligence and Machine Learning has become imperative for crafting effective data-driven marketing strategies. The AI 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 and data preprocessing, which handles data cleansing, handling missing values, normalization, 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 smarter 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.
Keywords
Artificial intelligence, Particle enriched pelican optimizer, Convolutional neural networks, Bidirectional long short-term memory.
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