Deep Learning-Based User Behavior Analysis: A Neural Network Approach for Predicting Purchasing Patterns
Keywords:
User Behavior Analysis, Deep Learning, Artificial Neural Network, Purchas-ing Patterns, Predictive Analytics, E-commerceAbstract
The extent of analysis into user behaviour will concern purchase patterns, increase marketing returns, and foster better interaction with customers. The following research extends a deep learning framework predicated on an artificial neural network (ANN) model for predicting user buying behaviour through demographic and behavioural information. This methodology preprocesses the dataset containing various categorical and numerical features with encoding approaches as well as feature normalisation. The experimental results validate that the suggested model attains an accuracy of 92%, which is the testimony of the strength of the model in detecting patterns of user behaviour. The assessment includes precision, recall, F1 score, and confusion matrix analysis which emphasise the strength of the model in classification. The research indicates that deep learning models may largely contribute to predictive analytics for e-commerce and digital marketing solutions. Future work would include more behavioural signals, explainability methods, and hybrid models to gain accuracy and interpretability.
DOI: https://doi.org/10.24321/3117.4809.202609
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