Online Shoppers Purchasing Intention

Keywords: Online, Shoppers

Background

This study employs artificial neural networks to predict online shoppers' purchasing intentions. By analyzing various factors, a predictive model is developed and trained using preprocessed data. The model demonstrates promising accuracy in predicting purchasing behavior, providing valuable insights for e-commerce businesses to enhance marketing strategies and improve conversion rates. Neural networks have the potential to overfit the training data, leading to poor generalization of unseen data. Balancing model complexity and avoiding overfitting is crucial to ensure accurate predictions on new instances. Handling large datasets and delivering timely predictions can be computationally demanding. To improve marketing strategies and enhance conversion rates for e-commerce businesses by understanding and predicting online shoppers' purchasing behavior. To develop an accurate predictive model using artificial neural networks that can effectively predict online shoppers' purchasing intention. Typical methods involve preparing the data, creating the model's architecture, training the network with optimization algorithms, optimizing hyperparameters, evaluating performance, and using the trained model for predictions and deployment. As it was a classification problem like the target variable was revenue whether it was false or true. While initializing the results compile method is used where the loss is binary_crossentropy, and the optimizer is RMS prop. After running % Epochs, accuracy is 97% whereas validation accuracy is 88%.

Aim & Objectives

Aim
To predict the Online Shoppers Purchasing Intentions using DL techniques
Objective
Employ an ANN model to predict online shoppers' purchasing intentions, improving targeted marketing and user experience.
Develop an ANN system that analyzes browsing behavior and demographic data to forecast buying decisions.
Evaluate the ANN's effectiveness in predicting purchasing intentions, enhancing e-commerce strategies and conversion rates.

Research Methodology

ANN Technique used

Software & Tools

Jupyter, Google Collab

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