Which type of neural network architecture is most commonly used in retail analytics for predicting time-based purchasing patterns like seasonal buying trends?

In the rapidly evolving retail landscape, machine learning techniques are transforming how businesses understand customer behavior and optimize sales strategies. Neural networks in particular have become a powerful tool for retailers seeking to extract meaningful patterns from complex customer data. This poll tests your knowledge of how these advanced algorithms are being implemented in modern retail analytics systems.

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Recurrent Neural Networks (RNNs) with LSTM or GRU cells
Convolutional Neural Networks (CNNs) with max pooling layers
Generative Adversarial Networks (GANs) with discriminator functions
Transformer Networks with self-attention mechanisms