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Annotation 7787715628300

#recurrent-neural-networks #rnn
Sarkar and De Bruyn (2021) demonstrate that a special RNN type can help marketing response modelers to benefit from the multitude of inter-temporal customer-firm interactions accompanying observed transaction flows for predicting the most likely next customer action.
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Sarkar and De Bruyn (2021) demonstrate that a special RNN type can help marketing response modelers to benefit from the multitude of inter-temporal customer-firm interactions accompanying observed transaction flows for predicting the most likely next customer action. However, their approach is limited to single point, next-step predictions and to continue with such forecasts into the long-run one must estimate the new model repeatedly with each addi

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