AI RESEARCH
CLVAE: A Variational Autoencoder for Long-Term Customer Revenue Forecasting
arXiv CS.LG
•
ArXi:2604.22636v1 Announce Type: cross Predicting customers' long-term revenue from sparse and irregular transaction data is central to marketing resource allocation in non-contractual settings, yet existing approaches face a trade-off. Traditional probabilistic customer base models deliver robust long-horizon forecasts by imposing strong structural assumptions, while flexible machine-learning models often require substantial