I was reading this article where he is trying to predict the sales of 811 products having data for 52 weeks for each product. This sounds like a problem where hierarchical modeling could be useful since we have 811 products that should share some similarities and also where we have to account for time for each of them. Also sales from a product could potentially affect sales from another product. This seemed like a really good candidate for bayesian modeling since there’s not that much data per product.