Case analysis studies of diffusion models on E-commerce transaction data

[摘要] (cont.) We partnered with a medium-sized online retail e-commerce firm with both online and offline retail channels to provide us with online transaction data. Using a modified Bass Diffusion Model, we were able to fit a sales forecast curve to a sample of products. We then used k-means cluster analysis to partition products into similar groups of sales transaction-behavior, over the period of 1 year. For each group, we tried to identify characteristics which we could use to forecast new product launch behavior. However, lack of accurate, characteristic mapping of products made it difficult to establish confidence in cluster forecasting for some groups with similar curves. With more accurate characteristic mapping of products, we;;re hopeful that cluster analysis can reasonably forecast new product performance in online retail catalogs.

[发布机构] Massachusetts Institute of Technology