Original paper
Predicting Under- and Overperforming SKUs within the Distribution–Market Share Relationship
Abstract
This research presents a retail analytics application which uses machine learning (ML) to identify and predict under- and overperforming consumer packaged goods (CPGs) using retail scanner data. Essential to measuring market performance at the SKU level is the relationship between distribution and market share (the velocity curve). We validate that ML can reproduce the velocity curve, and ML is further used to predict underperforming, in-line...
Paper Details
Title
Predicting Under- and Overperforming SKUs within the Distribution–Market Share Relationship
Published Date
Dec 1, 2021
Journal
Volume
97
Issue
4
Pages
697 - 714
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Notes
History