Analytics is fun. It can be especially fun when you find a method, data, or mathematical structure that reveals a treasure trove of new or improved use cases which you can then start exploring. Recently, the source of our treasure trove has been incrementality.
Incrementality is fascinating. It is the actual amount of revenue generated by introducing a new product to a store’s assortment. It is quite complex and therefore quite a challenge for retail analysts. But what is even more interesting are the many ways incrementality models – when you finally have them – can be utilized to analyze and manage the store assortment.
Incrementality has a significant impact on the results.
This post is an introduction to a 3-part series on incrementality use cases. The first use case for incrementality is to find additions to the assortment which maximize the added revenue. Compared to the usual approach of just adding products’ maximum expected sales, using incrementality adds a twist to the equation which favors the products which do not cannibalize existing products. Retailers are pretty good with the usual approach, and incrementality has a significant impact on the results.