Customer Analysis Part IV: Brand Analytics and Elasticity
This is part four of a multi-part series. Part one, segmentation and clustering, can be found here. Part two, classification, is here. Part 3, purchase analytics, here.
As before, the code below is simply snippets. The full code for this section can be found in the repo: https://github.com/jamesdeluk/data-science/blob/main/Projects/customer-analysis/ca4-brands.ipynb
Intro At last we reach out final part in this series. Here we’re looking at brands, quantities, and elasticities.
Data The first thing is to reimport the data, the same as part three. I also created NumPy array of prices I’ll use later for testing and simulation. We know the prices in our dataset range from 1.10 to 2.80; for nice numbers, I picked 1.00 to 3.00, in 0.01 intervals:
