We did a POC for customer segmentation and followed the below approach
a) extract data from source system (SAP business objects)
b) Use python jupyter notebook to manipulate, merge and group data (multiple csv files)
c) We cluster based on some preset variables. So, we use the below 4 variables a) Recency (R)
b) Frequency (F) c) Cutomer duration with our company (indicates loyalty) (Y) d) No of different market segments entered by the customers (indicates cross-selling) (P)
d) Run 1d kmeans algorithm (Jenks Breaks algo) for each variable. So, 4 algos are run (for 4 variables)
e) For the sake of interpretability and for easy modifications of rules based on business criteria, we also incorporate a rule to finally come up with meaningful customer segments like below
f) based on each business users defined requirement, we send out automated emails on a monthly basis
Now, my questions are as follows
a) How can I make this automated? my data gets updated every 45 days. We are always looking to create clusters of 4/5 for Recency and Frequency variable and 2 and 3 for Prod and years variable. This will not change.
b) But since, we provide results to sales users to follow up with customers, we want to be able to track the results across each run and have a dashboard to know whether a customer who needed attention is now moved to loyalist or champions segment because our sales users continuously followed up with them. We would like to measure that transition between each segments and this is planning to be used as a KPI for sales users. How can we do this?
c) Is 1d-kmeans algorithm considered as an AI algorithm?
d) How can this be made as a pipeline and any suggestions on how to improve this project further is welcome