Customer segmentation
Different types of customers respond to different marketing/sales approaches and even product features. Being able to assign customers to segments allows strategies to be developed to target these customers in ways that will be meaningful to them and result in positive ROI without the need for custom strategies for each customer.
Overview
Identifying customer segments and assign customers to those segments can drive ROI for the business.
TARGET
What segment does the customer belong to?
Challenge
In order to adequately segment customers, it is necessary to develop a 360 degree view of the customer. This involves the massive task of aggregating and merging all information about the customer from across the company. This data may be owned by multiple different departments in the company with different identifiers. All this data needs to be cleaned, joined and transformed into valuable ML features before going into model training. This pre-modeling prep process can be frustrating and time consuming. We are here to help.
Modeling techniques and libraries
Clustering
When segments have not been identified for most or all of the customers, or when the company is looking to identify new segments within their customer base, clustering is the standard technique. Clustering uses the attributes of the customer to group customers into segments of similar customers that can then be used for marketing purposes or in a supervised learning process to build a way to quickly segment new customers.
Package:
- Sklearn
Machine learning analysis
If the company has already identified segments for some of the customers, these labeled customers can be used to build supervised models to predict the segment as a function of the independent variables. Use model interpretability packages to evaluate the impact of the independent variables on the prediction.
Packages:
- Sklearn
- ELI5
- LIME
- SHAP
