Customer Segmentation and Churn Analysis
Personalising communication and offers by segmenting customer base
Challenge
Client had a one-size fits all approach to communication and offers, with minor differences driven mostly by customer channel
Challenge was to provide the Energy client with understandable and actionable customer segments along with an indication of propensity to churn within each segment
Integrated datasets from online engagement, tenure, contracts, products, consumption, etc. from current and historical customers
Developed propensity to churn model and validate initial results with stakeholders
Developed segmentation model to segment current customer base into actionable segments
Worked with stakeholders to prepare a presentation on each customer segment, size, average metrics and possible recommended actions
Solution
Value
Enabled customer teams to personalise communications and offers by segmenting the customer base on their engagement, usage, tenure, etc.
Identified pockets of high-value, low-engagement customers and low-value, high-engagement customers allowing a review of communication models
Roles
Data Scientist
Tools
Sector
Energy & EVs