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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

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Sector

Energy & EVs

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