Customer Portfolio Thermometer

Challenge Description

Energy companies store vast amounts of customer data in CRM (Customer Relationship Management) systems, including contracts, interaction history, billing status, complaints, payment behavior, and service notes. However, this data is rarely translated into structured risk and opportunity intelligence. The challenge is to build a Customer Portfolio Thermometer: a smart, non intrusive analytics layer that connects in read-only mode to a CRM system and generates a dynamic portfolio overview.

Business Context / Why This Matters?

The energy sector is entering a phase where customer risk and engagement dynamics are becoming more important than static customer profiles. Traditional CRM systems and billing platforms store vast amounts of administrative, contractual, and interaction data, but they do not translate this information into structured portfolio intelligence. They record what happened, but they do not explain which customers are becoming risky, which segments require attention, or where hidden value can be unlocked. For suppliers, BRPs (Balance Responsible Parties), LPG distributors, and energy service providers, the real challenge is not the lack of data, but the lack of insight. Early signals of churn, payment risk, dissatisfaction, operational stress, or declining engagement are often buried in fragmented CRM records, communication logs, and support notes. Without an intelligent layer above CRM, organizations remain reactive instead of proactive.

Specific Requirements

• Read-only integration with an existing CRM dataset, no data mutation
• Ability to process structured CRM data and optionally unstructured communication such as emails or call notes
• Demonstrable PoC that runs end-to-end and can be shown live on a laptop or tablet

NOTE: For this challenge, teams are allowed to create or enrich data themselves if this strengthens the clarity and impact of the demonstration.

Data Provided

A copy of the DVEP CRM and metering database is available

Solution (Expected Outcome)

The demonstration should show:

• A portfolio heat overview, for example green, yellow, red segments
• Identified risk groups such as churn risk, payment risk, imbalance risk, service dissatisfaction, low predictability
• Clear explanation per risk group why it is flagged
• Suggested actions such as proactive outreach, contract adjustment, advisory offer, monitoring