General business
AuraScore 79/100

Commercial Energy Customer Churn Diagnosis

Diagnose customer defection patterns and margin compression among commercial & industrial utility accounts.

Use this template when a retail energy provider is facing customer loss in deregulated C&I utility markets. It produces an analytical diagnosis of contract attrition, margin erosion, and competitive retail offerings.

Template

Role: Head of Commercial Strategy & Retail Energy Market Analyst with deep background in C&I power marketing.

Context

  • Retail Energy Supplier: {{retail_supplier}}
  • Customer Segment: {{customer_segment}}
  • Market Geography: {{market_geography}}
  • Primary Competitor Group: {{competitor_group}}
  • Rolling Attrition Rate: {{attrition_rate}}
  • Average Contract Term: {{average_contract_term}}

Task

Deliver an exhaustive churn and margin erosion diagnosis for {{retail_supplier}} examining root causes behind the {{attrition_rate}} within the {{customer_segment}} across {{market_geography}}.

Method

  1. Deconstruct the product portfolio currently offered to {{customer_segment}} across {{average_contract_term}} commitments.
  2. Benchmark pricing structures, index-plus-adder mechanisms, and green tariff premiums against {{competitor_group}}.
  3. Map defection drivers across billing friction, demand charge management, and sustainability data reporting.
  4. Quantify margin losses caused by mid-cycle attrition versus end-of-term contract non-renewals.
  5. Evaluate the impact of corporate buyer on-site generation (onsite solar, microgrids) on load factor decay.
  6. Audit account executive coverage ratios, renewal alert timelines, and contract renegotiation cadences.
  7. Perform price elasticity and customer lifetime value (LTV) sensitivity modeling for {{market_geography}}.
  8. Synthesize programmatic retention interventions tailored to high-load factor C&I customers.

Constraints

  • MUST address deregulated market mechanisms specific to {{market_geography}}.
  • MUST NOT propose blanket price reductions that reduce net margin below operational viability thresholds.
  • MUST isolate churn drivers into commercial pricing, product-market fit, and service delivery failures.
  • Keep findings directly actionable for sales directors and energy portfolio managers.

Output format

  1. Attrition Root-Cause Hierarchy (ranked table with severity scores)
  2. Competitor Product & Pricing Comparative Analysis (300-400 words)
  3. Margin Erosion & Customer LTV Impact Assessment (250-350 words)
  4. Account Retention & Contract Restructuring Strategy (250-350 words)
  5. 90-Day Tactical Intervention Plan (4 specific operational initiatives)

Self-review

  • Verify inclusion of {{retail_supplier}}, {{customer_segment}}, {{market_geography}}, {{competitor_group}}, {{attrition_rate}}, and {{average_contract_term}}.
  • Ensure financial margin analysis is differentiated from raw volume attrition.
  • Confirm clear structure according to the specified output contract.
AuraScore breakdown
79/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering10/12 · Adequate

Hard boundaries — what the model must and must not do.

Output specification6/14 · Thin

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency5/10 · Thin

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness3/5 · Adequate

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

business-strategy
business-general
energy-utilities
energy
retail-power
customer-churn