Renewable Tariff Explainer Clarity and Friction Teardown
Evaluate retail energy and clean tariff blog explainers for comprehension barriers, consumer skepticism, and CTA clarity.
Use this template to dissect complex retail energy tariff explainers, time-of-use blog guides, or community solar posts before publication. It isolates cognitive overload, consumer mistrust triggers, and conversion friction.
Role: Senior Utility Customer Experience Analyst and Technical Copy Strategist.
Context
- Rate structure: {{tariff_structure_type}}
- Target customer segment: {{customer_segment}}
- Governing jurisdiction policy: {{jurisdiction_policy}}
- Draft blog copy: {{sample_draft_copy}}
- Primary customer hesitation: {{key_consumer_objection}}
- Desired next step: {{utility_call_to_action}}
Task
Deliver an in-depth friction teardown of {{sample_draft_copy}} explaining {{tariff_structure_type}}, identifying cognitive roadblocks, policy ambiguities, and conversion drop-off risks for {{customer_segment}}.
Method
- Deconstruct {{sample_draft_copy}} to isolate technical billing terms (e.g., demand charges, peak multipliers) that cause reader confusion.
- Evaluate how accurately the post translates {{jurisdiction_policy}} rules into everyday household or commercial energy economics.
- Identify every instance where utility jargon obscures actual cost savings or risks, triggering {{key_consumer_objection}}.
- Map the narrative flow against the reader's decision journey, noting where cognitive fatigue is likely to cause bounce.
- Assess whether the calculation examples or baseline assumptions are realistic for {{customer_segment}}.
- Audit the presentation of {{utility_call_to_action}} for clarity, trust factors, and positioning relative to the reader's value proposition.
- Formulate specific structural rewrites, illustrative sidebars, and micro-copy fixes to maximize comprehension.
Constraints
- Analysis MUST highlight every term requiring greater explanatory scaffolding for non-technical readers.
- Critique MUST NOT recommend simplifying text at the expense of regulatory accuracy under {{jurisdiction_policy}}.
- Feedback MUST explicitly address mitigating {{key_consumer_objection}}.
- Recommendations MUST provide concrete before-and-after copy snippets for identified friction points.
Output format
Provide the analytical evaluation in markdown formatted as follows:
- Friction Diagnosis Summary (concise overview of primary drop-off risks, under 150 words)
- Comprehension and Trust Matrix (categorizing issues into: Regulatory Accuracy, Cost Transparency, and Cognitive Load)
- Deep-Dive Sectional Teardown (annotating specific paragraphs from {{sample_draft_copy}} with Before/After rewrite guidance)
- CTA and Conversion Optimization Plan (actionable steps to guide {{customer_segment}} seamlessly to {{utility_call_to_action}})
Self-review
- Ensure recommended revisions preserve legal compliance with {{jurisdiction_policy}}.
- Confirm the teardown addresses the precise root causes of {{key_consumer_objection}}.
- Check that before/after examples match the reading level of {{customer_segment}}.
Explicit role, a named task, and discrete steps the model can follow.
Background, inputs and variables the model needs before it starts.
Hard boundaries — what the model must and must not do.
A named, field-level shape for the response.
Ordered work items that force analysis before an answer.
Length and structure that travel across frontier models.
Signal density — instruction weight without padding.
Documented variables so the scaffold adapts to new inputs.
Quality bar, assumptions and behaviour when inputs are thin.
How much real usage the template has behind it.