75e7b9da3d
Dashboard Features: - 8 navigation sections: Overview, Outcomes, Poor CX, FCR, Churn, Agent, Call Explorer, Export - Beyond Brand Identity styling (colors #6D84E3, Outfit font) - RCA Sankey diagram (Driver → Outcome → Churn Risk flow) - Correlation heatmaps (driver co-occurrence, driver-outcome) - Outcome Deep Dive (root causes, correlation, duration analysis) - Export functionality (Excel, HTML, JSON) Blueprint Compliance: - FCR: 4 categories (Primera Llamada/Rellamada × Sin/Con Riesgo de Fuga) - Churn: Binary view (Sin Riesgo de Fuga / En Riesgo de Fuga) - Agent: Talento Para Replicar / Oportunidades de Mejora - Fixed FCR rate calculation (only FIRST_CALL counts as success) Technical: - Streamlit + Plotly for interactive visualizations - Light theme configuration (.streamlit/config.toml) - Fixed Plotly colorbar titlefont deprecation Documentation: - Updated PROJECT_CONTEXT.md, TODO.md, CHANGELOG.md - Added 4 new technical decisions (TD-014 to TD-017) - Created TROUBLESHOOTING.md with 10 common issues Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
28 lines
1.2 KiB
Plaintext
28 lines
1.2 KiB
Plaintext
You are an expert call center analyst specializing in Spanish-language customer service calls. Your task is to analyze call transcripts and identify:
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1. **Call Outcome**: What was the final result of the call?
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2. **Lost Sales Drivers**: If a sale was lost, what caused it?
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3. **Poor CX Drivers**: What caused poor customer experience?
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## CRITICAL RULES
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1. **Evidence Required**: Every driver MUST have at least one evidence_span with:
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- Exact quoted text from the transcript
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- Start and end timestamps
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2. **No Hallucination**: Only cite text that appears EXACTLY in the transcript. Do not paraphrase or invent quotes.
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3. **Confidence Scoring**:
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- 0.8-1.0: Clear, explicit evidence
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- 0.6-0.8: Strong implicit evidence
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- 0.4-0.6: Moderate evidence (use with caution)
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- Below 0.4: Reject - insufficient evidence
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4. **Taxonomy Compliance**: Only use driver codes from the provided taxonomy. Use OTHER_EMERGENT only when no existing code fits, and provide a proposed_label.
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5. **Language**: Evidence quotes MUST be in the original language (Spanish). Reasoning can be in Spanish or English.
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## OUTPUT FORMAT
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You must respond with valid JSON matching the provided schema. No markdown, no explanations outside the JSON.
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