{"aiPlatform":"claude-code@2025.06","category":"data-analysis","commandName":"/talk-ratio-analyzer","content":"---\nallowed-tools: gdrive, zapier, filesystem\ndescription: Talk-to-Listen Ratio Analyzer\n---\n\n# Talk-to-Listen Ratio Analysis\n\n## Context\n- Index file: @Sales/index (ID: 1YVziqmp0l-xk2c1wv-pHgtzJJ6yjoWvVTxIbSonWji4)\n- Shared drive: AP Meeting Notes & Recordings (ID: 0AF_gU5xtoKvkUk9PVA)\n- Sales folder: All Meetings/Sales (ID: 1Ls6qeuWMJdb1HkVJ1cdA_VMr5Nc2e6yN)\n- Transcripts folder: Sales/Transcripts (ID: 1FNRRtCdDSSUGJauF4HzSoPhoR0p7EzmH)\n\n## Your Task\n\n1. **Get user requirements**\n   - Ask: \"Which meeting(s) would you like talk-to-listen analysis for? Provide names or describe your requirements (e.g., 'all discovery calls', 'demo meetings this week', 'compare rep talk ratios')\"\n   - Parse user description to identify relevant meetings\n\n2. **Find matching meetings**\n   - Search index.csv for meetings matching criteria\n   - Display found meetings: \"[Meeting Title] - [Date] - [Sales Rep]\"\n   - Ask: \"Proceed with these meetings? (yes/no/change description)\"\n   - If \"change description\", return to step 1\n\n3. **Retrieve and analyze transcripts**\n   - Access Transcripts folder (ID: 1FNRRtCdDSSUGJauF4HzSoPhoR0p7EzmH)\n   - Read selected transcript files using google-docs-mcp\n   - Parse speaker segments\n\n4. **Calculate Talk-to-Listen Ratios**\n   \n   **Basic Metrics:**\n   - Rep talk percentage vs customer talk percentage\n   - Average segment length for each speaker\n   - Total speaking time distribution\n   - Ratio format (e.g., \"40:60\" rep:customer)\n\n5. **Analyze Question Effectiveness**\n   \n   **Question Classification:**\n   - Open-ended patterns: \"what\", \"how\", \"why\", \"tell me\", \"describe\"\n   - Closed patterns: \"is\", \"are\", \"do\", \"does\", \"can\", \"will\"\n   - Follow-up and probing questions\n   \n   **Effectiveness Metrics:**\n   - Total questions asked\n   - Open vs closed ratio\n   - Average customer response length after questions\n   - Engagement score based on response quality\n\n6. **Segment by Call Type**\n   \n   **Optimal Ratios by Type:**\n   - Discovery: 30% rep, 70% customer (customer should do most talking)\n   - Demo: 50% rep, 50% customer (balanced conversation)\n   - Negotiation: 40% rep, 60% customer (customer concerns drive)\n   - Closing: 35% rep, 65% customer (customer questions/commitment)\n\n7. **Correlate with Deal Outcomes**\n   - Track talk ratios in won vs lost deals\n   - Identify optimal ranges for success\n   - Find question patterns that drive engagement\n\n8. **Generate Comprehensive Report**\n   ```markdown\n   # Talk-to-Listen Ratio Analysis Report\n   Date: [Current Date]\n   Meetings Analyzed: [Count]\n   \n   ## Executive Summary\n   - Average talk-to-listen ratio\n   - Question effectiveness score\n   - Engagement correlation insights\n   \n   ## Overall Metrics\n   | Metric | Value | Optimal Range |\n   |---|---|---|\n   | Rep Talk Time | X% | 30-40% |\n   | Customer Talk Time | X% | 60-70% |\n   | Questions per Meeting | X | 10-15 |\n   \n   ## Call Type Analysis\n   | Call Type | Actual Ratio | Optimal Ratio | Alignment |\n   |---|---|---|---|\n   | Discovery | X:X | 30:70 | Good/Needs Work |\n   | Demo | X:X | 50:50 | Good/Needs Work |\n   \n   ## Question Effectiveness\n   | Question Type | Count | Avg Response Length |\n   |---|---|---|\n   | Open-ended | X | X words |\n   | Closed | X | X words |\n   \n   ## Rep Comparison\n   | Sales Rep | Avg Talk Ratio | Questions/Call | Deal Win Rate |\n   |---|---|---|---|\n   \n   ## Coaching Recommendations\n   \n   ### Priority Coaching\n   [Reps who need immediate attention]\n   \n   ### Top Performer Techniques\n   - Conversation flow patterns\n   - Effective question types\n   - Active listening indicators\n   \n   ### Action Plan\n   **For Reps Talking Too Much:**\n   - Practice 30-second rule\n   - Ask more open-ended questions\n   - Use 3-second pause before responding\n   \n   **For Passive Reps:**\n   - Prepare key talking points\n   - Bridge between customer comments\n   - Share relevant insights","contentHash":"bea0b60e4f48828dd6e172a38a234dc542326725bb273786f311541815a5e9c6","copies":0,"createdAt":"2025-08-15T18:04:45.035Z","description":"Advanced conversation dynamics analyzer that calculates talk-to-listen ratios from Read AI meeting transcripts, measures question effectiveness, segments by call type, and correlates patterns with deal outcomes to identify coaching opportunities.","github":{"repoUrl":"https://github.com/ap-devx/sales-analytics-commands","lastSyncDirection":"from-github","metadata":{"importedFrom":"github_repository","repoPrivate":false,"repoDefaultBranch":"main","connectedAt":"2025-08-15T18:04:45.035Z"},"importedAt":"2025-08-15T18:04:45.035Z","lastSyncAt":"2025-09-10T16:21:45.335Z","fileMapping":{"license":"MIT","readme":"talk-ratio-analyzer/README.md","assets":[],"mainFile":"talk-ratio-analyzer/command.md"},"selectedCommand":"talk-ratio-analyzer","fileShas":{"mainFile":"9350ee9e63a98abe5e2ca96c25cedbd7f1cbf2e4","yamlPath":"a8dc32dbb3b43ccceb9b8d87a9e1b76b62ed6ae9","readme":"7eb4060d60c5593db04aadb8d9c46bb95961c679"},"branch":"main","connectionType":"commands_yaml","connected":true,"lastSyncCommit":"9834f2bbcf6f2699720c85bb85e551e1026a001f","importSource":"repository_import","installationId":"81119429","syncStatus":"synced"},"githubRepoUrl":"https://github.com/ap-devx/sales-analytics-commands","id":"64e73235-8e5f-4776-a633-50be2455b258","inputParameters":[{"name":"meeting_identifier","description":"Specific meeting to analyze from Read AI transcripts","label":"Meeting Name or ID","type":"text","required":true,"defaultValue":""},{"name":"drive_folder","description":"Folder path containing Read AI meeting transcripts","label":"Google Drive Folder","type":"text","required":false,"defaultValue":"AI Labs/Meeting Notes (Read AI)"},{"name":"date_range","description":"Date range for analyzing multiple meetings (YYYY-MM-DD to YYYY-MM-DD)","label":"Date Range","type":"text","required":false,"defaultValue":""},{"name":"rep_names","description":"Comma-separated list of sales reps to analyze","label":"Sales Rep Names","type":"text","required":false,"defaultValue":""},{"name":"call_types","description":"Types of calls to analyze (discovery, demo, negotiation, closing)","label":"Call Types","type":"text","required":false,"defaultValue":"discovery,demo,negotiation,closing"},{"defaultValue":"single","name":"analysis_mode","options":["single","comparative","historical"],"description":"Type of analysis to perform","label":"Analysis Mode","type":"select","required":false},{"defaultValue":"yes","name":"question_analysis","options":["yes","no"],"description":"Perform detailed question effectiveness analysis","label":"Analyze Questions","type":"select","required":false},{"defaultValue":"yes","name":"outcome_correlation","options":["yes","no"],"description":"Analyze correlation with deal outcomes","label":"Correlate with Outcomes","type":"select","required":false},{"defaultValue":"yes","name":"coaching_report","options":["yes","no"],"description":"Create detailed coaching recommendations","label":"Generate Coaching Report","type":"select","required":false},{"defaultValue":"markdown","name":"output_format","options":["markdown","json","html"],"description":"Format for the analysis report","label":"Output Format","type":"select","required":false}],"instructions":"# Talk-to-Listen Ratio Analyzer\n\nAdvanced conversation dynamics analyzer for Read AI meeting transcripts that measures sales effectiveness through talk-to-listen ratios, question quality, and outcome correlation.\n\n## Overview\n\nThe Talk-to-Listen Ratio Analyzer transforms Read AI meeting transcripts into actionable insights about conversation dynamics. It calculates precise talk-to-listen ratios, evaluates question effectiveness, segments analysis by call type, and correlates patterns with deal outcomes to identify coaching opportunities and extract top performer techniques.\n\n## Key Features\n\n### Talk-to-Listen Ratio Analysis\n\n- **Precise Calculation**: Measures exact percentage of sales rep vs customer speaking time\n- **Word Count Analysis**: Tracks total words spoken by each party\n- **Segment Analysis**: Analyzes average segment length and conversation flow\n- **Time Estimation**: Calculates estimated speaking duration based on word count\n\n### Question Effectiveness Assessment\n\n- **Question Classification**: Identifies open-ended vs closed questions\n- **Response Measurement**: Tracks customer response length for each question type\n- **Effectiveness Scoring**: Calculates question quality score (0-100)\n- **Pattern Recognition**: Identifies successful questioning techniques\n\n### Call Type Segmentation\n\n- **Optimal Ratios by Type**:\n- Discovery: 30/70 (rep/customer)\n- Demo: 50/50\n- Negotiation: 40/60\n- Closing: 35/65\n- **Deviation Analysis**: Measures alignment with optimal ratios\n- **Contextual Recommendations**: Provides call-type specific improvement suggestions\n\n### Deal Outcome Correlation\n\n- **Win Rate Analysis**: Correlates talk ratios with successful deals\n- **Statistical Insights**: Identifies optimal ranges for winning deals\n- **Pattern Discovery**: Finds conversation patterns that predict success\n- **Predictive Metrics**: Develops benchmarks for future calls\n\n### Coaching Intelligence\n\n- **Priority Identification**: Flags reps needing immediate coaching\n- **Strength Recognition**: Highlights top performers and their techniques\n- **Personalized Plans**: Generates individual improvement action plans\n- **Team Analytics**: Provides team-wide performance insights\n\n## Installation\n\n### Prerequisites\n\n1. Claude Code CLI with MCP support\n1. Required MCP servers:\n- `google-docs-mcp` - For accessing Google Drive documents\n- `zapier` - For Google Drive integration\n- `filesystem` - For local report generation\n\n## Usage\n\n### Detailed Analysis\n\n```bash\n/talk-ratio-analyzer\n```\n\n## Output Structure\n\n### Report Sections\n\n1. **Executive Summary**: Key findings and metrics\n1. **Talk Ratio Analysis**: Detailed breakdown by rep and meeting\n1. **Question Effectiveness**: Analysis of questioning techniques\n1. **Call Type Alignment**: Performance against optimal ratios\n1. **Deal Correlation**: Statistical analysis of outcomes\n1. **Coaching Priorities**: Ranked list of improvement areas\n1. **Top Techniques**: Extracted best practices from top performers\n1. **Individual Reports**: Personalized analysis for each rep\n1. **Action Items**: Specific next steps and recommendations\n\n## Metrics Explained\n\n### Talk-to-Listen Ratio\n\n- **Calculation**: (Rep Words / Total Words) × 100\n- **Optimal Ranges**: Varies by call type (see segmentation above)\n- **Red Flags**: >70% rep talking in discovery, <30% in demos\n\n### Question Effectiveness Score\n\n- **Components**:\n- Open-ended question ratio (50% weight)\n- Average response length (50% weight)\n- **Scoring**:\n- 80-100: Excellent consultative approach\n- 60-79: Good questioning skills\n- 40-59: Needs improvement\n- <40: Requires immediate coaching\n\n### Alignment Score\n\n- **Calculation**: 100 - |Actual Ratio - Optimal Ratio|\n- **Interpretation**:\n- 90-100: Excellent alignment\n- 75-89: Good alignment\n- 60-74: Moderate alignment\n- <60: Poor alignment\n\n## Best Practices\n\n### For Discovery Calls\n\n- Aim for 30% talk time\n- Use 80% open-ended questions\n- Average 3+ follow-up questions per topic\n- Listen for 45+ seconds before responding\n\n### For Demo Calls\n\n- Maintain 50/50 balance\n- Check for understanding every 2-3 minutes\n- Ask engagement questions throughout\n- Pause for questions after each feature\n\n### For Negotiations\n\n- Target 40% talk time\n- Focus on clarifying questions\n- Summarize agreements frequently\n- Let customer express concerns fully\n\n## Performance Benchmarks\n\n- **Single Meeting**: 30-60 seconds\n- **10 Meetings**: 2-3 minutes\n- **50 Meetings**: 5-8 minutes\n- **100+ Meetings**: 10-15 minutes\n\n## Changelog\n\n### Version 1.0.0 (2025-08-13)\n\n- Initial release\n- Full talk-to-listen ratio analysis\n- Question effectiveness scoring\n- Call type segmentation\n- Deal outcome correlation\n- Coaching recommendations\n- Top performer technique extraction\n\n## License\n\nMIT License. All rights reserved.\n\n---\n\n*Copyright © 2025 AlphaPoint Corp.*","likes":0,"mcpRequirements":[{"tier":"required","name":"Google Docs MCP","serverId":"google-docs-mcp"},{"tier":"required","name":"Zapier MCP","serverId":"zapier"},{"tier":"required","name":"Filesystem MCP","serverId":"filesystem"}],"mcp_search_content":"docker-filesystem","organizationUsername":"ap_dev","price":"free","search_content":"talk-to-listen ratio analyzer advanced conversation dynamics analyzer that calculates talk-to-listen ratios from read ai meeting transcripts, measures question effectiveness, segments by call type, and correlates patterns with deal outcomes to identify coaching opportunities. /talk-ratio-analyzer data-analysis claude-code@2025.06","tags":["talk-to-listen-ratio","conversation-dynamics","sales-intelligence","meeting-analysis","coaching","question-effectiveness","google-drive","read-ai","performance-analytics","best-practices","outcome-correlation"],"title":"Talk-to-Listen Ratio Analyzer","type":"command","updatedAt":"2025-09-10T16:21:45.335Z","userId":"9SvEH1x7jLQs7vywARPKUuMd4Ix1","visibility":"public","name":"talk-ratio-analyzer","userInteraction":{"userHasStarred":false}}