Primary Use Case: Voice-to-Text & Insight Extraction

Background Overview

Field teams need to capture insights from customer conversations quickly and accurately. Manual note-taking is time-consuming and often incomplete. This primary use case describes voice transcription, insight extraction, and knowledge capture to improve field productivity.

Goals & Value

• Real-time Transcription: Convert voice to text during conversations.
• Insight Extraction: Automatically identify key points and opportunities.
• Knowledge Retention: Capture and store insights systematically.
• Productivity Improvement: Reduce manual documentation time.

Participating Roles

• Field Sales: Record voice notes during customer interactions.
• Field Service: Capture service issues and resolutions via voice.
• Sales Managers: Review captured insights and coach teams.
• Data Team: Maintain transcription accuracy and insight models.
• IT Team: Ensure voice data security and privacy.

Primary Scenario User Story

As a field service technician, I want to speak my notes instead of typing them, so that I can focus on customer service and ensure complete documentation.

Sub-scenario Details

Sub-scenario A: Voice Recording & Transcription

• Roles & Triggers: Field staff need to capture conversations.
• Main Process:
  1. Field staff record voice notes during interactions.
  2. System transcribes voice to text in real-time.
  3. Review and edit transcriptions for accuracy.
  4. Store transcriptions with customer records.
• Success Criteria: Accurate transcription; fast processing; editable output.
• Exceptions & Risk Control: Transcription errors; background noise; privacy concerns.
• Metric Suggestions: Transcription accuracy, processing speed, edit time.

Sub-scenario B: Key Information Extraction

• Roles & Triggers: Need to identify important points from conversations.
• Main Process:
  1. Analyze transcribed text for key information.
  2. Extract customer requirements, pain points, and opportunities.
  3. Identify action items and follow-up tasks.
  4. Tag information for easy search and retrieval.
• Success Criteria: Accurate extraction; relevant insights; actionable items.
• Exceptions & Risk Control: Missed key points; false positives; context understanding.
• Metric Suggestions: Extraction accuracy, relevance score, action item completion.

Sub-scenario C: Automated Summary Generation

• Roles & Triggers: Need concise summaries of long conversations.
• Main Process:
  1. Generate summaries of transcribed conversations.
  2. Highlight key points and decisions.
  3. Structure summaries for easy review.
  4. Distribute summaries to relevant stakeholders.
• Success Criteria: Clear summaries; complete coverage; appropriate distribution.
• Exceptions & Risk Control: Summary accuracy; key point omission; distribution failures.
• Metric Suggestions: Summary quality, distribution success, stakeholder feedback.

Sub-scenario D: Knowledge Base Integration

• Roles & Triggers: Captured insights should be searchable.
• Main Process:
  1. Store transcribed insights in knowledge base.
  2. Make insights searchable by topic and customer.
  3. Link insights to related documentation.
  4. Enable sharing and collaboration on insights.
• Success Criteria: Searchable insights; easy access; relevant connections.
• Exceptions & Risk Control: Search accuracy; data organization; access permissions.
• Metric Suggestions: Search success rate, insight utilization, collaboration rate.

Scenario-level Test Case Examples

Test Preparation: Prepare voice recording app, transcription engine, insight extraction tools, and knowledge base platform.

Test Case A-1: Voice Note Transcription (Positive)

• Prerequisites: Sales has important customer conversation.
• Steps:
  1. Sales records voice notes during conversation.
  2. System transcribes to text.
• Expected Results:
  • Voice accurately transcribed to text.
  • Key points extracted automatically.
  • Notes stored with customer record.

Test Case B-1: Insight Extraction (Negative)

• Prerequisites: Complex conversation with multiple topics.
• Steps:
  1. Record conversation and transcribe.
  2. System extracts insights.
• Expected Results:
  • Key points correctly identified.
  • Action items highlighted.
  • Opportunities flagged for follow-up.

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