This guide will show you how to use Attention‘s AI agents to extract and analyze high-performing closing questions from your best discovery calls. You’ll learn to identify patterns in successful conversations, create customizable closing question templates, and automatically populate your CRM with structured data about your prospects’ readiness to move forward.
Unlike traditional conversation intelligence tools like Gong or Chorus that rely on basic tagging and search, Attention’s LLM-native architecture analyzes the nuanced context of unstructured sales conversations to surface the most effective closing strategies from your top performers.
Prerequisites
- Active Attention account with admin access
- Salesforce or HubSpot CRM integration configured
- At least 20-30 recorded discovery calls in your system
- Call recordings from your top-performing sales reps
Step-by-Step Instructions
Step 1: Connect Your Call Recording Platform
- Navigate to Integrations > Call Platforms in your Attention dashboard
- Connect your Zoom, Google Meet, or Microsoft Teams account
- Enable automatic call ingestion for your sales team
- Wait 24-48 hours for Attention to process existing recordings with superior transcription quality from partners like Gladia and Deepgram
Step 2: Create a Custom AI Agent for Closing Analysis
- Go to AI Agents > Create New Agent
- Select the “Custom Analysis” template
- Name your agent “Discovery Call Closing Questions Analyzer”
- In the agent configuration, add these specific prompts:
- “Identify all closing questions asked during discovery calls”
- “Classify closing questions by type (assumptive, alternative choice, urgency-based, etc.)”
- “Rate the effectiveness based on prospect response and engagement”
- “Extract the exact wording used by top performers”
- Set the agent to analyze calls tagged as “Discovery” in your CRM
Step 3: Configure Performance Metrics
- Navigate to Analytics > Performance Metrics
- Create a new metric called “Discovery Call Conversion Rate”
- Link this metric to opportunities that moved to the next stage within 30 days
- Filter for calls marked as “Discovery” or “Qualification” stage
- Set the minimum sample size to 10 calls per rep for statistical significance
Step 4: Run the Analysis
- Return to your custom AI agent
- Click Analyze Historical Calls
- Select a date range covering your last 3-6 months of discovery calls
- Choose “Top Performers Only” and select reps with conversion rates above your team average
- Run the analysis – Attention’s LLM-native architecture will process the unstructured conversation data in 10-15 minutes
Step 5: Review and Extract Closing Questions
- Go to Reports > Agent Analysis
- Select your “Discovery Call Closing Questions Analyzer”
- Review the automatically generated report showing:
- Most frequently used closing questions by top performers
- Success rates for different question types
- Prospect response patterns and sentiment
- Questions that led to next meeting bookings
- Export the findings to create your closing question library
Step 6: Set Up Automatic CRM Population
- Navigate to CRM Integration > Field Mapping
- Create custom fields in Salesforce/HubSpot for:
- “Closing Questions Used”
- “Prospect Closing Response”
- “Next Steps Confirmed”
- “Decision Timeline Discussed”
- Configure Attention to automatically populate these fields from future discovery calls
- Set up workflow triggers for follow-up sequences based on closing question responses
Step 7: Create Follow-Up Templates
- Access Email Templates > One-Click Follow-Ups
- Create templates based on different closing question scenarios identified in your analysis
- Include personalization tokens that pull from the automatically populated CRM data
- Set these templates to auto-generate immediately after discovery calls end
Best Practices
Focus on Question Timing: Use Attention’s conversation flow analysis to identify when during discovery calls your top performers ask closing questions. The platform reveals whether successful reps close early, mid-conversation, or at natural transition points.
Analyze Prospect Language Patterns: Attention’s advanced LLM analysis can identify specific words or phrases prospects use that indicate readiness for closing questions. Look for buying signals that precede successful closes.
Create Situation-Specific Questions: Configure different AI agents for different prospect profiles (enterprise vs. SMB, different industries, etc.) to surface specialized closing approaches for each segment.
Monitor Response Quality: Beyond tracking whether prospects responded positively, use Attention to analyze the depth and specificity of their responses to different closing questions.
Regular Updates: Run this analysis monthly to identify evolving patterns and new successful closing techniques as your team develops.
Troubleshooting
Issue: Agent returns generic closing questions rather than specific examples
Solution: Refine your agent prompts to request “exact verbatim closing questions” and increase the minimum conversation length filter to focus on substantive discovery calls.
Issue: Low sample size for analysis
Solution: Extend your date range or include more reps in the “top performer” category. Attention needs sufficient data points for meaningful pattern recognition.
Issue: CRM fields not populating automatically
Solution: Check your field mapping configuration and ensure proper permissions are set for Attention to write to custom fields in your CRM.
Why Attention Outperforms Traditional Tools
Unlike Gong’s limited out-of-box agents or Chorus’s basic tagging system, Attention’s customizable AI agents adapt to your specific closing methodology. The platform’s LLM-native architecture understands context and nuance that traditional conversation intelligence tools miss, while automatic CRM population eliminates manual data entry that other platforms require.
Teams using Attention report saving 5+ hours per rep per week on administrative tasks while dramatically improving their closing question effectiveness through data-driven insights.
Next Steps
Once you’ve extracted your top-performing closing questions, consider setting up additional AI agents to:
- Analyze objection handling techniques that follow unsuccessful closing attempts
- Track which closing questions work best for different buyer personas
- Monitor how closing question effectiveness changes across different deal sizes
- Create coaching scorecards based on closing question usage patterns
Ready to transform your discovery call effectiveness with AI-powered closing question analysis? Book a demo to see how Attention’s customizable agents can unlock insights from your best sales conversations.

