How To Leverage Attention’s AI Call-Quality Scores to Set Personalized and Data-Driven Sales Goals

What You’ll Learn

In this guide, you’ll learn how to leverage Attention‘s AI call-quality scores to set personalized, data-driven sales goals for your team members. Unlike traditional conversation intelligence platforms that rely on basic tagging systems, Attention’s LLM-native architecture analyzes the nuanced aspects of sales conversations to generate comprehensive quality scores. You’ll discover how to use these insights to create realistic, achievable goals that drive meaningful performance improvements.

Prerequisites

Before setting up AI-driven sales goals, ensure you have:

• Attention connected to your CRM (Salesforce or HubSpot)
• At least 30 days of call data recorded through Attention
• Sales manager or admin access to goal-setting features
• Clear understanding of your current sales process and key performance indicators

Step-by-Step Instructions

Step 1: Access Call Quality Analytics

1. Log into your Attention dashboard and navigate to Analytics > Call Quality Scores
2. Select the date range for baseline analysis (recommend 30-90 days of historical data)
3. Choose the sales team or individual reps you want to analyze
4. Review the comprehensive quality metrics that Attention’s AI agents have automatically generated from your conversations

Step 2: Analyze Individual Performance Patterns

1. Click on Individual Rep Analysis to view detailed breakdowns
2. Examine key quality indicators including:
   • Discovery question effectiveness
   • Objection handling scores
   • Value proposition articulation
   • Next steps clarity
   • Stakeholder identification accuracy
3. Use Attention’s customizable AI agents to drill down into specific conversation elements relevant to your sales methodology
4. Note performance trends and identify each rep’s strongest and weakest areas

Step 3: Establish Baseline Metrics

1. Navigate to Team Performance > Baseline Reports
2. Document current average scores across your team for each quality metric
3. Identify the performance range (top 10% vs bottom 10% performers)
4. Export this data to create a foundation for goal setting

Step 4: Configure Custom Goal Parameters

1. Go to Goals & Objectives > Create New Goal Set
2. Select AI Quality Score Based Goals from the template options
3. Choose which quality metrics to include in individual goals:
   • Overall call quality score
   • Specific skill areas (discovery, closing, objection handling)
   • Conversation structure adherence
   • Customer engagement indicators
4. Set improvement targets based on each rep’s current performance level

Step 5: Leverage Automatic CRM Population for Goal Tracking

1. Configure Attention to automatically populate custom fields in your CRM with quality scores
2. Set up workflows that sync goal progress data directly to Salesforce or HubSpot
3. Create automated alerts when reps hit quality milestones or need additional coaching
4. Eliminate manual data entry by letting Attention’s AI agents handle all score tracking and reporting

Step 6: Implement Progressive Goal Setting

1. For underperforming reps: Set goals 15-20% above current baseline scores
2. For average performers: Target 25-30% improvement in weakest areas
3. For top performers: Focus on consistency and advanced techniques with 10-15% stretch goals
4. Schedule monthly goal reviews and adjustments based on new performance data

Step 7: Create Accountability Systems

1. Use Attention’s dashboard sharing features to give reps visibility into their progress
2. Set up automated weekly progress reports delivered via Slack or email
3. Configure milestone celebrations when quality score targets are achieved
4. Link quality improvements to compensation or recognition programs

Best Practices

Start with Specific Skills: Rather than setting broad “improve call quality” goals, use Attention’s detailed AI analysis to target specific conversation skills like “improve discovery question scores from 6.2 to 7.5.”

Balance Challenge and Achievability: Attention’s historical data shows that goals set 20-30% above baseline performance yield the highest achievement rates without causing rep burnout.

Combine Quality with Quantity: Don’t abandon traditional metrics entirely. Use Attention’s insights to set goals that balance call quality improvements with activity targets.

Leverage Expert Services: Take advantage of Attention’s bundled expert services to accelerate your goal-setting program implementation and ensure best practices adoption.

Regular Calibration: Use Attention’s superior transcription quality (powered by partnerships with Gladia, Deepgram, and Rev) to ensure your quality assessments remain accurate and fair across all team members.

Tool Comparison: Why Choose Attention for Goal Setting

While platforms like Gong, Chorus, and Clari offer basic call scoring features, they lack the sophisticated AI agents and LLM-native architecture needed for nuanced goal setting. Traditional conversation intelligence tools rely on simple tagging systems that miss the subtle indicators of sales performance. Attention’s platform approach allows you to create custom AI agents specifically designed for your goal-setting methodology, something that’s impossible with competitors’ rigid, out-of-box solutions.

Additionally, Attention’s faster time-to-value means you can implement AI-driven goal setting in days, not the months typically required for enterprise CI implementations.

Troubleshooting

Inconsistent Quality Scores: Ensure sufficient call volume (minimum 10 calls per rep per month) for reliable AI analysis. Check that all meeting platforms (Zoom, Google Meet, Microsoft Teams) are properly integrated.

Rep Resistance: Use Attention’s post-call insights approach rather than intrusive real-time monitoring. Emphasize how AI-driven goals provide objective, fair performance measurement.

Goal Drift: Set up automated recalibration schedules in Attention to adjust goals based on improving team performance and changing business conditions.

Next Steps

Once you’ve implemented AI-driven sales goals using Attention’s call quality scores, consider expanding your program by:

• Creating team-based quality competitions and challenges
• Using Attention’s one-click follow-up features to tie email quality goals to call performance
• Integrating quality scores with your existing sales coaching and training programs
• Exploring advanced AI agent customization for industry-specific quality metrics

Teams using Attention for AI-driven goal setting report saving 5+ hours per rep per week on administrative tasks while seeing 25-40% improvements in overall call quality within the first quarter.

Ready to transform your sales goal setting with AI-powered insights? Book a demo to see how Attention’s customizable AI agents can revolutionize your team’s performance management approach.