Overview
Metrics are custom business dimensions that let you score and analyze deals beyond standard revenue and stage tracking. Using a 1-5 scale, metrics help quantify qualitative aspects of your sales process and identify patterns that drive success.Metric Structure
- Name: Clear, specific dimension (e.g., “Champion Strength”)
- Description: What this metric measures and how to score it
- Scale Definition: What each score (1-5) represents
- Use Case: When and why to apply this metric
Scoring Framework
All metrics use a consistent 1-5 scale:- 5: Excellent/Ideal state
- 4: Good/Above average
- 3: Average/Neutral
- 2: Below average/Concerning
- 1: Poor/Major risk
Common Metric Types
Sales Process Quality
- Champion Strength: How well-positioned and influential your champion is
- Buying Process Clarity: How well-defined the customer’s evaluation process is
- Decision Timeline: Urgency and clarity of purchase timing
- Budget Authority: Access to and influence over purchasing decisions
Technical Fit
- Solution Alignment: How well your product matches their requirements
- Implementation Complexity: Ease of deployment and integration
- Technical Champion Buy-in: Support from technical stakeholders
- Competitive Positioning: Strength against alternatives
Strategic Value
- Business Impact: Potential value delivery to customer
- Strategic Importance: Priority level within customer organization
- Executive Sponsorship: C-level support and involvement
- Expansion Potential: Opportunity for future growth
Metric Analytics
- Deal Correlation: Which metrics predict deal success
- Score Distribution: How deals perform across different metric ranges
- Trend Analysis: How metric scores change throughout sales cycles
- Segmentation: Deal performance by metric combinations
- Forecasting: Use metric patterns to predict deal outcomes
Setup Process
- Define Dimension: What business aspect you want to measure
- Create Scale: Define what each 1-5 score represents
- Train Team: Ensure consistent scoring across sales reps
- Apply Systematically: Score deals consistently throughout pipeline
- Analyze Patterns: Use data to identify success factors
Best Practices
- Clear Definitions: Make scoring criteria objective and specific
- Team Alignment: Ensure all reps understand and apply metrics consistently
- Regular Calibration: Review and adjust metric definitions as needed
- Actionable Insights: Focus on metrics that inform specific actions
- Balanced Portfolio: Use 3-5 metrics that cover different deal aspects
Data Integration
Metrics work alongside other Hindsight data:- Deal Conversations: AI extracts evidence supporting metric scores
- Feature Discussions: Connect capability mentions to technical fit metrics
- Decision Driver Analysis: Link strategic metrics to buyer priorities
- Competitive Intelligence: Inform positioning metrics with market data
Reporting & Insights
- Metric Dashboards: Visual summaries of deal performance by dimension
- Correlation Analysis: Which metrics most strongly predict outcomes
- Team Performance: How different reps score and succeed with metrics
- Pipeline Health: Early warning indicators from metric trends
- Win/Loss Patterns: Metric profiles of successful vs. unsuccessful deals
Common Use Cases
- Deal Qualification: Identify and prioritize high-potential opportunities
- Risk Assessment: Flag deals with concerning metric patterns
- Sales Coaching: Help reps improve in specific areas
- Process Optimization: Identify stages where deals typically struggle
- Forecasting Accuracy: Improve prediction models with qualitative factors