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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.

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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

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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

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Common Metric Types

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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

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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

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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

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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

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Setup Process

  1. Define Dimension: What business aspect you want to measure
  2. Create Scale: Define what each 1-5 score represents
  3. Train Team: Ensure consistent scoring across sales reps
  4. Apply Systematically: Score deals consistently throughout pipeline
  5. Analyze Patterns: Use data to identify success factors

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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

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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

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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

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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