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sales intermediate

Calculate Sales Performance Metrics

AI prompt to analyze sales data and calculate key performance metrics like conversion rates, CAC, LTV, and revenue growth for better CRM insights.

Works with: chatgptclaudegemini

Prompt Template

Act as a senior sales analyst and calculate comprehensive sales metrics based on the provided data. Analyze the following sales information and provide detailed calculations with explanations. Sales Data: - Time Period: [TIME_PERIOD] - Total Revenue: [TOTAL_REVENUE] - Number of Deals Closed: [DEALS_CLOSED] - Number of Leads Generated: [LEADS_GENERATED] - Number of Qualified Prospects: [QUALIFIED_PROSPECTS] - Customer Acquisition Cost: [CUSTOMER_ACQUISITION_COST] - Average Deal Size: [AVERAGE_DEAL_SIZE] - Sales Team Size: [SALES_TEAM_SIZE] Calculate and provide the following metrics with formulas and interpretations: 1. **Conversion Rates**: Lead-to-prospect conversion rate, prospect-to-customer conversion rate, and overall lead-to-customer conversion rate 2. **Revenue Metrics**: Revenue per salesperson, revenue growth rate (if previous period data available), and average revenue per customer 3. **Efficiency Metrics**: Sales velocity, quota attainment rate, and pipeline conversion rate 4. **Performance Indicators**: Win rate analysis, sales cycle insights, and productivity metrics For each metric: - Show the calculation formula - Provide the actual calculated value - Explain what the metric means - Indicate if the result is good, average, or needs improvement based on industry benchmarks - Suggest actionable recommendations for improvement where applicable Present the analysis in a clear, structured format suitable for executive reporting and CRM system input.

Variables to Customize

[TIME_PERIOD]

The reporting period for the sales data

Example: Q3 2024 (July - September)

[TOTAL_REVENUE]

Total revenue generated during the period

Example: $2,450,000

[DEALS_CLOSED]

Number of successful deals completed

Example: 156

[LEADS_GENERATED]

Total number of leads generated

Example: 3,200

[QUALIFIED_PROSPECTS]

Number of leads that became qualified prospects

Example: 640

[CUSTOMER_ACQUISITION_COST]

Average cost to acquire each customer

Example: $1,250

[AVERAGE_DEAL_SIZE]

Average value of each closed deal

Example: $15,700

[SALES_TEAM_SIZE]

Number of sales representatives

Example: 8

Example Output

# Sales Performance Metrics Analysis - Q3 2024 ## Conversion Rates **Lead-to-Prospect Conversion**: 20% (640/3,200) - Industry benchmark: 13-20% ✅ **GOOD** - Recommendation: Maintain current lead qualification process **Prospect-to-Customer Conversion**: 24.4% (156/640) - Formula: Deals Closed ÷ Qualified Prospects - Industry benchmark: 15-20% ✅ **EXCELLENT** **Overall Lead-to-Customer**: 4.9% (156/3,200) - This indicates strong lead quality and sales process efficiency ## Revenue Metrics **Revenue per Salesperson**: $306,250 ($2,450,000/8) - Strong performance indicating good territory management **Average Revenue per Customer**: $15,700 - Matches provided average deal size, indicating consistent pricing ## Efficiency Metrics **Customer Acquisition Cost vs. Deal Size Ratio**: 1:12.6 - CAC of $1,250 generates $15,700 average deal value - Healthy ratio suggesting profitable customer acquisition **Sales Productivity**: 19.5 deals per rep (156/8) - Above average productivity for the quarter ## Key Recommendations 1. **Optimize lead generation** - Current conversion rates are strong, focus on increasing lead volume 2. **Investigate top performers** - Identify what's driving the excellent prospect conversion rate 3. **Scale successful processes** - With strong metrics across the board, consider expanding team size

Pro Tips for Best Results

  • Include previous period data when available to calculate growth rates and trends
  • Always compare your metrics against industry benchmarks to provide meaningful context
  • Break down metrics by individual salesperson or team to identify top performers and improvement areas
  • Use conditional formatting or visual indicators (✅❌) to make the analysis more digestible
  • Include specific, actionable recommendations rather than just presenting numbers

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