sales-forecasting
Produces revenue forecasts by analyzing CRM pipeline data, historical close rates, seasonal trends, and deal velocity. Provides best-case, worst-case, and most-likely scenarios. Highlights risks to fo
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View on GitHubSKILL.mdskills/sales-forecasting/SKILL.md
GitHubSales Forecasting
Generate accurate sales forecasts based on pipeline data, historical trends, and win rates.
Integrations: HubSpot, Salesforce
When to Use
- Leadership needs revenue projections for upcoming quarters
- The user wants to assess pipeline health and coverage
- The user mentions "forecast", "revenue projection", or "pipeline coverage"
Steps
Step 1: Gather Pipeline Data
Pull all open deals with stage, value, close date, and engagement metrics.
Step 2: Apply Historical Win Rates
Calculate expected revenue using historical conversion rates by segment.
Step 3: Generate Scenarios
Produce best-case, worst-case, and most-likely revenue scenarios.
Step 4: Identify Risks
Flag deals with declining engagement or overdue close dates.
Output
Deliver:
- Three-scenario revenue forecast
- Pipeline coverage analysis
- Risk assessment with recommended actions