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sales-forecast

Build sales forecasts grounded in pipeline data and historical conversion rates, not feelings. Categorize deals into commit/upside/best-case, calculate weighted pipeline, run sanity checks, and produce actionable forecast reports. Separately, compare prior forecasts to actual outcomes to diagnose accuracy patterns and bias.

  • Area: Sales & Clients
  • Category: sales
  • Level: beginner
  • Input: conversation
  • Output: document
  • Setup: none
  • Roles: CEO / Founder, Head of Sales

Builds sales forecasts from vault deal and lead records with commit, upside, and best-case pipeline categorization.

How you ask

  • “Forecast revenue”
  • “Quota attainment”
  • “Commit number”

Inputs

  • lead-records — Lead records — the prospects being worked.
  • deal-records — Deal records the forecast is built from.
  • profile — Company or client profile — entity and relationship context.
  • pipeline_data — Active deals from the client deals folders (client.deals) and the lead profiles under the company leads folder ({company.leads}, one {lead.profile} per lead)
  • forecast_period — Month or quarter being forecast (e.g., 2026-Q2, 2026-04)
  • revenue_target — Quota or revenue goal for the period — ask if not provided
  • prior_forecasts — Previous forecast reports from the company sales folder (company.sales, subfolder reports/), filename sales_forecast_*.md
  • actuals — Closed-won deal data and revenue actuals for the same periods

Outputs

  • accuracy_report (markdown)
  • forecast_report (markdown)
  • {company.sales}/reports/forecast_accuracy_{YYYY-MM-DD}.md
  • {company.sales}/reports/sales_forecast_{YYYY-MM-DD}.md