Required pipeline: how much pipeline (and how many deals) you need

Translate a revenue target into required pipeline dollars, wins, and opportunities using win rate and average deal size.

Updated 2026-01-30

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Why required pipeline matters

Pipeline is the input; bookings are the output. If you know your win rate and average deal size, you can estimate how much pipeline and how many opportunities you need to hit a target.

Core math

  • Wins needed = target / average deal size.
  • Opportunities needed = wins / win rate.
  • Pipeline needed (value) ~ target / win rate.

Make it accurate

  • Segment by deal size (ACV bands) and motion (PLG vs sales-led).
  • Use stage-consistent win rate.
  • Add a slippage buffer based on history (many deals push).
  • Re-check the buffer each quarter as close rates and cycles change.

Translate to activity targets

  • Convert opportunities needed into required SQLs using stage conversion rates.
  • Translate SQLs into MQLs or PQLs based on historical funnel ratios.
  • Back into daily or weekly targets for pipeline creation.

Pipeline required QA checklist

  • Use win rate and deal size from the same segment and stage definition.
  • Check that expected close dates fit the target period.
  • Remove pipeline that is stalled or missing next steps.
  • Confirm that required pipeline per rep is realistic for capacity.

Scenario stress test

  • Run win rate down 5 points to see how pipeline needs expand.
  • Test ACV up and down 10% to see how required wins change.
  • Use the scenario range to plan top-of-funnel requirements.

Common mistakes

  • Using a single average deal size across segments.
  • Using win rate from the wrong funnel stage.
  • Ignoring time lag (pipeline must be closeable within the period).

Planning checklist

  • Translate pipeline dollars into required SQLs and MQLs.
  • Use historical slippage to add a realistic buffer.
  • Review coverage weekly and adjust targets early.

More in saas metrics

Pipeline coverage and sales cycle math: set realistic targets (and avoid sandbagging)
PLG metrics hub: activation, trial conversion, stickiness, and adoption