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Sales Funnel Targets Calculator
Translate a revenue target into required wins, opportunities, SQLs, MQLs, and leads using funnel conversion rates.
If you want $X in new revenue, you need a certain number of wins. Wins require opportunities, and opportunities require qualified leads.
This calculator converts a revenue target into funnel volume targets using your conversion rates so you can plan demand generation and sales capacity.
Prefer an explanation- Read the guide.
Sales funnel targets: leads -> MQL -> SQL -> opp -> win (how to plan)Sales ops metrics hub: quota, pipeline, win rate, and capacity planningRequired pipeline: how much pipeline (and how many deals) you needPipeline coverage: what it is, how to calculate it, and benchmarks
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Tip: you can type commas (e.g., 10,000).
Example
Using the default inputs, the result is:
3,333
- Revenue target (period)
- $500,000
- Average deal size (ACV)
- $25,000
- Lead -> MQL
- 20%
- MQL -> SQL
- 30%
- SQL -> Opportunity
- 40%
- Opportunity -> Win
- 25%
How to calculate
- Enter your revenue target and average deal size (ACV).
- Enter funnel conversion rates from lead -> MQL -> SQL -> opp -> win.
- Review required counts at each funnel stage and implied pipeline value.
Formula
wins = target / deal size; opps = wins / opp->win; SQLs = opps / SQL->opp; MQLs = SQLs / MQL->SQL; leads = MQLs / lead->MQL
- Conversion rates are stable and measured over consistent windows.
- Ignores time lag (sales cycle); align inputs to the same period.
- Assumes average deal size is representative; segment for higher accuracy.
FAQ
Why does a small change in conversion rates move leads a lot-
Because conversion rates multiply. Small improvements at each stage compound into a large reduction in top-of-funnel volume required.
Should I use leads or MQLs as the starting point-
Use the earliest stage you can measure consistently. If lead quality varies widely by channel, model channels separately for accuracy.
Common mistakes
- Using conversion rates from a different segment (SMB vs enterprise).
- Mixing definitions (what counts as an MQL/SQL).
- Ignoring time lag (leads generated now may close next period).
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Quick checks
- Keep time units consistent (monthly vs annual) across inputs and outputs.
- Segment by cohort/channel/plan before trusting a blended average.
- Use the related guide to avoid common definition and denominator mismatches.