Sales Pipeline Leak Evaluator

Find the stage where your pipeline is bleeding the most deals.

%
%
%
%
MQLs
1,400
35% of leads
SQLs
630
45% of MQLs
Opportunities
347
55% of SQLs
Won deals
97
2.4% lead→win

Your weakest link is Opp → Win at 28%. Lifting the lowest stage a few points compounds through every stage below it, fix the leak, don't just pour in more leads.

Overall lead-to-win is the product of every stage, so a single weak conversion caps the whole funnel regardless of top-of-funnel volume.

About this calculator

Total lead-to-win rate hides where a funnel actually breaks. A pipeline can look fine in aggregate while one stage, often MQL→SQL or SQL→Opportunity, is quietly capping everything downstream. This calculator walks a lead volume through four stage conversion rates and flags the single weakest link, because fixing that one stage compounds through every stage below it.

How to use it

  1. Enter monthly leads at the top of funnel, and the four stage conversion rates: lead→MQL, MQL→SQL, SQL→opportunity, opportunity→win.
  2. Read the volume surviving at each stage, MQLs, SQLs, opportunities, and won deals.
  3. Check the verdict for your weakest stage, the lowest conversion rate among the four you entered.
  4. Prioritize fixing that stage before adding more top-of-funnel leads, since a weak stage caps everything that flows through it regardless of volume.

Methodology

Each stage multiplies the surviving volume from the stage above by that stage's conversion rate: MQLs = leads × lead→MQL rate, SQLs = MQLs × MQL→SQL rate, and so on through opportunities and wins.

Overall lead-to-win rate is the product of all four stage rates, not their average. A single weak stage caps the whole chain: a funnel with three 50% stages and one 10% stage converts at roughly the same overall rate as a funnel where every stage is 10%.

The "weakest link" flagged in the verdict is simply the lowest of the four rates entered. It's a diagnostic pointer, not a full root-cause analysis, the actual cause (routing delay, poor MQL definition, weak SDR follow-up, pricing friction) needs to be investigated separately.

This model assumes stage rates are independent of volume. In practice, pushing more raw leads into a weak filter (like MQL scoring) can change the rate itself, so re-check rates periodically rather than treating them as fixed constants.

FAQ

Why focus on the weakest stage instead of the overall conversion rate?

Because overall lead-to-win is a multiplied chain, improving your strongest stage by 10 points does far less than improving your weakest stage by the same 10 points. A stage already converting at 70% has little room to improve; one converting at 15% usually has the most fixable friction and the most leverage.

What typically causes an MQL→SQL leak specifically?

Most commonly a mismatch between marketing's MQL definition and what sales actually considers qualified, plus routing delay (leads going stale before a rep reaches them) and unclear follow-up ownership. It's rarely a top-of-funnel volume problem.

Should I use average rates over a long period, or last month's?

Use a rolling 3-6 month average where possible. Single-month rates are noisy, especially at the opportunity→win stage where deal cycles can span months and distort a single period's numbers.

Does fixing the weakest stage guarantee more revenue?

It guarantees more deals surviving that stage, which flows through to more wins if downstream stages hold steady. It doesn't guarantee deal value or win-rate at later stages stays the same as a higher volume of deals moves through them, watch for quality dilution if the fix just lowers the qualification bar.