What is a good overall funnel conversion rate from lead to closed-won?

Overall lead-to-close conversion rates vary widely by industry and motion. B2B SaaS companies with an inbound-led model typically see 2-5%, while outbound-driven organizations average 0.5-2%. The more important metric is how each stage conversion compares to your own historical baseline and peer benchmarks.

How large a sample size do I need for reliable funnel conversion analysis?

For statistically meaningful conversion rates at each stage, aim for a minimum of 200 records entering each funnel stage over the analysis period. With fewer than 200, single deals disproportionately swing your percentages. For segment-level analysis, you may need to extend the time window to accumulate sufficient volume.

Funnel Conversion Analysis: Finding the Leaks in Your Revenue Engine

Every revenue organization has funnel leaks - the question is whether you can see them. A deal that quietly disqualifies in Discovery costs pipeline. A proposal that stalls in legal review costs time. Funnel conversion analysis turns these invisible losses into visible, measurable, and fixable problems. When done rigorously, it becomes the most actionable analysis in your RevOps toolkit.

Building Your Conversion Funnel Map
Stage-by-Stage Conversion Benchmarks
Identifying Drop-Off Points
Segmenting Conversions for Deeper Insight
The Actionable Recommendations Framework
Key Takeaways

Building Your Conversion Funnel Map¶

Before calculating rates, define your funnel stages precisely. Ambiguous stage definitions produce unreliable conversion data. A typical B2B funnel includes:

MQL (Marketing Qualified Lead)
SAL (Sales Accepted Lead)
SQL (Sales Qualified Lead)
Discovery Completed
Proposal Sent
Negotiation
Closed Won / Closed Lost

Map each stage to a clear, binary entry criterion. For example, “Discovery Completed” should mean a specific set of qualification criteria has been documented, not simply that a meeting occurred.

Stage-by-Stage Conversion Benchmarks¶

Here are typical stage conversion rates for a B2B SaaS company selling to mid-market accounts with an average deal size of $30K-$75K:

Stage Transition	Median Conversion	Top Quartile	Bottom Quartile
MQL to SAL	45%	58%	32%
SAL to SQL	52%	65%	38%
SQL to Discovery	68%	78%	55%
Discovery to Proposal	55%	67%	40%
Proposal to Negotiation	60%	72%	48%
Negotiation to Closed Won	48%	60%	35%
Overall MQL to Won	2.8%	5.1%	1.0%

Important: These benchmarks shift significantly by segment. Enterprise deals (ACV $150K+) typically show lower early-stage conversion but higher late-stage close rates. SMB funnels convert faster at every stage but carry smaller values.

Identifying Drop-Off Points¶

Not all funnel leaks are equal. Prioritize by revenue impact using this formula:

Revenue Impact of Leak = (Lost Deals at Stage x Average Deal Value x Downstream Win Rate)

For example, if 40 deals drop off at the Proposal stage each quarter, and your average deal is $50K with a 48% close rate from Proposal onward:

Revenue Impact = 40 x $50,000 x 0.48 = $960,000 in leaked quarterly revenue

Compare this to a leak at the MQL-to-SAL stage where 100 leads drop off but the downstream value is much lower:

Revenue Impact = 100 x $50,000 x 0.028 = $140,000

The Proposal-stage leak is nearly 7x more costly despite involving fewer records.

Segmenting Conversions for Deeper Insight¶

Analyze conversion rates across these dimensions to uncover hidden patterns:

By lead source: Inbound leads typically convert MQL-to-SQL at 35-50%, while outbound converts at 15-25% but may close at higher rates
By deal size: Segment into SMB, mid-market, and enterprise tiers
By rep tenure: Reps with less than 6 months experience often show 20-30% lower Discovery-to-Proposal conversion
By industry vertical: Regulated industries often stall at Negotiation due to procurement complexity

The Actionable Recommendations Framework¶

For each identified leak, build a structured response:

Quantify: Calculate the quarterly revenue impact of the leak
Diagnose: Interview reps, review lost deal notes, and analyze time-in-stage data
Hypothesize: Propose a specific root cause (e.g., “Proposals lack ROI modeling, causing CFO rejection”)
Intervene: Design a targeted fix - new enablement content, process change, or qualification criteria update
Measure: Set a 90-day conversion target and track weekly progress

For example, one mid-market SaaS company discovered their Discovery-to-Proposal conversion was 41% versus a 55% benchmark. Root cause analysis revealed reps were sending proposals before confirming budget authority. Adding a mandatory budget confirmation field to the Discovery stage increased conversion to 57% within one quarter.

Key Takeaways¶

Prioritize funnel leaks by revenue impact, not by volume of lost deals - late-stage leaks are almost always more costly
Segment conversion rates by lead source, deal size, rep tenure, and industry to reveal patterns hidden in aggregate data
Use the five-step framework (Quantify, Diagnose, Hypothesize, Intervene, Measure) to turn analysis into action
Revisit funnel benchmarks quarterly - conversion rates drift as your market, product, and team evolve