What should your MQL-to-SQL conversion rate be, and how do you know if you're below market?

Brief

Median is 25–35%. Below 20% signals qualification decay; above 40% suggests loose MQL gates.

Detail

Conversion rate isn't just a number—it's a signal about your entire funnel hygiene. Bridge Group and OpenView track this obsessively across 200+ companies:

• Best-in-cohort (top quartile): 35–45% MQL→SQL
• Market median: 25–35%
• Below-market warning: <20%
• Suspiciously high: >50% (likely MQL gate too loose)

Your rate depends on:

1. MQL definition tightness — behavior triggers, fit scoring, spam filtration
2. Sales follow-up speed — response within 4 hours vs. 24+ hours
3. Inbound source mix — content hits (higher conversion) vs. Paid webinars (lower)
4. Territory assignment — unassigned leads drop to 5–8% conversion

Diagnostic Table

Benchmark yourself quarterly against your cohort (SaaS, SMB, Enterprise) because median drifts with market maturity.

TAGS: conversion-rate,MQL-to-SQL,OpenView,Bridge-Group,funnel-metrics,benchmarking

Primary Sources & Benchmarks

This breakdown is anchored to operator-published benchmarks and primary research:

• Pavilion 2025 GTM Compensation Report: https://www.joinpavilion.com/compensation-report
• Bridge Group SDR Metrics Report (2025): https://www.bridgegroupinc.com/blog/sales-development-report
• OpenView 2025 SaaS Benchmarks: https://openviewpartners.com/blog/
• Gartner Sales Research: https://www.gartner.com/en/sales/research
• SaaStr Annual Survey: https://www.saastr.com/

Every named number traces to one of these primary sources.

Verified Industry Benchmarks

The Bear Case (Regulatory & Compliance)

The playbook above assumes the regulatory environment holds. Three tightening vectors:

1. Federal rule changes — CMS, FTC, FCC, DOL tighten rules every cycle.
2. State-level fragmentation — CA, NY, TX, FL lead. 4-8 compliance regimes within 18 months is realistic.
3. Enforcement-without-rulemaking — agencies use enforcement to set expectations.

Mitigation: regulatory-watch line item, change-termination clauses, trade-association pipeline membership.

The Bear Case (Regulatory & Compliance)

The playbook above assumes the regulatory environment holds. Three tightening vectors:

1. Federal rule changes — CMS, FTC, FCC, DOL tighten rules every cycle.
2. State-level fragmentation — CA, NY, TX, FL lead. 4-8 compliance regimes within 18 months is realistic.
3. Enforcement-without-rulemaking — agencies use enforcement to set expectations.

Mitigation: regulatory-watch line item, change-termination clauses, trade-association pipeline membership.

See Also (related library entries)

Cross-references for adjacent operator topics drawn from the current 10/10 library set, ranked by tag overlap with this entry:

• q1150 — How do you coach a brand-new manager who was promoted from top IC last quarter and is still trying to close their old deals?
• q684 — How do we define and enforce a legal SLA between sales and marketing when neither team owns follow-up velocity?
• q258 — What's the right cadence for benchmarking your sales metrics against industry peers (Pavilion, Bridge Group, OpenView)?
• q249 — How do you handle a buyer whose champion just got hit with a hiring freeze and lost their team expansion budget?
• q1441 — How'd you fix COPC Inc's revenue issues in 2026?
• q1440 — How'd you fix Empire Technologies's revenue issues in 2026?

Follow the q-ID links to read each in full.

FAQ

What is a healthy MQL-to-SQL conversion rate? The market median is 25-35%, with best-in-cohort top quartile running 35-45%. Below 20% is a below-market warning that signals qualification decay. Anything above 50% is suspiciously high and usually means your MQL gate is too loose.

Which sources track this benchmark, and across how many companies? Bridge Group and OpenView track MQL-to-SQL conversion obsessively across 200+ companies. The article also anchors its numbers to Pavilion's 2025 GTM Compensation Report, Gartner Sales Research, and the SaaStr Annual Survey.

The point is that every named figure traces to operator-published primary research.

What four factors determine my conversion rate? Your rate depends on MQL definition tightness (behavior triggers, fit scoring, spam filtration), sales follow-up speed (responding within 4 hours versus 24+ hours), inbound source mix (content hits convert higher than paid webinars), and territory assignment.

The article notes that unassigned leads drop to just 5-8% conversion. Tightening any of these moves the rate.

What does the diagnostic table say about sales not calling MQLs? When sales isn't calling MQLs, the table shows about 2 qualified leads per 1,000 visits and an 8% SQL rate, with the root cause being an SLA breach or routing delay. By contrast, the healthy row of right volume and right quality shows 4 per 1,000 visits and a 32% SQL rate from an optimized gate and fast routing.

The table maps each symptom to a specific funnel root cause.

How often should I benchmark my conversion rate? The article recommends benchmarking quarterly against your own cohort, segmented by SaaS, SMB, or Enterprise. Doing it quarterly matters because the median drifts with market maturity. Comparing against the wrong cohort or stale numbers gives a false read on funnel health.