MQL to SQL Conversion Rate Calculator

Calculate the conversion rate from Marketing Qualified Leads (MQLs) to Sales Qualified Leads (SQLs). Measure lead qualification effectiveness.

MQL to SQL Conversion Rate
conversionRate%
% of MQLs that become SQLs
Rejected MQLs
rejectedMqls
MQLs not accepted by sales
💡 MQL to SQL Benchmarks
• Good MQL to SQL rate: 40-50%
• Excellent rate: 50%+
• Below 30% indicates lead quality issues
• Sales and marketing must align on definitions
• Track rejection reasons to improve quality

MQL to SQL Conversion Rate

MQL to SQL conversion rate measures how many marketing-qualified leads are accepted by sales as sales-qualified leads.

Formula

MQL to SQL Rate = (SQLs / MQLs) × 100

Understanding Lead Stages

MQL (Marketing Qualified Lead): Lead that meets marketing criteria based on engagement and fit. Examples: downloaded 3+ content pieces, visited pricing page, opened 5+ emails, matches ICP firmographics.

SQL (Sales Qualified Lead): MQL vetted by sales and confirmed as a legitimate opportunity. Meets BANT criteria (Budget, Authority, Need, Timeline) or similar qualification framework.

Why This Metric Matters

  • Lead Quality Indicator: Low conversion means marketing is passing poor leads
  • Alignment Measure: Shows if sales and marketing agree on definitions
  • Efficiency Signal: Reveals wasted effort on unqualified leads
  • Process Improvement: Identifies where to optimize qualification

Benchmark Targets

Conversion RateAssessmentAction
50%+ExcellentMaintain quality, scale volume
40-50%GoodOptimize scoring model
30-40%FairImprove lead quality or definitions
Below 30%PoorFix alignment or targeting immediately

Common Rejection Reasons

  1. Not in ICP: Wrong company size, industry, or geography
  2. No Budget: Cannot afford solution
  3. No Authority: Contact not a decision-maker
  4. No Need: No pain point or problem to solve
  5. No Timeline: Not buying in near term (6+ months)
  6. Already Solved: Using competitor or built internally

Improving Your Rate

1. Tighten MQL Criteria

Add more qualification signals before MQL status: behavioral (demo request, pricing page visit), firmographic (company size, industry), engagement (email opens, content downloads), intent data (research topics, competitive searches).

2. Create SLA with Sales

Document exactly what makes an MQL. Include: minimum engagement score, required firmographic fit, disqualifying factors, expected response time. Review quarterly and adjust based on SQL feedback.

3. Implement Lead Scoring

Points-based system combining fit and behavior. Example: 20 points for ICP company size, 15 points for pricing page visit, 10 points per content download, 5 points per email open. MQL threshold = 50 points. Adjust weights based on SQL analysis.

4. Add Qualification Step

Insert SDR qualification call before MQL to SQL handoff. Quick 5-minute discovery to confirm BANT criteria before flagging as SQL. Reduces sales time wasted on bad leads.

Frequently Asked Questions

What is the difference between MQL and SQL?

Marketing Qualified Lead (MQL) is a lead that marketing deems ready for sales based on engagement (content downloads, email clicks, website visits). Sales Qualified Lead (SQL) is an MQL that sales has vetted and accepted as a legitimate opportunity based on BANT criteria (Budget, Authority, Need, Timeline) or similar framework.

What is a good MQL to SQL conversion rate?

Good MQL to SQL conversion rate: 40-50%. Excellent: 50%+. Below 30% indicates misalignment between sales and marketing on lead definitions or poor lead quality. B2B SaaS averages 25-35%. Enterprise sales often 15-25% due to stricter qualification. Inbound leads convert 40-60%, outbound 20-40%.

Why is my MQL to SQL conversion rate low?

Six common causes: 1) Misaligned MQL definition (marketing too aggressive), 2) Poor lead scoring (wrong signals tracked), 3) Insufficient lead nurturing before handoff, 4) Sales not following up fast enough, 5) Targeting wrong ICP (ideal customer profile), 6) Sales capacity constraints causing rejection. Track rejection reasons and fix root cause.

How do I improve MQL to SQL conversion?

Seven tactics: 1) Align sales and marketing on MQL definition via SLA, 2) Improve lead scoring model based on SQL patterns, 3) Add more qualification steps before MQL status, 4) Implement lead nurturing programs, 5) Use predictive lead scoring, 6) Add behavior-based triggers (demo requests, pricing page visits), 7) Tighten ICP targeting to reduce noise.

Should I measure SQL to Opportunity conversion too?

Yes! Track full funnel: MQL → SQL → Opportunity → Customer. Typical rates: MQL to SQL 40%, SQL to Opportunity 50%, Opportunity to Customer 25%. This reveals where pipeline breaks down. If SQL to Opp is low (under 30%), sales qualification is poor. If MQL to SQL is low, marketing quality is poor.

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