// Glossary · sales

SQL vs MQL

Also: Sales Qualified Lead vs Marketing Qualified Lead · MQL to SQL

MQL is a contact with marketing engagement. SQL has passed handoff criteria and is actively worked by sales. The line between them is where most pipeline arguments happen.

A Marketing Qualified Lead is a contact who has shown enough marketing engagement to be worth a sales conversation. Downloaded a whitepaper, attended a webinar, hit a lead score threshold, requested a demo. A Sales Qualified Lead is a contact who has passed the handoff criteria sales agreed to accept and is now actively being worked toward a deal. The MQL belongs to marketing. The SQL belongs to sales. The handoff between them is the single most contested line in B2B revenue ops, and the place where most attribution arguments live.

The reason the line matters is accountability. Marketing measures itself on MQLs delivered. Sales measures itself on SQLs converted to pipeline. If the handoff criteria are loose, marketing dumps unqualified contacts into the SDR queue and sales burns hours on bad leads. If the criteria are tight, marketing complains that sales is rejecting half the MQLs without working them. The cleanest version of the handoff is a written SLA: marketing commits to volume and quality definition, sales commits to working every SQL within a defined SLA, and both teams review rejections weekly. The AI Ops Department builds the dashboard that surfaces the rejection rate in real time so the argument stops being a vibe.

For funded teams running PLG, the MQL versus SQL framing is incomplete because the most valuable leads are PQLs, not MQLs. A user who hit the activation threshold inside your product has signaled intent more cleanly than any whitepaper download ever will. The healthy modern revenue motion runs three lanes: outbound SQLs sourced by an AI SDR, inbound MQLs sourced by marketing programs, and PQLs sourced by product behavior. Each lane has its own conversion rate, its own handoff criteria, and its own ROI math. Lumping them all under one MQL bucket is what makes pipeline forecasts unreliable.

// Examples
  • A Series B SaaS defines SQL as: ICP-matched, hit lead score 75, requested a demo, confirmed budget. MQL conversion to SQL runs 18%, SQL conversion to pipeline runs 41%.
  • A fintech writes a marketing-to-sales SLA: marketing delivers 200 SQLs per month at 70% acceptance, sales works each one within 24 hours. Quarterly review surfaces criteria drift.
  • A devtool replaces most MQL volume with PQL routing once PLG matures, leaving MQLs as a top-of-funnel awareness signal rather than a primary pipeline source.
// Common questions
Who decides the handoff criteria between MQL and SQL?
Marketing and sales agree on it together, usually documented in a service-level agreement reviewed quarterly. The criteria typically include ICP fit, lead score threshold, intent signal, and a defined disqualification reason. Without written criteria, every rejected lead becomes a political argument instead of a process question.
What is a healthy MQL to SQL conversion rate?
Varies by industry and source. Mid-market SaaS typically sees 13 to 25 percent MQL to SQL conversion. Below 10 percent suggests marketing is sending unqualified leads or sales is being too strict. Above 35 percent suggests the MQL definition is too tight and marketing is leaving volume on the table.
Where do PQLs fit between MQL and SQL?
PQLs usually skip the MQL stage entirely. The product behavior is itself the qualification signal, so a PQL goes directly to sales as a high-intent SQL with usage context attached. Healthy PLG companies treat PQLs as their highest-converting lane, with MQLs as a complementary inbound signal for accounts not yet in product.
How do I diagnose a broken MQL to SQL handoff?
Look at rejection rate and rejection reasons. If sales is rejecting more than 40 percent of MQLs, the criteria are too loose. If the same rejection reason shows up repeatedly (wrong title, wrong company size, no budget), marketing has a targeting problem. Review rejected leads weekly until the pattern surfaces.
// Related terms
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