Marketing qualified lead (MQL)

A Marketing Qualified Lead (MQL) is a prospect that marketing has evaluated and flagged as more likely to become a customer based on preset criteria such as pages viewed (e.g., pricing), content downloaded, or campaign engagement. MQLs meet the bar to be passed to sales for further qualification. 

Why It Matters

  • Focuses sales time: Clear MQL rules send sellers higher-intent prospects instead of raw inquiries. 

  • Creates a clean handoff: Shared definitions (MQL → SQL) reduce back-and-forth and improve pipeline quality. 

  • Enables measurement: Teams can track MQL volume, acceptance rate, and conversion to opportunity/revenue to improve programs.

Examples

  • B2B SaaS: A visitor reads 2 product pages, downloads a comparison guide, and returns to the pricing page. They cross your scoring threshold and are labeled MQL → routed to sales for follow-up. 

  • Event marketing: Someone attends a webinar and clicks a demo CTA. They meet your fit + engagement criteria and become an MQL; sales qualifies them to SQL after a discovery call. 

How MQLs Are Determined (Common Signals)

  • Behavioral: key pages (pricing, demo), downloads, webinar/ebook registrations, repeat visits, email engagement. 

  • Fit: ICP match (industry, company size, role). Often combined via lead scoring (fit + behavior). 

  • Lifecycle context: New vs. returning, campaign influence, channel.

  • Sales feedback loop: Thresholds are tuned using sales acceptance and close-rate data. 

Best Practices

  1. Co-define MQL & SQL with sales. Write a short SLA: what qualifies as MQL, who acts, and response-time targets (speed-to-lead matters). 

  2. Use lead scoring. Blend fit (ICP) and engagement (behavior) to set an objective threshold for MQL. Review quarterly. 

  3. Prioritize high-intent behaviors. Pricing views, product trials, and bottom-funnel downloads should weigh more than top-funnel clicks. 

  4. Tighten the handoff. When a lead hits MQL, route it immediately and capture disposition (accepted → SQL, recycled, disqualified) to improve the model. 

  5. Measure beyond volume. Track MQL→SQL acceptance, opportunity rate, win rate, and pipeline/revenue, not just MQL count. 

  6. Refine with discovery frameworks. Sales can qualify MQLs using BANT (Budget, Authority, Need, Timeline) or similar frameworks before promotion to SQL. 

Related Terms

  • Sales Qualified Lead (SQL) 

  • Lead Scoring 

  • BANT 

  • Lead Routing / SLA

FAQs

Q1. MQL vs. SQL; what’s the difference?
MQL = marketing-qualified by preset criteria/score and ready for sales outreach. SQL = sales has done discovery and confirmed real buying intent (moves into the pipeline). 

Q2. Who decides the MQL criteria?
Marketing and sales together. Start with best-guess thresholds, then tune using acceptance rates, opportunity rates, and wins. 

Q3. What’s a good response time for MQLs?
As fast as possible. Research shows many firms wait too long, fast follow-up correlates with higher connection and qualification rates. Set speed-to-lead SLAs. 

Q4. Should every content download be an MQL?
No. Weight bottom-funnel actions (pricing/demo) more than generic downloads. Use scoring so only qualified prospects hit MQL. 

Q5. Can MQLs exist without a CRM?
You’ll get better results with a MAP + CRM setup (e.g., HubSpot/Salesforce) that tracks engagement, scores leads, and routes them instantly. 



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