MQL vs SQL
| Aspect | MQL (Marketing Qualified Lead) | SQL (Sales Qualified Lead) |
|---|---|---|
| Definition | Engaged with marketing content | Ready for sales conversation |
| Qualification | Behavioral scoring (downloads, visits) | BANT/MEDDIC criteria met |
| Owner | Marketing team | Sales team |
| Conversion Rate | ~15-30% to SQL | ~20-30% to Opportunity |
| Typical Volume | Higher volume, lower quality | Lower volume, higher quality |
💡TL;DR
MQL = marketing says "worth pursuing" based on engagement (downloads, webinars, page visits). SQL = sales says "ready to buy" after qualifying (budget, authority, need, timeline). Key metrics: MQL-to-SQL conversion (target: 20-30%), SQL-to-Opportunity (target: 30-50%). Common problems: marketing passes weak MQLs, sales ignores good ones. Fix with clear SLAs: sales must follow up within 24 hours, marketing must hit quality thresholds.
Definition
MQL (Marketing Qualified Lead) is a lead that has engaged with marketing content and meets basic demographic criteria. SQL (Sales Qualified Lead) is a lead that sales has vetted and confirmed has budget, authority, need, and timeline. The MQL-to-SQL handoff is where most lead leakage occurs.
🏢What This Means for SMB Teams
SMBs often skip the MQL stage entirely—founders handle both marketing and sales. As you grow, define clear MQL criteria to prevent sales from drowning in unqualified leads. Start simple: 2-3 engagement criteria + 1-2 firmographic filters.
Connect marketing signals to sales actions. Zero handoff friction.
Marketing generates intent, sales captures revenue—in sync.
📋Practical Example
A 55-person B2B SaaS ($9M ARR) had MQL-to-SQL conversion of only 8%—sales complained about lead quality. Analysis revealed marketing was scoring anyone who downloaded a whitepaper as MQL. They tightened criteria: MQL now requires 3+ content engagements AND company size 50-500 employees AND visited pricing page. Volume dropped 60%, but MQL-to-SQL jumped to 28%. Sales trusted leads more, response time improved from 18 hours to 4 hours, and pipeline grew 35%.
🔧Implementation Steps
- 1
Define MQL criteria: 2-3 behavioral triggers + 1-2 firmographic filters.
- 2
Define SQL criteria: BANT minimums (e.g., budget >$10k, timeline <6 months).
- 3
Set SLAs: sales follows up MQLs within 24 hours, dispositions within 48 hours.
- 4
Track MQL-to-SQL conversion weekly; investigate drops below 20%.
- 5
Hold monthly marketing-sales alignment meetings to calibrate definitions.
❓Frequently Asked Questions
What's a good MQL-to-SQL conversion rate?
20-30% is healthy for B2B SaaS. Below 15% indicates MQL criteria are too loose; above 40% might mean you're being too restrictive and missing opportunities. Benchmark against your own trends, not just industry averages.
Should we use SAL (Sales Accepted Lead) between MQL and SQL?
SAL adds clarity for high-volume teams. It means sales acknowledged the lead but hasn't fully qualified yet. For SMBs with <1000 leads/month, MQL→SQL is usually sufficient. Add SAL when you need to track sales response time separately.
⚡How Optifai Uses This
Optifai scores leads automatically using engagement signals and firmographic data. It tracks MQL-to-SQL conversion by source, alerts when rates drop, and suggests criteria adjustments based on closed-won patterns.
📚References
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Related Terms
MQL (Marketing Qualified Lead)
A lead that has shown enough engagement with marketing content to be considered sales-ready based on predefined criteria. MQLs typically meet demographic fit (ICP match) and behavioral thresholds (downloads, page views, email engagement). Marketing hands MQLs to sales for follow-up.
SQL (Sales Qualified Lead)
A lead that sales has accepted and confirmed as worth pursuing through direct qualification. SQLs have passed BANT or similar criteria (Budget, Authority, Need, Timeline) during a conversation. SQLs enter the active pipeline as opportunities.
SAL (Sales Accepted Lead)
A lead that sales has agreed to follow up on after receiving from marketing, but before full qualification. SAL is the interim stage between MQL and SQL, representing sales acknowledgment that the lead meets basic criteria worth investigating.
Lead Scoring
A methodology for ranking prospects based on their perceived value to the organization, using demographic/firmographic attributes and behavioral signals to prioritize sales outreach.
BANT (Budget, Authority, Need, Timeline)
A sales qualification framework developed by IBM. Assesses four criteria: Budget (can they afford it?), Authority (are you talking to the decision-maker?), Need (do they have a problem you solve?), Timeline (when do they need to decide?). Used to determine if a lead is worth pursuing.