What is a Sales Qualified Lead (SQL)?
A Sales Qualified Lead (SQL) is a prospect that has been vetted by sales and confirmed as a legitimate opportunity worth active pursuit. Unlike a Marketing Qualified Lead (MQL), an SQL typically indicates verified need, fit, and a path to purchase—often after an initial sales conversation.
Common SQL Criteria
Criteria vary by company and segment, but SQLs commonly meet standards such as:
- ICP fit: firmographic and use-case alignment
- Problem + urgency: clear pain and a compelling reason to act
- Stakeholders: known buyer roles and a path to the economic buyer
- Process: an understood decision process and timeline
- Mutual next step: agreed next meeting (demo, technical validation, proposal review)
SQL vs Opportunity
Some teams use SQL and “opportunity” interchangeably, while others treat SQL as a pre-opportunity stage. The key is consistent definitions—otherwise pipeline metrics and conversion rates become unreliable.
Why SQL Definition Matters
- Pipeline quality: clear criteria prevents low-quality deals entering pipeline.
- Forecasting: stronger SQL gates reduce late-stage slippage.
- Sales productivity: reps spend time where win probability is higher.
- Marketing alignment: MQL → SQL conversion reveals lead quality and handoff health.
How to Improve MQL → SQL Conversion
- Tighten ICP targeting: fewer “wrong-fit” leads at the top.
- Improve speed-to-lead: follow up quickly while intent is high.
- Use consistent discovery: standard questions and qualification frameworks reduce variance.
- Close the loop: collect disqualification reasons and feed them back into marketing.
How AI Helps With SQL Qualification
AI can automatically extract qualification signals from calls and emails, flag missing information (stakeholders, success metrics, timeline), and suggest next steps—making qualification more consistent across reps and segments.
help_outlineFrequently Asked Questions
Who should own the definition of an SQL?
Sales and marketing should co-own it. Sales needs to trust it for prioritization, and marketing needs it for measurement. Capture it in an SLA and revisit quarterly.
What’s the difference between SQL and a discovery call?
Some teams define SQL as “scheduled discovery,” while others define SQL after a successful discovery call. Either can work, but it must be consistent so conversion rates and pipeline quality metrics stay meaningful.
What are common reasons a lead is not accepted as an SQL?
Wrong ICP, no clear pain, low urgency, no buyer access, unclear timeline, or mismatched expectations on pricing/implementation. Tracking these reasons helps improve targeting and messaging.
How does SQL quality impact forecasting?
Higher-quality SQLs generally lead to higher win rates and less slippage, which improves forecast accuracy and reduces the pipeline coverage you need to hit quota.