A sales qualified lead (SQL) is a prospective customer that has been researched and vetted by marketing and/or SDRs and meets the criteria to be pursued by an account executive.
An SQL has progressed beyond initial interest (MQL stage) and meets qualification criteria like budget, authority, need, and timeline. The handoff from marketing or SDR to AE at the SQL stage is one of the most critical transitions in the revenue funnel. Get it wrong and AEs waste time on unqualified conversations while real buyers go uncontacted.
MQL vs SQL
An MQL (marketing qualified lead) has shown interest through actions like downloading content, attending a webinar, or visiting the website multiple times. An SQL has been validated, typically through an SDR conversation or a direct sales interaction, as having genuine buying intent, confirmed budget or budget process, and decision-making authority or access to it. The conversion rate from MQL to SQL is typically 15-30% for well-qualified pipelines. Below 15% usually means marketing is generating low-intent leads. Above 30% might mean marketing's criteria are too strict and they're leaving qualified prospects on the table.
SQL Definition Best Practices
The #1 source of sales-marketing friction is disagreement on what counts as an SQL. Effective CROs establish a Service Level Agreement (SLA) with clear criteria: minimum company size, confirmed budget range, decision timeline, and identified stakeholders. This prevents marketing from passing unqualified leads and sales from rejecting good ones.
Common Mistakes with SQL Definitions
Changing the SQL definition mid-quarter to hit a number. Marketing teams under pressure will loosen criteria to inflate SQL counts, which floods the pipeline with unqualified opportunities. Then sales blames marketing for junk leads, marketing blames sales for not following up, and the CRO spends Q2 rebuilding trust between the two teams. Lock the definition at the start of each year. Review it quarterly, but don't change it just because someone's behind on their metric.
Real-World Example
A B2B SaaS company had a 22% MQL-to-SQL conversion rate. Marketing generated 1,000 MQLs per month, producing 220 SQLs. Sales wanted more pipeline, so the CRO lowered the SQL threshold: any company with 50+ employees that requested content became an SQL. MQL-to-SQL conversion jumped to 45% overnight. But SQL-to-opportunity conversion dropped from 40% to 12%. Net result: fewer actual opportunities than before, plus frustrated AEs spending time on calls that went nowhere. The fix was restoring the original SQL criteria and investing in SDR capacity to better qualify inbound leads.
In Practice
The best SQL definitions include both positive criteria (what makes a lead qualified) and negative criteria (what disqualifies). Positive: company has 100+ employees, confirmed budget exists, decision timeline within 6 months, spoke with a stakeholder at director level or above. Negative: company is in a vertical you don't serve, prospect is evaluating for a project 12+ months out, prospect is a student or consultant doing research. Negative criteria prevent the most common source of sales-marketing conflict: technically qualified leads that waste AE time. Document both lists in a shared SLA that marketing and sales review together quarterly.
