SQL stands for Sales Qualified Lead, and it represents the final qualification step before a lead becomes an active opportunity. While marketing qualifies leads based on fit and engagement data (MQL), sales qualifies based on direct conversation and assessment of buying readiness.
The SQL criteria typically assess BANT (Budget, Authority, Need, Timeline) or a similar framework. Does the lead have budget for the purchase? Are they the decision-maker or connected to one? Do they have a genuine need that your product solves? Is there a timeline for making a decision? Sales makes this determination through discovery calls, email exchanges, or other direct interactions.
The MQL-to-SQL conversion rate is one of the most important metrics in the marketing-sales handoff. Industry benchmarks for B2B range from 20% to 40%. A rate below 20% usually means MQL criteria are too loose. A rate above 50% might mean the criteria are too strict (marketing is holding back leads that could convert).
For MOps teams, the SQL stage is important for attribution and funnel reporting even though sales owns the qualification decision. You need to track when leads transition to SQL status, how long the MQL-to-SQL conversion takes, and which marketing sources produce the highest SQL conversion rates. This data feeds back into marketing strategy and lead scoring optimization.
The operational implementation of SQL tracking varies. In Salesforce, it is typically a lead status or opportunity stage. In HubSpot, it is a lifecycle stage. The key is that the transition from MQL to SQL is explicitly recorded with a timestamp so you can measure conversion rates and velocity.