Sales Qualified Lead (SQL)
B2B & Lead GenDefinition
A sales qualified lead (SQL) is a prospect that sales has accepted as worth active selling, because they show real buying intent, fit your ideal customer profile and are ready for a direct conversation. An SQL sits one step beyond a marketing qualified lead (MQL): the MQL showed interest, the SQL has been vetted and is ready to enter the sales process.
The SQL is the moment a lead stops being a marketing metric and becomes a sales opportunity. An MQL has raised a hand by downloading something, requesting a demo or hitting a lead score threshold. An SQL has cleared a higher bar: sales has looked at the fit and timing, confirmed there is a real need, budget potential and authority in play, and agreed to work the deal. Drawing that line clearly is what stops the endless argument where marketing claims it sent plenty of leads and sales claims none of them were any good.
A useful SQL definition is written down and shared, not left to gut feel. Many teams use a simple framework (need, budget, authority, timing) plus firmographic fit, and require that sales formally accepts the lead before it counts. The discipline matters because every lead pushed to sales too early wastes a rep's time and erodes trust in marketing's leads, while leads held back too long go cold. The SQL stage exists to make the handoff explicit and measurable rather than informal and disputed.
In practice, leads flow from MQL to SQL through a quick qualification step: a sales development rep reviews or calls the MQL, checks it against the agreed criteria, and either accepts it as an SQL that enters the pipeline or sends it back to marketing for more nurturing. CRM stages, lead scoring and clear ownership keep this clean, so you can report exactly how many MQLs convert to SQLs and how many SQLs turn into opportunities and deals.
SQLs matter because they connect marketing spend to revenue. Counting MQLs alone is misleading: you can generate cheap MQLs all day that never become customers. The MQL-to-SQL conversion rate exposes whether your top-of-funnel is attracting the right people, and the SQL-to-deal rate shows whether sales can close them. Optimising paid campaigns toward SQLs and pipeline rather than raw lead volume is what aligns budget with the outcomes the business actually pays for.
Example
Marketing sends 100 MQLs in a month; sales accepts 30 of them as SQLs after qualification, an MQL-to-SQL rate of 30% that tells you the top-of-funnel quality is solid.
If only 8 of those 100 MQLs become SQLs, the lead source or targeting is attracting the wrong people, and the fix is upstream in the campaign, not harder selling.
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Frequently Asked Questions
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An MQL has shown interest and meets marketing's criteria, such as a lead score threshold or a demo request. An SQL is an MQL that sales has reviewed and accepted as worth pursuing, because it fits the ideal customer profile and shows real buying readiness. The MQL is interest; the SQL is a vetted opportunity.
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Sales does, but against criteria agreed jointly with marketing. The best teams write down a shared definition (fit plus need, budget, authority and timing) and require sales to formally accept the lead. That shared standard removes the guesswork and the blame game over lead quality.
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Because raw lead counts hide quality. You can buy cheap leads that never convert. Tracking the MQL-to-SQL and SQL-to-deal rates shows whether your campaigns attract the right buyers and lets you optimise spend toward pipeline and revenue rather than vanity volume.
Generate leads sales actually wants
We build B2B campaigns and tracking around SQLs and pipeline, not raw lead counts, so marketing and sales finally agree on what a good lead looks like.