What is SQL?
A lead that sales has accepted as worth active pursuit.
An SQL, sales qualified lead, is a lead that your sales team has reviewed and agreed is ready for direct sales conversation, having passed whatever criteria you've set for fit and intent. It sits a step further along than a marketing qualified lead (MQL), which marketing believes is worth following up on. The SQL label means sales has actually agreed, not just marketing hoping.
Why SQL matters
The MQL to SQL handoff is where a lot of marketing and sales tension lives. Marketing wants credit for generating volume, sales only wants leads worth their time, and without a clear, mutually agreed definition of what counts as sales-qualified, both teams end up arguing over quality instead of working from the same standard. Getting this definition right fixes most of that friction.
Tracking SQL volume and conversion rate separately from MQL volume also gives you an honest read on lead quality, not just lead quantity. A campaign that generates hundreds of MQLs but very few SQLs is producing noise, while one that generates fewer MQLs but a high proportion convert to SQL is finding the right people, even if the raw numbers look smaller.
How SQL works in practice
- 01Agree a written definition of SQL criteria jointly between marketing and sales, covering fit, budget, and buying intent.
- 02Build the qualification criteria into your CRM as explicit fields, not a vague gut-feel judgement made inconsistently.
- 03Track MQL to SQL conversion rate by source, so you know which channels produce leads sales actually wants.
- 04Review disagreements about SQL status regularly with both teams, since these disagreements usually reveal a criteria problem.
- 05Report SQL volume and conversion rate to leadership alongside MQL volume, not instead of it, so quality is visible.
Common mistakes
- ·Marketing and sales never actually agree a shared SQL definition, so each side judges lead quality by a different standard.
- ·Teams track only MQL volume and celebrate it, ignoring that a shrinking share are converting to SQL.
- ·Sales rejects leads without recording a reason, so marketing can't learn what's actually wrong with lead quality.
- ·Nobody revisits the SQL criteria as the business or ICP changes, so the definition slowly goes stale.
How to measure SQL
Track MQL to SQL conversion rate by lead source and by campaign, and track SQL to closed-won rate as the ultimate quality check. A healthy funnel shows both stages improving or holding steady together; if MQL volume grows but SQL conversion falls, the extra volume is likely lower quality. Review this monthly with both marketing and sales present.
What good looks like
A well-functioning SQL process has a written, specific definition both teams agree on, tracked consistently in the CRM rather than judged case by case. Sales trusts that an SQL is genuinely worth their time, which keeps the relationship with marketing collaborative rather than adversarial. MarketJargon can run a lead scoring and CRM hygiene agent to keep this handoff consistent.
The agent that runs SQL
SQL questions, answered
What's the difference between an MQL and an SQL?
An MQL is a lead marketing believes is worth following up on, based on engagement and fit signals. An SQL is a lead sales has reviewed and agreed is genuinely ready for a direct sales conversation.
Who should own the SQL definition, marketing or sales?
Both, jointly. It needs to reflect what marketing can realistically identify from available data and what sales actually finds worth their time, so it should be built and revisited together, not imposed by one side.
How many SQLs should a campaign produce?
There's no universal benchmark, since it depends entirely on deal size, sales cycle, and industry. The more useful comparison is your own SQL conversion rate over time and across channels.
What happens if sales keeps rejecting marketing's SQLs?
It usually means the criteria are wrong or being applied inconsistently. Treat repeated rejections as a signal to revisit and tighten the definition together, rather than a sign either team is failing.
Related terms
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