MQL to SQL conversion rate

This rate shows how many of the leads marketing hands over are good enough for sales to work. It sits at the border between the two teams, which is why it causes more arguments than any other funnel number. The overall conversion rate describes the whole path; this one isolates the handoff.

Example

A B2B SaaS company passes 500 MQLs to sales in March. Sales reviews them and accepts 110 as SQLs; the rest are students, competitors, companies below the target size or people who never answer.

MQL to SQL conversion: 110 / 500 = 22%.

If marketing paid $40,000 for those leads, the cost per SQL is $40,000 / 110, about $364, against $80 per MQL. The figures are illustrative.

How to use it

Write the MQL and SQL criteria down and get both heads to sign them. A marketing and sales SLA is the usual place: it fixes the definitions, how fast sales must respond and how rejected leads go back to marketing with a reason.

Track the rate by source. A webinar channel at 35% (70 SQLs from 200 MQLs) and a lead magnet at 8% (12 from 150) need different decisions, and the blended number hides both.

Review rejection reasons every month. If “no budget” is the reason for most rejections, marketing needs a company size filter. If “no response” leads, check how many leads waited more than 24 hours for a first call.

Common mistakes

• Changing the MQL scoring threshold mid-quarter and comparing the rate with the previous quarter.
• Measuring by calendar month when sales takes 10 to 14 days to qualify. Use cohorts: MQLs created in March and what became of them.
• Letting sales skip leads without a status, so unworked leads count as rejected.
• Rewarding marketing for MQL volume only, which pushes the rate down.

Related terms