What is a good MQL to SQL conversion rate?
The MQL to SQL conversion rate is the handoff between marketing and sales, and it is where alignment problems show up first. It measures how many marketing-qualified leads sales actually accepts as worth pursuing.
This rate is a two-sided signal. Too low and marketing is passing junk; too high and marketing may be hoarding leads or setting the MQL bar so high that volume suffers.
Short answer
A good MQL to SQL conversion rate is commonly 20 to 40 percent, meaning that share of marketing-qualified leads are accepted by sales as sales-qualified. A low rate usually means MQL criteria are too loose or lead quality is poor. A very high rate can mean marketing is being too conservative about what it passes.
Key takeaways
- Commonly 20 to 40 percent for B2B.
- Low rates mean loose MQL criteria or poor lead quality.
- Very high rates can mean marketing is too conservative.
- It is the core marketing-to-sales alignment metric.
What drives the rate
The rate depends on how MQL and SQL are defined and how well the two teams agree on them. Shared, documented definitions and a feedback loop where sales tells marketing why leads were rejected are what pull the rate into a healthy band.
A rate stuck below 20 percent usually means marketing is optimizing for MQL volume, a vanity metric, rather than for leads sales can actually close.
How Ardovo handles it
Ardovo tracks MQL to SQL conversion by source and campaign so both teams see which programs produce accepted leads. Rook flags sources whose leads look busy but rarely convert, so you stop paying for volume that never becomes revenue.
Frequently asked questions
What is a good MQL to SQL conversion rate?
Commonly 20 to 40 percent for B2B. Below 20 percent usually signals loose MQL criteria or weak lead quality. Above 50 percent can mean marketing is being too conservative and limiting volume.
Why is my MQL to SQL rate so low?
Usually because MQL criteria are too loose, so marketing passes leads that lack real intent or fit. Tighten the definition with sales, add a feedback loop on rejections, and score for fit as well as engagement.
What is the difference between an MQL and an SQL?
An MQL is a marketing-qualified lead that has shown enough engagement to warrant attention. An SQL is a sales-qualified lead that sales has accepted as worth active pursuit. The conversion between them measures handoff quality.