What is a good sales qualified lead rate?

Blended MQL-to-SQL medians sit near 13.0%, with inbound and demo requests running higher and cold lists lower. Below roughly 8% is weak, 8 to 14% is workable, and above 20% is strong.

How is SQL rate calculated?

Divide sales qualified leads by total leads and multiply by 100. For 130 SQLs from 1,000 leads the rate is 13.0%.

What separates an SQL from a regular lead?

An SQL has cleared agreed qualification criteria — fit, intent, and readiness — and been accepted by sales as worth active pursuit, rather than simply having submitted a form.

Why is my SQL rate low?

Typically source mix or loose targeting: channels misaligned with the ideal customer profile produce volume that fails qualification. Tightening sources usually lifts the rate more than relaxing criteria.

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Sales Qualified Lead Rate Calculator

Measure what share of leads clear qualification into sales-ready opportunities — and decide whether to refine targeting, tighten scoring, or feed sales more volume.

Leads

leads

Sales qualified leads

count

Sales qualified lead rate

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Average

Scenario lens Current · Benchmark · Optimized

Value / conversion

Leverage

Formula

SQL rate = Sales qualified leads / Leads × 100

Understanding sales qualified lead rate

Reference material — the calculator above stays the primary tool.

What SQL rate measures

Sales qualified lead rate is the share of leads that pass qualification and are accepted by sales as worth pursuing. It sits between raw lead volume and closed revenue, measuring how well the top of the funnel produces opportunities the sales team will actually work rather than discard.

It is the cleanest single read on lead quality: a high lead count with a low SQL rate means marketing is generating volume that sales cannot use, regardless of how the headline number looks.

How to read your result

The result is labelled against a fixed benchmark so the number resolves into a decision:

Low — well under the median; targeting or qualification criteria are letting through poor-fit leads. Average — near the median; sharpening scoring and source mix pays off. Strong — at or above the median; lead quality is high, so scaling volume feeds sales efficiently.

SQL rate benchmarks by source

Qualification yield tracks channel intent and scoring strictness. Treat these as orientation, not targets — your own funnel history is the better comparison.

Context	Typical median
Inbound / demo requests	20–30%
Content / gated leads	10–15%
Paid search leads	8–14%
Cold outbound / list leads	3–7%

Levers that lift SQL rate

Qualification yield rises with sharper inputs more than with looser criteria: align lead sources to the ideal customer profile, agree explicit scoring thresholds between marketing and sales, gate higher-intent forms, and feed disqualification reasons back into targeting. A rising SQL rate with steady volume is the signal that quality is improving. Model the change as a scenario above.

Is a higher SQL rate always better?

Not if it comes from loosening the bar. Read SQL rate alongside lead conversion and cost per lead — the related tools cover those. An SQL rate that climbs while close rates fall means qualification has been relaxed, not improved, so confirm accepted leads still convert downstream.