sales
MQL (Marketing Qualified Lead)
A lead engaged enough to suggest interest but not yet ready for sales contact.
Definition
An MQL is a prospect who has shown interest (downloaded content, attended a webinar, fits ICP) but has not expressed buying intent. Typically the stage before SQL (Sales Qualified Lead). The MQL definition should be specific: e.g., 'matches ICP firmographics AND has visited pricing page OR downloaded a bottom-funnel asset'. Without a clear definition, marketing claims every email signup as an MQL and sales wastes time on cold contacts.
Defining MQL precisely
A useful MQL definition requires both fit criteria (firmographics matching ICP) and intent signals (behavior suggesting buying interest). Example for a US B2B SaaS: company size 50 to 500 employees, US-based, in target industries (SaaS, financial services, professional services), with a contact who has visited the pricing page OR downloaded a bottom-funnel asset (ROI calculator, customer case study, competitive comparison) in the last 30 days. The definition is intentionally restrictive. Without a specific definition, marketing teams claim every newsletter signup as an MQL and sales teams ignore the entire MQL queue. The discipline of agreeing on criteria, in writing, between marketing and sales is the first foundation of pipeline health.
MQL to SQL conversion benchmarks
Healthy US B2B benchmarks. Overall MQL to SQL conversion: 20 to 35 percent. Below 15 percent suggests MQL criteria are too loose (marketing is sending unqualified leads to sales). Above 50 percent suggests criteria are too restrictive (you are missing real leads because the threshold is too high). The ratio also reveals organizational tension: marketing wants to count more MQLs (volume metric); sales wants fewer but better. Resolve through agreed criteria and joint accountability for SQL count, not MQL count alone. The conversion rate should be tracked weekly, with anomalies investigated within the same week.
Scoring fit and intent separately
Most effective US B2B lead scoring uses two separate scores combined. Fit score (0 to 100): firmographics that match ICP. Company size, industry, geography, tech stack, role of contact. Stable; can be set when the lead is created and rarely changes. Intent score (0 to 100): behavior signals over a recency window. Page views weighted by page type (pricing page worth 30, blog post worth 2). Downloads weighted by funnel stage. Email engagement weighted by recency. Volatile; refreshed daily. MQL threshold is fit score above 60 AND intent score above 40, for example. Separating the two scores reveals different problem types: low fit means targeting is off; low intent means content or nurture is weak.
MQL nurture before SQL handoff
Not every MQL is ready for sales immediately. Healthy programs include an MQL nurture track between MQL trigger and SQL handoff, typically 7 to 21 days of additional content, retargeting, and behavior monitoring. The goal: ensure intent is sustained and growing before consuming sales rep time. HubSpot, Marketo, and ActiveCampaign all support automated MQL nurture sequences. The sequence should be value-led (educational content tied to buying problems), not aggressive (no daily sales emails). MQLs that re-engage during nurture become high-quality SQLs; MQLs that disengage drop back to lower scoring and stay in marketing nurture.
FAQ
Who defines MQL criteria, marketing or sales?
Both, together, in writing. Marketing alone defines criteria too loosely (volume incentive); sales alone defines too tightly (preserve rep time). The right process is a joint workshop, usually quarterly, where marketing leads and sales leads agree on fit criteria, intent signals, and the threshold for MQL trigger. The agreement is documented in the CRM and reviewed monthly. Disagreement between marketing and sales on lead quality almost always traces back to undefined or unilateral MQL criteria.
How long should a lead stay an MQL before being downgraded?
Typically 30 to 60 days of inactivity, depending on sales cycle length. For US B2B with 30 to 60 day sales cycles, 30 days is appropriate. For longer enterprise cycles (90 to 180 days), 60 to 90 days. After the window expires without continued intent signals, downgrade back to general lead status and continue with lower-frequency marketing nurture. The downgrade is automatic in HubSpot, Marketo, and similar platforms via workflow rules. Without the downgrade, the MQL pool fills with stale leads and conversion rate drops over time.
What if marketing sends MQLs that sales rejects?
Track rejection reasons in the CRM. Common categories: wrong fit (firmographics did not match), wrong intent (lead was researching, not buying), wrong timing (lead acknowledged future interest only), wrong role (lead was not the decision maker), already a customer, competitor. The rejection reason data drives quarterly MQL criteria refinement. If 40 percent of rejections are wrong-fit, tighten firmographic criteria. If 40 percent are wrong-timing, extend the nurture period before handoff. Without rejection tracking, MQL quality cannot be systematically improved.
Do MQLs apply to small business and self-serve products?
Less formally, but the concept still applies. For self-serve SaaS or e-commerce, the MQL equivalent is product-qualified lead (PQL): a user whose in-product behavior signals buying intent (created multiple workspaces, invited team members, reached usage limits, viewed billing). PQLs trigger sales-assisted outreach for upgrade or expansion. The methodology is the same: combine fit signals (account size, plan, geography) with intent signals (in-product behavior, support tickets) to identify accounts worth direct sales engagement.
What software supports MQL workflows?
Marketing automation platforms with native lead scoring: HubSpot Marketing Hub, Marketo Engage, Pardot (Salesforce Marketing Cloud Account Engagement), ActiveCampaign, Customer.io. All support custom scoring rules, automated MQL trigger, CRM sync, and MQL nurture sequences. For US small business under 5M revenue, HubSpot Pro tier ($800 to $3,000 per month depending on contacts) is the standard answer. For larger enterprises, Marketo or Pardot integrated with Salesforce. Plain CRM without marketing automation can implement basic MQL logic via custom properties but lacks behavior tracking depth.
In your business
- →Define MQL with 4-5 specific criteria
- →Track MQL to SQL conversion rate - under 20% suggests over-loose criteria
- →Score on fit (firmographics) and intent (behavior) separately