Marketing Qualified Lead (MQL)
A lead who meets both fit and engagement thresholds agreed between marketing and sales, making them ready for sales follow-up.
A Marketing Qualified Lead (MQL) is a prospect who meets both the fit criteria (right company size, industry, job title) and the engagement threshold (content downloads, demo requests, pricing-page visits) agreed between marketing and sales. MQLs are the handoff point where marketing transitions a lead to sales for direct outreach.
Definition
A Marketing Qualified Lead (MQL) is a prospect who has been scored and deemed ready for sales engagement based on a shared definition between marketing and sales. MQL criteria always combine two dimensions: fit (is this the right kind of buyer — right industry, company size, role, geography?) and engagement (have they taken enough actions — whitepaper download, multiple pricing visits, demo request, webinar attendance — to indicate real interest?). When both thresholds are crossed, the lead is passed to an SDR or AE for direct outreach within an agreed-upon SLA, typically 5 to 15 minutes.
How MQL criteria are defined
A working MQL definition combines explicit fit data (job title, seniority, company size, industry, country) with implicit behavioral data (pages visited, time on site, content downloaded, email engagement, event attendance). Most teams use a scoring model — for example, +20 for visiting the pricing page, +15 for a demo video watch, +10 for a whitepaper, minus points for non-ICP traffic — and set an MQL threshold where the lead is routed to an SDR.
The critical discipline is that marketing and sales sign the definition together and review it quarterly. When MQL to SQL conversion drops below 10%, the definition is usually too loose. When sales stops following up because 'MQLs are dead', the definition is usually right but the routing SLA is broken.
MQL vs SQL vs PQL
An MQL is marketing's call: fit plus engagement is strong enough to warrant outreach. An SQL (Sales Qualified Lead) is sales' acceptance: after qualification, the rep agrees the lead is worth active pursuit and enters it into the pipeline as an opportunity. A PQL (Product Qualified Lead) is a user who has signed up and hit a usage threshold — like inviting teammates, importing data, or exceeding a free-plan limit — indicating they are ready to convert.
Modern B2B funnels often run all three in parallel: inbound MQLs from content and paid, outbound MQLs from intent and visitor identification, and PQLs from a product-led motion. The stronger your signal, the higher the downstream conversion — PQLs typically convert at 5 to 10x the rate of traditional MQLs.
Why it matters
The MQL is the formal handshake between marketing and sales. Without an agreed MQL definition, marketing passes unqualified leads (wasting SDR capacity) or hoards qualified leads (starving pipeline), and every QBR devolves into an argument about lead quality. A tight MQL definition with SLAs is the single biggest lever on sales-and-marketing alignment.
Examples
- Director+ at a 100+ employee company who views pricing three times in a week
- Visitor who downloads a buyer's guide and books a demo in the same session
- Return visitor matching your target industry with 5+ product pages viewed
- Webinar attendee from a target account who also visits case studies post-event
How Bullseye helps
Bullseye generates MQLs the moment a visitor matching your ICP hits a high-intent page — pricing, demo, product comparison. You stop depending on form fills and start acting on real behavioral signals. Leads arrive in your CRM pre-enriched with firmographics, intent data, and the exact pages they viewed, so SDRs can reach out within the SLA with full context.
Frequently asked questions
What is a Marketing Qualified Lead (MQL)?
An MQL is a prospect who meets both fit criteria (right industry, company size, role) and engagement criteria (meaningful actions like pricing visits, demo requests, or content downloads) agreed between marketing and sales. Once a lead crosses the MQL threshold, it is handed to an SDR or AE for direct outreach.
What is the difference between an MQL and an SQL?
An MQL is marketing's judgment that a lead is ready for sales outreach. An SQL (Sales Qualified Lead) is sales' acceptance after qualification — the rep agrees the lead is worth active pursuit and opens an opportunity. MQL is the handoff; SQL is the acceptance.
How do you qualify a marketing qualified lead?
Most teams use a lead-scoring model that combines fit data (title, seniority, company size, industry) with behavioral data (pages viewed, forms filled, emails opened, events attended). When the combined score exceeds an agreed threshold, the lead becomes an MQL and is routed to sales within a short SLA — ideally 5 minutes.
What is a good MQL to SQL conversion rate?
The B2B average is around 13%. Healthy high-performing teams run between 20 and 40% depending on motion. Below 10% usually means the MQL definition is too loose or routing SLAs are broken. Above 50% often means marketing is under-passing leads.
Is an MQL still relevant in a product-led world?
Yes, but it now sits alongside PQLs. Even in product-led motions, high-ACV deals still require sales involvement, and MQLs remain the primary signal for that motion. PLG companies typically run MQLs from content and outbound in parallel with PQLs from usage, routed differently but measured on the same revenue target.
Related terms
Buyer Intent Data
Behavioral signals — website visits, content consumption, search activity, and review-site research — that reveal which accounts are actively evaluating a purchase.
Lead Generation
The set of marketing and sales tactics used to attract strangers and convert them into identified prospects with stated or inferred interest.
Lead Scoring
A methodology for ranking prospects on a numerical scale based on their fit with your ICP and the strength of their engagement or buying signals.
Sales Qualified Lead (SQL)
A lead that sales has formally accepted as worth pursuing after qualifying fit, need, budget, and timing — the handoff from marketing to pipeline.
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