Growth wiki

MQL

Flag leads who meet defined engagement or fit criteria, creating a qualified handoff between marketing and sales for efficient follow-up.

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Definition

MQL

A Marketing Qualified Lead (MQL) is a lead that has met specific criteria indicating sufficient interest and fit to warrant sales attention, though not yet vetted through direct sales conversation. MQL definitions vary by organisation but typically combine explicit signals (form submissions, demo requests, content downloads) with implicit behaviour (repeated website visits, email engagement, pricing page views) and firmographic fit (company size, industry, role). The threshold separating ordinary leads from MQLs should be empirically derived: analyse which behaviours and characteristics correlate with eventual sale, then set MQL criteria accordingly. Common frameworks include lead scoring systems that accumulate points for various actions and attributes, triggering MQL status when scores cross a defined threshold. The MQL stage exists to filter high-volume lead flow, ensuring sales teams receive prospects worth their time rather than drowning in unqualified contacts. Clear MQL definitions create accountability: marketing owns MQL volume and quality; sales owns MQL-to-opportunity conversion.

Importance

Why this matters

MQls matter because they create the crucial handoff point between marketing and sales, establishing shared definitions that eliminate the finger-pointing plaguing most revenue organisations. Without MQL criteria, sales complains that marketing sends rubbish leads whilst marketing insists sales doesn't follow up properly—both often correct because there's no agreed qualification standard. MQL definitions force the question: what does a good lead actually look like? This forces both teams to examine conversion data honestly rather than operating on hunches. For marketing, MQL targets provide clear success metrics beyond vanity measures like website traffic; marketing can optimise specifically for MQL volume and cost-per-MQL rather than vague engagement. For sales, consistent MQL quality means their pipeline is full of genuinely viable prospects rather than tyre-kickers and early-stage researchers. The staging also improves customer experience: leads receive appropriate nurture based on their readiness, avoiding aggressive sales outreach when they're merely researching or gentle nurture when they're actively comparing vendors. Organisations implementing robust MQL frameworks report 25-40% increases in sales productivity because reps spend time exclusively on qualified opportunities rather than sifting through raw leads. The definition also highlights where processes break: if MQL volume is strong but conversion to opportunity is weak, you've got lead quality problems; if opportunities convert well but MQL volume is low, you need more top-of-funnel activity.

Introduction

Introduction to

MQL

An MQL is a lead whose behaviour and fit suggest that speaking to sales would feel natural rather than intrusive. In other words, marketing has collected enough signals—page views, downloads, role, company size—to believe the person could buy within a sensible timeframe.

  • A SaaS finance director who attended a live ROI webinar and downloaded the pricing sheet.
  • A manufacturing COO who spent ten minutes on your case-study library and booked a product-tour slot.

Both have crossed the invisible line between casual interest and genuine consideration, so they earn the “Marketing-Qualified” badge in the CRM.

What is not an MQL?

  • A student using a generic Gmail address to grab your ebook.
  • A competitor’s intern subscribing to your newsletter.
  • A CEO who skimmed one blog post and vanished.

Those contacts may stay in nurture lists, but until they show stronger intent or a closer ICP fit, they remain ordinary leads.

HubSpot lets you build smart lists: “Lifecycle stage → Lead” AND “Page views ≥ 3” AND “Persona = Finance leader”.

Pipedrive makes you push a Lead into a Pipeline stage once it earns MQL status—simple but stops leakage.

Example 1

Example 2

Example 3

How to use it

How to apply

MQL

Key concepts and frameworks explained clearly. Quick reference when you need to understand a term, refresh your knowledge, or share with your team.

See entire growth wiki

Define crisp fit and engagement criteria

Start with your ICP spreadsheet: target industries, firm size, tech stack, job titles and regions. Add engagement milestones that show genuine intent—pricing page view, webinar attendance, asset download, chatbot question. Publish the matrix so everyone can reference it.

Example (digital agency):

  • Fit: SaaS, 10–200 employees, C-level or VP Marketing.
  • Engagement: Viewed portfolio page + downloaded case study OR booked a 15-min discovery via Calendly.

Build a transparent lead-scoring model

Assign numeric weights. Fit traits might contribute 60 %, engagement 40 %. A finance director from a 150-employee SaaS gets 50 fit points; attending a live demo adds 40 intent points, totalling 90—above the 75-point MQL threshold. Use HubSpot’s native scoring or a Zapier pipe feeding Pipedrive custom fields. Keep the formula public so sales trusts the math.

Automate alerts and routing

When a lead crosses the threshold, trigger:

  • Slack ping to the assigned SDR.
  • Auto-creation of a task “Call within 24 h”.
  • Removal from generic nurture sequences.
  • Speed matters—responses within one hour can double connection rates. Automations guarantee no hot lead languishes in a spreadsheet.

Nurture leads falling just short of MQL status

A CTO who scored 60/75 may need a nudge: invite to a technical webinar, send a focused case study, or offer a no-obligation audit. Marketing automation (HubSpot workflows, ActiveCampaign, Customer.io) drips value until the lead self-qualifies.

Review and refine every quarter

Pull conversion data: Lead → MQL, MQL → SQL, SQL → Closed-Won. If MQL-to-SQL is under 20 %, fit criteria are too loose; tighten industry filters or raise the score threshold. If conversion is over 60 % but MQL volume starves sales, loosen criteria or create fresh engagement hooks. Continuous calibration keeps quality and quantity in balance.

Practical examples

Architecture firm: Fit—property developers with ≥ £5 m build budget; Engagement—download BIM integration checklist.

Bookkeeping agency: Fit—UK SaaS, ARR £1–10 m, Finance Lead; Engagement—uploads trial data + views pricing.

Cyber-security MSP: Fit—Healthcare or fintech; Engagement—attends “Zero-trust roadmap” webinar + requests breach-cost calculator.

Documenting these rules in the CRM and living by them ensures every MQL handed to sales is truly worth a call—raising pipeline accuracy, win rates and team trust across the funnel.

Books

Relevant books for

MQL

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Spin selling
Book summary & review

Spin selling

Neil Rackham

A clear walkthrough of Situation, Problem, Implication, Need payoff with examples that match complex deals.

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Sales enablement

Equip your sales team with a structured system that shortens cycles, lifts win rates and compounds revenue.

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Course

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Flag leads who meet defined engagement or fit criteria, creating a qualified handoff between marketing and sales for efficient follow-up.

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