What Is a Marketing Qualified Lead (MQL)? Definition, Examples & How to Convert Them

A marketing qualified lead (MQL) is a prospect who has engaged with your marketing enough to indicate genuine interest, but who is not yet ready for a direct sales conversation. MQLs sit between a raw enquiry and a sales-ready lead: they have raised their hand through content, email, or website behaviour, and deserve active nurturing rather than immediate hand-off to sales.

Getting MQL definition right is one of the highest-leverage alignment tasks a B2B marketing team can do. Done well, it focuses sales effort on the right prospects and gives marketing a measurable output tied directly to revenue. Done poorly, it floods sales with noise and damages trust between the two teams.

What is a marketing qualified lead (MQL)?

A marketing qualified lead is a contact who meets a set of predefined criteria, combining firmographic fit and behavioural engagement signals, that indicate they are more likely to become a customer than an unqualified enquiry.

MQLs are typically identified through a lead scoring model that awards points for:

• Behavioural signals: content downloads, webinar attendance, email clicks, pricing-page visits, demo-page visits, or repeat site visits within a short window
• Firmographic fit: industry, company size, job title, geography, or technology stack matching your ideal customer profile (ICP)

When a contact’s score crosses a threshold agreed between marketing and sales, they are designated an MQL and enter the nurture or handoff process.

Keep in mind what the label does and does not tell you. Forrester’s analysts put it bluntly:

“At best, an MQL is an indication of interest and a potential buying cycle. It’s a signal. It doesn’t necessarily mean that an individual is qualified to buy or that they are a representative of an opportunity.”

Amy Hawthorne and Terry Flaherty, VP, Principal Analysts at Forrester

MQL vs SQL vs PQL

Understanding where an MQL sits relative to other lead types is essential for a clean handoff process and accurate funnel reporting. See also: sales qualified lead (SQL), product qualified lead (PQL), and sales accepted lead (SAL).

Many CRMs track this same progression as a single “lifecycle stage” property on the contact record, moving a contact from Subscriber through Lead, MQL, SQL, Opportunity, and Customer as they move forward. See our guide to customer lifecycle stages for how this CRM property maps to the broader customer journey.

The MQL → SAL → SQL progression is the most common handoff sequence in B2B SaaS. Marketing generates and nurtures MQLs; sales reviews and accepts them (SAL); sales then qualifies further (SQL) before opening an opportunity.

An example of a marketing qualified lead

Sarah Chen is a Head of Marketing at a 200-person SaaS company. She downloads a whitepaper on “B2B Lead Qualification Frameworks”, attends a live webinar on lead scoring, and visits the pricing page twice within the same week. She matches the ICP (SaaS, 50 to 500 employees, marketing leadership). Her cumulative lead score crosses the MQL threshold, triggering an SDR sequence.

This contrasts with a contact who downloads the same whitepaper but works at a five-person agency outside the ICP: same behaviour, wrong fit, so not an MQL.

How to define MQL criteria for your team

There is no universal MQL definition. The right threshold depends on your sales capacity, your conversion rates, and how tightly marketing and sales are aligned. Here is a practical framework:

Step 1: agree on ICP dimensions

Work with sales to define the firmographic floor: minimum company size, target industries, relevant job titles, and any disqualifying factors (e.g. competitor employees, students). A contact who fails the ICP check should never become an MQL regardless of engagement score.

Step 2: map behavioural signals to intent levels

Not all engagement is equal. Assign higher scores to signals closer to purchase intent:

• High intent: pricing-page visit, demo request, contact form submission, free trial sign-up
• Medium intent: webinar attendance, case study download, return visit within 7 days
• Low intent: blog post read, newsletter subscription, social click

Weight them honestly, or the score gets gamed. Mark Roberge, HubSpot’s founding sales leader, found that at HubSpot a demo request closed at about three times the rate of an ebook download, yet both counted as one MQL. When marketing fell behind on its monthly MQL target, the easy option won:

“And as the month went on and marketing fell behind on their SLA, all the calls to actions changed to ebook downloads. And the sales team was like, where are the demo requests?”

Mark Roberge, on HubSpot’s Skill Up podcast

HubSpot’s fix was to value leads by their likelihood to close rather than count them, which is the logic behind scoring high-intent signals higher.

Step 3: set the threshold collaboratively

Run a cohort analysis on past closed-won customers to find the score distribution at the point of first sales contact. Set your MQL threshold at a score that historically correlates with an SQL conversion rate sales agrees is worth their time. Revisit quarterly.

Step 4: document and socialise the definition

Write the MQL definition into your CRM as a formal status, and make sure both marketing and sales can articulate it in the same words. Ambiguity here is a common source of misalignment between marketing and sales.

MQL to SQL conversion

The MQL-to-SQL conversion rate is the percentage of MQLs that sales accepts and advances to a qualified opportunity. It is one of the most important metrics in a B2B conversion funnel.

Benchmarks: published MQL-to-SQL figures vary widely and rarely say who measured them or how, so your own trend is a better guide than any industry number. The most robust data point is a step earlier: SiriusDecisions research found sales accepted only 42% of marketing-sourced leads, against the 85% or more it expected when both teams agree the lead definition (see sales accepted lead for the detail and caveats). If your rate is low or falling, investigate these failure modes:

• Threshold set too low: marketing is passing leads before they have shown sufficient intent. Raise the behavioural score floor.
• ICP not enforced: contacts are scoring highly on behaviour but failing on fit. Add hard-block disqualification rules for out-of-ICP firmographics.
• Speed-to-lead lag: MQLs are sitting in a queue for more than 24 to 48 hours before SDR contact. Intent decays rapidly; automate immediate follow-up.
• Definition drift: the MQL criteria were agreed months ago and no longer reflect what sales actually closes. Revisit the definition in your next marketing and sales alignment review.

The SLA between marketing and sales

A healthy MQL process requires a documented service-level agreement (SLA): marketing commits to delivering a volume of MQLs at a quality level; sales commits to following up within a defined window (typically 24 hours) and providing disposition feedback (accepted, rejected, reason). Without the feedback loop, marketing cannot improve MQL quality over time.

Beyond the MQL: buying groups and opportunities

Some analysts now argue the MQL should not be the main measure at all. Forrester, whose SiriusDecisions Demand Waterfall became the industry standard for B2B demand stages such as the MQL, now recommends tracking buying groups and opportunities instead. Its reasoning is that B2B purchases are made by groups, not individuals: in Forrester’s Buyers’ Journey Survey, 2023, 93% of B2B buyers said they were part of a buying group of two or more people. The survey is Forrester’s own research, and the post does not give a sample size.

“Counting leads does not provide a true indication of success, as they do not directly equate to what actually matters: namely, deals that can be closed.”

Simon Daniels, Principal Analyst at Forrester

You do not need to abandon MQLs to act on this. Tracking how many MQLs turn into opportunities and revenue, and which accounts have several people engaging at once, gets you most of the benefit with the process you already have.

Questions to ask yourself

As a growth or agile marketing professional, pressure-test your MQL process with these questions:

• Does this lead fit our ideal customer profile in terms of industry, company size, and role?
• Has the lead shown high-intent behaviour (pricing-page visits, demo requests, or repeat engagement) rather than passive content consumption?
• Is the lead’s pain point aligned with the problems our product solves?
• Can sales contact this lead within 24 hours of MQL designation?
• Are we tracking MQL-to-SQL conversion rate and feeding disposition data back to marketing?

About Growth Method

Defining and improving MQLs comes down to one thing: connecting marketing activity to the pipeline it actually produces. Growth Method is the practical way to use AI in marketing. Our agents suggest campaigns from your own data, then help you plan, launch and analyse them, with no AI vendor lock-in, security taken care of and humans in the loop. Connect your CRM and analytics, and the agents can find which campaigns produced qualified leads and pipeline, prioritise the next ones, and launch them.

We are on-track to deliver a 43% increase in inbound leads this year. There is no doubt the adoption of Growth Method is the primary driver behind these results.

Laura Perrott, Colt Technology Services

The marketers who win treat qualification like engineers: define the signal, measure it, and iterate until it predicts revenue. Get started and see which of your campaigns produce MQLs that sales wants: free to start, no credit card required.

Frequently asked questions

What is a marketing qualified lead (MQL)?

A marketing qualified lead (MQL) is a prospect who has engaged with a company’s marketing content (such as downloading a guide, attending a webinar, or visiting a pricing page) to a degree that suggests genuine interest, but who has not yet been passed to sales. MQLs are identified through lead scoring based on behaviour and firmographic fit.

How is an MQL different from an SQL?

An MQL is qualified by the marketing team based on engagement signals and fit criteria. A sales qualified lead (SQL) is a prospect that the sales team has reviewed and accepted as ready for a direct sales conversation. The key difference is who owns the qualification and how far along the buying journey the prospect is.

What makes a good MQL?

A good MQL combines firmographic fit (right industry, company size, and role) with behavioural signals that indicate intent, such as multiple content downloads, repeat pricing-page visits, webinar attendance, or a direct demo request. Both dimensions must align; a well-fitting company with zero engagement is not a strong MQL.

What is a typical MQL to SQL conversion rate?

There is no reliable public benchmark: published figures vary widely and rarely say how they were measured, so track your own rate over time instead. If your MQL-to-SQL rate is falling, the most common causes are poorly defined MQL criteria, misalignment between marketing and sales on what “qualified” means, or leads being passed too early.

What is a PQL and how does it differ from an MQL?

A product qualified lead (PQL) is a prospect who has experienced value from the product itself (typically through a free trial or freemium tier) and has hit usage thresholds that predict conversion. Unlike an MQL, which is qualified through marketing content engagement, a PQL is qualified through product usage data. PQLs are common in product-led growth (PLG) companies.

Additional reading

• What is a Marketing Qualified Lead (MQL)?
• Marketing Qualified Leads: What They Are and How to Generate More
• What is a Marketing Qualified Lead? A Complete Guide

See how this topic is trending: Google Trends: MQL